Dhana ya Uigaji

Viumbe · akili na akili zinazowezekana, zilizopangwa kwa ushahidi

Kama dunia ni uigaji, akili zinaweza kuwa miongoni mwa vitu vigumu zaidi kukokotoa ndani yake. Mwongozo huu unaorodhesha visa vinavyojulikana, kutoka seli moja hadi binadamu. Pia unahusu mifumo bandia iliyojengwa hadi sasa, na akili ambazo wanasayansi na wanafalsafa wamependekeza lakini hakuna aliyeziona.

Kila nambari ina chanzo na lebo ya uhakika. imepimwa ni hesabu ya moja kwa moja, makadirio imekokotolewa kutoka data nyingine, na haijahesabiwa inamaanisha hakuna aliyechapisha hesabu. Kama mfumo wowote kati ya hii una uzoefu ni swali tofauti. Ushahidi wake uko chini ya vigezo vya uwezo wa kuhisi na viashiria vya fahamu.

Akili za mtu mmoja mmoja

Niuroni katika gamba la ubongo (mamalia) au pallium (ndege), kiashiria cha anatomia kinachotumika sana cha uwezo wa kiakili. Kipimo cha logarithmiki; nguzo imara ni hesabu, nguzo zenye michirizi ni makadirio au hesabu zinazobishaniwa (†). Reptilia na wanyama wasio na uti wa mgongo hawaonyeshwi, kwa kuwa hakuna hesabu inayolinganishwa.
  1. Orca †bilioni 43.1
  2. Nyangumi rubani mwenye mapezi marefu †bilioni 37.2
  3. Binadamu▲1bilioni 16.3
  4. Pomboo-bandari †bilioni 14.9
  5. Pomboo mwenye pua ya chupa †bilioni 12.7
  6. Nyangumi mwenye mdomo wa Cuvierbilioni 9.1
  7. Sokwe mkubwabilioni 8.5
  8. Orangutanbilioni 8.5
  9. Sokwe mtubilioni 7.4
  10. Pomboo wa kawaidabilioni 6.7
  11. Sili wa kinubibilioni 6.1
  12. Tembo wa Afrika▼1bilioni 5.6
  13. Nyangumi mkubwa wa finbilioni 5.2
  14. Nyangumi wa buluubilioni 5.1
  15. Nyangumi minkebilioni 3.2
Onyesha nambari
#MnyamaGamba au palliumUbongo mzima
1Orca †bilioni 43.1
2Nyangumi rubani mwenye mapezi marefu †bilioni 37.2
3Binadamubilioni 16.3bilioni 86.1
4Pomboo-bandari †bilioni 14.9
5Pomboo mwenye pua ya chupa †bilioni 12.7
6Nyangumi mwenye mdomo wa Cuvierbilioni 9.1
7Sokwe mkubwabilioni 8.5
8Orangutanbilioni 8.5
9Sokwe mtubilioni 7.4
10Pomboo wa kawaidabilioni 6.7
11Sili wa kinubibilioni 6.1
12Tembo wa Afrikabilioni 5.6bilioni 257
13Nyangumi mkubwa wa finbilioni 5.2
14Nyangumi wa buluubilioni 5.1
15Nyangumi minkebilioni 3.2bilioni 57.4
16Nyani wa mzeitunibilioni 2.88bilioni 10.95
17Nyangumi mweupebilioni 2.7
18Nyangumi mbegu mdogobilioni 2.02
19Makao wa buluu na manjanobilioni 1.92bilioni 3.14
20Makaka rhesusbilioni 1.71bilioni 6.39
21Twigabilioni 1.67bilioni 11.21
22Kima-kindibilioni 1.34bilioni 3.25
23Bundi mkubwa wa Eurasiabilioni 1.33bilioni 1.9
24Keabilioni 1.28bilioni 2.15
25Bundi thelujibilioni 1.27bilioni 1.81
26Kunguru mkubwabilioni 1.2bilioni 2.17
27Bundi wa kahawia-njanobilioni 1.15bilioni 1.58
28Kima wa kapuchinibilioni 1.14bilioni 3.69
29Kokatu mwenye kishungi cha salfabilioni 1.14bilioni 2.12
30Kasuku wa kijivu wa Afrikamilioni 850bilioni 1.57
31Kunguru-mshindomilioni 820bilioni 1.51
32Kudu mkubwamilioni 793.07bilioni 6.09
33Bundi mwenye masikio marefumilioni 673milioni 991.31
34Kokatu wa Goffinmilioni 599bilioni 1.16
35Simbamilioni 545.24bilioni 4.67
36Tai mwenye mkia mweupemilioni 542.93bilioni 1.65
37Kunguru wa Ulayamilioni 529bilioni 1.09
38Mbwa wa nyumbanimilioni 526
39Fisi mwenye mistarimilioni 495.28bilioni 3.88
40Kunguru-mdogo wa magharibimilioni 492milioni 967.99
41Mbuni wa kawaidamilioni 479.41bilioni 1.63
42Magpie wa Eurasiamilioni 443milioni 897.27
43Falcon sakermilioni 442.95bilioni 1.2
44Emumilioni 439bilioni 1.34
45Rakunimilioni 437.94bilioni 2.15
46Bundi wa ghalanimilioni 437milioni 689.54
47Bundi mdogomilioni 400.82milioni 585.92
48Tai mweusimilioni 398.9bilioni 1.01
49Bundi mdogo wa Eurasiamilioni 364milioni 533.26
50Kipanga wa kawaidamilioni 351.7bilioni 1
51Rhea mkubwamilioni 330.34bilioni 1.03
52Swani bubumilioni 323.66bilioni 1
53Nguruwe wa nyumbanimilioni 293bilioni 2.22
54Bata-bukini wa kijivumilioni 258.65milioni 738.23
55Dubu wa kahawiamilioni 250.97bilioni 9.59
56Paka wa nyumbanimilioni 250bilioni 1.22
57Marmoseti wa kawaidamilioni 245milioni 638
58Kestrel wa kawaidamilioni 237.9milioni 624.58
59Bata mdogo wa Eurasiamilioni 167.29milioni 375.41
60Kasuku-nyasimilioni 149milioni 321.82
61Bata-bukini mwenye kifua chekundumilioni 148.62milioni 482.71
62Bata wa mbaomilioni 138.21milioni 305.82
63Kipanga mdogomilioni 131.9milioni 350.37
64Bata wa marumarumilioni 130.14milioni 386.92
65Tausi wa Indiamilioni 129.62milioni 570.93
66Kurasow mwenye kishungi cha manjanomilioni 124.62milioni 652.99
67Njiwa wa Victoria mwenye kishungimilioni 118.45milioni 578.7
68Bata-mwitumilioni 112.26milioni 367.47
69Bata mzinga wa porinimilioni 105.65milioni 492.87
70Kipanga wa Eurasiamilioni 87.83milioni 401.75
71Kozi wa Reevesmilioni 80.69milioni 387.17
72Njiwa wa mwambamilioni 72milioni 310
73Sungura wa Ulayamilioni 71.5milioni 513
74Kuku-mwitu mwekundumilioni 60.7milioni 220.84
75Tinamu wa Chilemilioni 59.13milioni 241.37
76Finchi pundamiliamilioni 55.2milioni 135.98
77Tinamu mwenye kishungi mzurimilioni 51.38milioni 217.77
78Njiwa-miti wa kawaidamilioni 51.33milioni 258.68
79Tinamu mwenye kishungi wa quebrachomilioni 48.29milioni 235.67
80Hua wa Kiafrika mwenye kolamilioni 40milioni 139.27
81Kware wa kaskazinimilioni 39.11milioni 148.4
82Kwale wa kijivumilioni 36.88milioni 170.29
83Panyamilioni 31milioni 200
84Kware wa kawaidamilioni 22.57milioni 117.76
85Kware mfalmemilioni 20.52milioni 80.48
86Njiwa wa almasimilioni 18.21milioni 87.88
87Panyamilioni 13.7milioni 70.9
88Panya-fuko asiye na manyoyamilioni 5.31milioni 33.62

Vigezo vinavyofunzika (uzito wa miunganisho), kwa kipimo cha logarithmiki: kila modeli mashuhuri katika hifadhidata ya Epoch AI yenye idadi ya vigezo (imepatikana 3 Oktoba 2026). Nguzo imara ni hesabu ambazo Epoch inaziona za uhakika; nguzo zenye michirizi ni hesabu inazoziona zinazowezekana au za kubahatisha. Nguzo zenye * ni makadirio ya modeli zilizofungwa ambazo wasanidi wake hawachapishi ukubwa wake, yaliyokusanywa 2 Oktoba 2026 kutoka uchambuzi wa watu wengine; kijiti kinaonyesha masafa ya kadirio. Gemini 3 na baadaye: hakuna kadirio lililochapishwa. Safu tupu ni idadi za sinapsi: kigezo kiko karibu na sinapsi kuliko niuroni.
  1. Neokotekisi ya binadamu1.6 × 10¹⁴
  2. GPT-5.5 (OpenAI, 2026) *~4.7 × 10¹²
  3. Claude Fable 5 (Anthropic, 2026) *~3.5 × 10¹²
  4. Grok 3 (xAI, 2025)~3 × 10¹²
  5. Grok 4 (xAI, 2025)~3 × 10¹²
  6. Gemini 2.5 Pro (Google, 2025) *~3 × 10¹²
  7. Kimi K3 (Moonshot, 2026)~2.8 × 10¹²
  8. Qwen 3.8 Max (Alibaba, 2026)2.4 × 10¹²
  9. Qwen3.8-2.4T-A95B (Alibaba, 2026)2.4 × 10¹²
  10. Grok 4.7 (xAI, 2026) *~2.1 × 10¹²
  11. Llama 4 Behemoth (Meta AI, 2025)~2 × 10¹²
  12. GPT-4 (OpenAI, 2023)~1.8 × 10¹²
  13. DeepSeek-V4-Pro (DeepSeek, 2026)~1.6 × 10¹²
  14. LongCat-2.0 (Meituan Inc, 2026)~1.6 × 10¹²
  15. Switch (Google, 2021)1.6 × 10¹²
  16. GLaM (Google, 2021)1.2 × 10¹²
  17. PanGu-Σ (Huawei Noah's Ark Lab, 2023)1.1 × 10¹²
  18. Kimi K2.5 (Moonshot, 2026)~1 × 10¹²
  19. Composer 2 (Cursor, 2026)1 × 10¹²
  20. Kimi K2.6 (Moonshot, 2026)1 × 10¹²
  21. Composer 2.5 (Cursor, 2026)~1 × 10¹²
  22. MiMo-V2-Pro (Xiaomi Corp, 2026)1 × 10¹²
  23. MiMo-V2.5-Pro (Xiaomi Corp, 2026)~1 × 10¹²
  24. M6-T (Alibaba, 2021)~1 × 10¹²
  25. Kimi K2 (Moonshot, 2025)1 × 10¹²
  26. Qwen3-Max (Alibaba, 2025)~1 × 10¹²
  27. Ling-1T (Ant Group, 2025)1 × 10¹²
  28. Kimi K2 Thinking (Moonshot, 2025)~1 × 10¹²
  29. Inkling (Thinking Machines, 2026)~9.8 × 10¹¹
  30. Tencent Hy4 preview (Tencent, 2026)~7.7 × 10¹¹
  31. GLM-5.1 (Z.ai (Zhipu AI), 2026)7.5 × 10¹¹
  32. K-EXAONE 2.0 (LG AI Research, 2026)7.5 × 10¹¹
  33. DeepSeek V4.1 Flash (DeepSeek, 2026)~7.5 × 10¹¹
  34. GLM-5 (Z.ai (Zhipu AI), 2026)~7.4 × 10¹¹
  35. GLM-5.3 (Z.ai (Zhipu AI), 2026)7.4 × 10¹¹
  36. A.X K2 (SK Telecom, 2026)6.9 × 10¹¹
  37. DeepSeekMath-V2 (DeepSeek, 2025)6.8 × 10¹¹
  38. Mistral Large 3 (Mistral AI, 2025)6.8 × 10¹¹
  39. DeepSeek-V3 (DeepSeek, 2024)6.7 × 10¹¹
  40. DeepSeek-R1 (DeepSeek, 2025)6.7 × 10¹¹
Onyesha nambari
#MfumoVigezo vyoteVinavyotumika kwa tokeniMwakaAina
1Neokotekisi ya binadamu1.6 × 10¹⁴1.6 × 10¹⁴sinapsi
2GPT-5.5 (OpenAI, 2026) *~4.7 × 10¹²2026makadirio
3Claude Fable 5 (Anthropic, 2026) *~3.5 × 10¹²2026makadirio
4Grok 3 (xAI, 2025)~3 × 10¹²2025makadirio
5Grok 4 (xAI, 2025)~3 × 10¹²2025makadirio
6Gemini 2.5 Pro (Google, 2025) *~3 × 10¹²2025makadirio
7Kimi K3 (Moonshot, 2026)~2.8 × 10¹²2026makadirio
8Qwen 3.8 Max (Alibaba, 2026)2.4 × 10¹²2.4 × 10¹²2026usanifu haujatajwa
9Qwen3.8-2.4T-A95B (Alibaba, 2026)2.4 × 10¹²9.5 × 10¹⁰2026mchanganyiko wa wataalamu
10Grok 4.7 (xAI, 2026) *~2.1 × 10¹²2026makadirio
11Llama 4 Behemoth (Meta AI, 2025)~2 × 10¹²2025makadirio
12GPT-4 (OpenAI, 2023)~1.8 × 10¹²2023makadirio
13DeepSeek-V4-Pro (DeepSeek, 2026)~1.6 × 10¹²2026makadirio
14LongCat-2.0 (Meituan Inc, 2026)~1.6 × 10¹²2026makadirio
15Switch (Google, 2021)1.6 × 10¹²1.6 × 10¹²2021mchanganyiko wa wataalamu (idadi hai haijachapishwa)
16GLaM (Google, 2021)1.2 × 10¹²1.2 × 10¹²2021mchanganyiko wa wataalamu (idadi hai haijachapishwa)
17PanGu-Σ (Huawei Noah's Ark Lab, 2023)1.1 × 10¹²1.1 × 10¹²2023mchanganyiko wa wataalamu (idadi hai haijachapishwa)
18Kimi K2.5 (Moonshot, 2026)~1 × 10¹²2026makadirio
19Composer 2 (Cursor, 2026)1 × 10¹²1 × 10¹²2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
20Kimi K2.6 (Moonshot, 2026)1 × 10¹²1 × 10¹²2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
21Composer 2.5 (Cursor, 2026)~1 × 10¹²2026makadirio
22MiMo-V2-Pro (Xiaomi Corp, 2026)1 × 10¹²1 × 10¹²2026usanifu haujatajwa
23MiMo-V2.5-Pro (Xiaomi Corp, 2026)~1 × 10¹²2026makadirio
24M6-T (Alibaba, 2021)~1 × 10¹²2021makadirio
25Kimi K2 (Moonshot, 2025)1 × 10¹²1 × 10¹²2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
26Qwen3-Max (Alibaba, 2025)~1 × 10¹²2025makadirio
27Ling-1T (Ant Group, 2025)1 × 10¹²5 × 10¹⁰2025mchanganyiko wa wataalamu
28Kimi K2 Thinking (Moonshot, 2025)~1 × 10¹²2025makadirio
29Inkling (Thinking Machines, 2026)~9.8 × 10¹¹2026makadirio
30Tencent Hy4 preview (Tencent, 2026)~7.7 × 10¹¹2026makadirio
31GLM-5.1 (Z.ai (Zhipu AI), 2026)7.5 × 10¹¹7.5 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
32K-EXAONE 2.0 (LG AI Research, 2026)7.5 × 10¹¹7.5 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
33DeepSeek V4.1 Flash (DeepSeek, 2026)~7.5 × 10¹¹2026makadirio
34GLM-5 (Z.ai (Zhipu AI), 2026)~7.4 × 10¹¹2026makadirio
35GLM-5.3 (Z.ai (Zhipu AI), 2026)7.4 × 10¹¹4 × 10¹⁰2026mchanganyiko wa wataalamu
36A.X K2 (SK Telecom, 2026)6.9 × 10¹¹6.9 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
37DeepSeekMath-V2 (DeepSeek, 2025)6.8 × 10¹¹6.8 × 10¹¹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
38Mistral Large 3 (Mistral AI, 2025)6.8 × 10¹¹4.1 × 10¹⁰2025mchanganyiko wa wataalamu
39DeepSeek-V3 (DeepSeek, 2024)6.7 × 10¹¹3.7 × 10¹⁰2024mchanganyiko wa wataalamu
40DeepSeek-R1 (DeepSeek, 2025)6.7 × 10¹¹3.7 × 10¹⁰2025mchanganyiko wa wataalamu
41SenseChat 5.5 (SenseTime, 2024)6 × 10¹¹6 × 10¹¹2024usanifu haujatajwa
42Step 5 Preview (StepFun, 2026)~6 × 10¹¹2026makadirio
43PaLM-E (Google, 2023)~5.6 × 10¹¹2023makadirio
44Hunyuan-TurboS (Tencent, 2025)5.6 × 10¹¹5.6 × 10¹¹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
45LongCat-Flash (Meituan Inc, 2025)~5.6 × 10¹¹2025makadirio
46Nemotron 3 Ultra (Nvidia, 2026)~5.5 × 10¹¹2026makadirio
47PaLM (Google Research, 2022)5.4 × 10¹¹5.4 × 10¹¹2022mnene
48Minerva (Google, 2022)5.4 × 10¹¹5.4 × 10¹¹2022mnene
49U-PaLM (Google, 2022)5.4 × 10¹¹5.4 × 10¹¹2022mnene
50LMSI-Palm (Google, 2022)5.4 × 10¹¹5.4 × 10¹¹2022mnene
51Flan-PaLM 540B (Google, 2022)5.4 × 10¹¹5.4 × 10¹¹2022mnene
52Megatron-Turing NLG 530B (Microsoft, 2021)5.3 × 10¹¹5.3 × 10¹¹2021mnene
53MegaScale (ByteDance, 2024)~5.3 × 10¹¹2024makadirio
54A.X K1 (SK Telecom, 2025)5.2 × 10¹¹5.2 × 10¹¹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
55Doubao-pro (ByteDance, 2024)~5 × 10¹¹2024makadirio
56Grok 4.20 (xAI, 2026)~5 × 10¹¹2026makadirio
57Qwen3-Coder-480B-A35B (Alibaba, 2025)4.8 × 10¹¹3.5 × 10¹⁰2025mchanganyiko wa wataalamu
58MiniMax-M3 (MiniMax, 2026)4.3 × 10¹¹2.2 × 10¹⁰2026mchanganyiko wa wataalamu
59ERNIE-4.5-VL-424B-A47B (Baidu, 2025)4.2 × 10¹¹4.7 × 10¹⁰2025mchanganyiko wa wataalamu
60Llama 3.1-405B (Meta AI, 2024)4 × 10¹¹4 × 10¹¹2024mnene
61Llama 4 Maverick (Meta AI, 2025)~4 × 10¹¹2025makadirio
62Jamba 1.5-Large (AI21 Labs, 2024)4 × 10¹¹4 × 10¹¹2024mchanganyiko wa wataalamu (idadi hai haijachapishwa)
63Qwen3.5 397B-A17B (Alibaba, 2026)~4 × 10¹¹2026makadirio
64Hunyuan-Large (Tencent, 2024)3.9 × 10¹¹3.9 × 10¹¹2024mchanganyiko wa wataalamu (idadi hai haijachapishwa)
65GLM-4.7 (Z.ai (Zhipu AI), 2025)~3.6 × 10¹¹2025makadirio
66GLM-4.6 (Z.ai (Zhipu AI), 2025)~3.6 × 10¹¹2025makadirio
67GLM-4.5 (Z.ai (Zhipu AI), 2025)3.5 × 10¹¹3.2 × 10¹⁰2025mchanganyiko wa wataalamu
68PaLM 2 (Google, 2023)~3.4 × 10¹¹2023makadirio
69Med-PaLM 2 (Google Research, 2023)~3.4 × 10¹¹2023makadirio
70Nemotron-4 340B (Nvidia, 2024)3.4 × 10¹¹3.4 × 10¹¹2024mnene
71GLM-5.3-Flash (Z.ai (Zhipu AI), 2026)~3.2 × 10¹¹2026makadirio
72Grok-1 (xAI, 2023)~3.1 × 10¹¹2023makadirio
73Motif-3 (Motif Technologies, 2026)3.1 × 10¹¹3.1 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
74SB-LM (Google, 2007)~3 × 10¹¹2007makadirio
75Tencent Hy3 preview (Tencent, 2026)3 × 10¹¹3 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
76Tencent Hy3 (Tencent, 2026)3 × 10¹¹3 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
77DeepSeek-V4-Flash (DeepSeek, 2026)~2.8 × 10¹¹2026makadirio
78Gopher (DeepMind, 2021)2.8 × 10¹¹2.8 × 10¹¹2021mnene
79TML-Interaction-Small (Thinking Machines, 2026)2.8 × 10¹¹2.8 × 10¹¹2026mchanganyiko wa wataalamu (idadi hai haijachapishwa)
80ST-MoE (Google, 2022)~2.7 × 10¹¹2022makadirio
81ERNIE 3.0 Titan (Baidu, 2021)2.6 × 10¹¹2.6 × 10¹¹2021mnene
82Solar Open2 250B (Upstage, 2026)~2.5 × 10¹¹2026makadirio
83Aramco Metabrain AI (Saudi Aramco, 2024)~2.5 × 10¹¹2024makadirio
84Yuan 1.0 (Inspur, 2021)2.5 × 10¹¹2.5 × 10¹¹2021usanifu haujatajwa
85DeepSeek-Coder-V2 236B (DeepSeek, 2024)2.4 × 10¹¹2.4 × 10¹¹2024mchanganyiko wa wataalamu (idadi hai haijachapishwa)
86DeepSeek-V2.5 (DeepSeek, 2024)2.4 × 10¹¹2.4 × 10¹¹2024mchanganyiko wa wataalamu (idadi hai haijachapishwa)
87K-EXAONE (LG AI Research, 2025)2.4 × 10¹¹2.4 × 10¹¹2025usanifu haujatajwa
88Qwen3-235B-A22B (Alibaba, 2025)~2.4 × 10¹¹2025makadirio
89Qwen3-235B-A22B-Thinking (Alibaba, 2025)~2.4 × 10¹¹2025makadirio
90P1-235B-A22B (Shanghai AI Lab, 2025)~2.4 × 10¹¹2025makadirio
91Seed-1.6-Thinking (ByteDance, 2025)2.3 × 10¹¹2.3 × 10¹¹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
92MiniMax-M2 (MiniMax, 2025)2.3 × 10¹¹1 × 10¹⁰2025mchanganyiko wa wataalamu
93MiniMax-M2.1 (MiniMax, 2025)2.3 × 10¹¹2.3 × 10¹¹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
94HyperCLOVA 204B (NAVER, 2021)~2 × 10¹¹2021makadirio
95Amazon Titan (Amazon, 2023)~2 × 10¹¹2023makadirio
96Falcon-180B (Technology Innovation Institute, 2023)1.8 × 10¹¹1.8 × 10¹¹2023mnene
97Jurassic-1-Jumbo (AI21 Labs, 2021)1.8 × 10¹¹1.8 × 10¹¹2021usanifu haujatajwa
98BLOOM-176B (Hugging Face, 2022)1.8 × 10¹¹1.8 × 10¹¹2022mnene
99BLUUMI (University of Turku, 2023)~1.8 × 10¹¹2023makadirio
100InstructGPT 175B (OpenAI, 2022)1.8 × 10¹¹1.8 × 10¹¹2022mnene
101OPT-175B (Meta AI, 2022)1.8 × 10¹¹1.8 × 10¹¹2022mnene
102BlenderBot 3 (McGill University, 2022)~1.8 × 10¹¹2022makadirio
103GPT-3 175B (OpenAI, 2020)1.7 × 10¹¹1.7 × 10¹¹2020mnene
104Palmyra X 004 (Writer, 2024)~1.5 × 10¹¹2024makadirio
105FLAN 137B (Google Research, 2021)1.4 × 10¹¹1.4 × 10¹¹2021usanifu haujatajwa
106LaMDA (Google, 2022)1.4 × 10¹¹1.4 × 10¹¹2022usanifu haujatajwa
107MEB (Microsoft, 2021)1.4 × 10¹¹1.4 × 10¹¹2021usanifu haujatajwa
108Pangu Ultra (Huawei, 2025)1.4 × 10¹¹1.4 × 10¹¹2025usanifu haujatajwa
109DBRX (Databricks, 2024)1.3 × 10¹¹1.3 × 10¹¹2024mchanganyiko wa wataalamu (idadi hai haijachapishwa)
110GLM-130B (Tsinghua University, 2022)1.3 × 10¹¹1.3 × 10¹¹2022mnene
111Pixtral Large (Mistral AI, 2024)1.2 × 10¹¹1.2 × 10¹¹2024usanifu haujatajwa
112Mistral Large 2 (Mistral AI, 2024)~1.2 × 10¹¹2024makadirio
113Qwen3.5-122B-A10B (Alibaba, 2026)~1.2 × 10¹¹2026makadirio
114Galactica (Meta AI, 2022)~1.2 × 10¹¹2022makadirio
115Nemotron 3 Super (Nvidia, 2026)~1.2 × 10¹¹2026makadirio
116gpt-oss-120b (OpenAI, 2025)1.2 × 10¹¹5.1 × 10⁹2025mchanganyiko wa wataalamu
117Telechat2-115B (China Telecom, 2024)1.1 × 10¹¹1.1 × 10¹¹2024usanifu haujatajwa
118Kaiju Large (Character.ai, 2025)~1.1 × 10¹¹2025makadirio
119Llama 4 Scout (Meta AI, 2025)~1.1 × 10¹¹2025makadirio
120InternLM (Shanghai AI Lab, 2023)1 × 10¹¹1 × 10¹¹2023mnene
121Solar Open 100B (Upstage, 2025)1 × 10¹¹1 × 10¹¹2025usanifu haujatajwa
122DLRM-2020 (Facebook AI, 2019)1 × 10¹¹1 × 10¹¹2019mnene
123xTrimoPGLM -100B (Tsinghua University, 2023)1 × 10¹¹1 × 10¹¹2023usanifu haujatajwa
124Yi-Large (01.AI, 2024)~1 × 10¹¹2024makadirio
125VAETKI (NC AI, 2025)1 × 10¹¹1 × 10¹¹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
126ESM3 (EvolutionaryScale, 2024)9.8 × 10¹⁰9.8 × 10¹⁰2024usanifu haujatajwa
127Neokotekisi ya panya8.1 × 10¹⁰8.1 × 10¹⁰sinapsi
128Flamingo (DeepMind, 2022)8 × 10¹⁰8 × 10¹⁰2022mnene
129Qwen3-Coder-Next (Alibaba, 2026)~8 × 10¹⁰2026makadirio
130Qwen2-72B (Alibaba, 2024)7.3 × 10¹⁰7.3 × 10¹⁰2024mnene
131Qwen2.5-72B (Alibaba, 2024)7.3 × 10¹⁰7.3 × 10¹⁰2024mnene
132Qwen2.5 Instruct (Alibaba, 2024)7.3 × 10¹⁰7.3 × 10¹⁰2024mnene
133Qwen-72B (Alibaba, 2023)7.2 × 10¹⁰7.2 × 10¹⁰2023mnene
134Palmyra X 003 (Writer, 2024)~7.2 × 10¹⁰2024makadirio
135Qwen1.5-72B (Alibaba, 2024)7.2 × 10¹⁰7.2 × 10¹⁰2024mnene
136LLaVA-OV-72B (ByteDance, 2024)7.2 × 10¹⁰7.2 × 10¹⁰2024mnene
137NVLM-X 72B (Nvidia, 2024)~7.2 × 10¹⁰2024makadirio
138NVLM-H 72B (Nvidia, 2024)~7.2 × 10¹⁰2024makadirio
139NVLM-D 72B (Nvidia, 2024)7.2 × 10¹⁰7.2 × 10¹⁰2024usanifu haujatajwa
140MindLink-72B (Kunlun Inc., 2025)7.2 × 10¹⁰7.2 × 10¹⁰2025usanifu haujatajwa
141Chinchilla (DeepMind, 2022)7 × 10¹⁰7 × 10¹⁰2022mnene
142Llama 2-70B (Meta AI, 2023)7 × 10¹⁰7 × 10¹⁰2023mnene
143PPLX-70B-Online (Perplexity, 2023)~7 × 10¹⁰2023makadirio
144Llama 3-70B (Meta AI, 2024)7 × 10¹⁰7 × 10¹⁰2024mnene
145ALLaM adapted 70B (Saudi Data and Artificial Intelligence Authority, 2024)7 × 10¹⁰7 × 10¹⁰2024usanifu haujatajwa
146Llama 3.3 70B (Meta AI, 2024)7 × 10¹⁰7 × 10¹⁰2024mnene
147Reka Core (Reka AI, 2024)~6.7 × 10¹⁰2024makadirio
148LLaMA-65B (Meta AI, 2023)6.5 × 10¹⁰6.5 × 10¹⁰2023mnene
149SNM-skip (Google, 2014)~6.2 × 10¹⁰2014makadirio
150PaLI-X (Google Research, 2023)~5.5 × 10¹⁰2023makadirio
151RT-2 (Google DeepMind, 2023)5.5 × 10¹⁰5.5 × 10¹⁰2023usanifu haujatajwa
152RT-2-X (Google DeepMind, 2023)5.5 × 10¹⁰5.5 × 10¹⁰2023usanifu haujatajwa
153NLLB (Meta AI, 2022)5.5 × 10¹⁰5.5 × 10¹⁰2022mnene
154BloombergGPT (Bloomberg, 2023)5.1 × 10¹⁰5.1 × 10¹⁰2023mnene
155M4-50B (Google, 2019)5 × 10¹⁰5 × 10¹⁰2019mchanganyiko wa wataalamu (idadi hai haijachapishwa)
156Mixtral 8x7B (Mistral AI, 2023)~4.7 × 10¹⁰2023makadirio
157AlphaCode (DeepMind, 2022)4.1 × 10¹⁰4.1 × 10¹⁰2022usanifu haujatajwa
158Falcon-40B (Technology Innovation Institute, 2023)4 × 10¹⁰4 × 10¹⁰2023mnene
159Qwen3-Omni-30B-A3B (Alibaba, 2025)3.5 × 10¹⁰3 × 10⁹2025mchanganyiko wa wataalamu
160Yi-34B (01.AI, 2023)3.4 × 10¹⁰3.4 × 10¹⁰2023mnene
161Cambrian-1-34B (New York University (NYU), 2024)3.4 × 10¹⁰3.4 × 10¹⁰2024usanifu haujatajwa
162Oryx 34B (Tsinghua University, 2024)3.4 × 10¹⁰3.4 × 10¹⁰2024usanifu haujatajwa
163Kaiju Medium (Character.ai, 2025)~3.4 × 10¹⁰2025makadirio
164EXAONE 4.5 (LG AI Research, 2026)3.3 × 10¹⁰3.3 × 10¹⁰2026usanifu haujatajwa
165Qwen2.5-32B (Alibaba, 2024)3.3 × 10¹⁰3.3 × 10¹⁰2024mnene
166QwQ-32B (Alibaba, 2025)~3.3 × 10¹⁰2025makadirio
167EXAONE 3.5 32B (LG AI Research, 2024)3.2 × 10¹⁰3.2 × 10¹⁰2024usanifu haujatajwa
168EXAONE Deep 32B (LG AI Research, 2025)3.2 × 10¹⁰3.2 × 10¹⁰2025usanifu haujatajwa
169EXAONE 4.0 (LG AI Research, 2025)3.2 × 10¹⁰3.2 × 10¹⁰2025usanifu haujatajwa
170Olmo 3 (Allen Institute for AI, 2025)3.2 × 10¹⁰3.2 × 10¹⁰2025usanifu haujatajwa
171HyperCLOVA X SEED 32B Think (NAVER, 2025)3.2 × 10¹⁰3.2 × 10¹⁰2025usanifu haujatajwa
172Nemotron 3-Nano-30B-A3B (Nvidia, 2025)~3.2 × 10¹⁰2025makadirio
173Tongyi DeepResearch (Alibaba, 2025)3 × 10¹⁰3 × 10¹⁰2025usanifu haujatajwa
174MM1-30B (Apple, 2024)~3 × 10¹⁰2024makadirio
175Movie Gen Video (Meta AI, 2024)3 × 10¹⁰3 × 10¹⁰2024usanifu haujatajwa
176AgentFounder-30B (Alibaba, 2025)3 × 10¹⁰3 × 10¹⁰2025usanifu haujatajwa
177PLUG (Alibaba, 2021)2.7 × 10¹⁰2.7 × 10¹⁰2021usanifu haujatajwa
178Qwen Image (Alibaba, 2025)2.7 × 10¹⁰2.7 × 10¹⁰2025usanifu haujatajwa
179GenSLM (University of Chicago, 2022)2.5 × 10¹⁰2.5 × 10¹⁰2022usanifu haujatajwa
180ViT-22B (Google, 2023)2.2 × 10¹⁰2.2 × 10¹⁰2023usanifu haujatajwa
181KN-LM (Google, 2007)~2.1 × 10¹⁰2007makadirio
182gpt-oss-20b (OpenAI, 2025)2.1 × 10¹⁰2.1 × 10¹⁰2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
183RNN for 1B words (Google, 2013)~2 × 10¹⁰2013makadirio
184GPT-NeoX-20B (EleutherAI, 2022)2 × 10¹⁰2 × 10¹⁰2022mnene
185UL2 (Google Research, 2022)2 × 10¹⁰2 × 10¹⁰2022usanifu haujatajwa
186Parti (Google Research, 2022)2 × 10¹⁰2 × 10¹⁰2022usanifu haujatajwa
187GPT-3.5 Turbo (OpenAI, 2023)~2 × 10¹⁰2023makadirio
188GPT-3.5 Turbo Instruct (OpenAI, 2023)~2 × 10¹⁰2023makadirio
189SPHINX (Shanghai AI Lab, 2023)~2 × 10¹⁰2023makadirio
190AlexaTM 20B (Amazon, 2022)2 × 10¹⁰2 × 10¹⁰2022usanifu haujatajwa
191CogAgent (Tsinghua University, 2023)~1.8 × 10¹⁰2023makadirio
192Turing-NLG (Microsoft, 2020)~1.7 × 10¹⁰2020makadirio
193CogVLM-17B (Tsinghua University, 2023)1.7 × 10¹⁰1.7 × 10¹⁰2023usanifu haujatajwa
194PaLI (Google, 2022)~1.7 × 10¹⁰2022makadirio
195CodeT5+ (Salesforce, 2023)1.6 × 10¹⁰1.6 × 10¹⁰2023usanifu haujatajwa
196StarCoder (Hugging Face, 2023)1.6 × 10¹⁰1.6 × 10¹⁰2023mnene
197ESM2-15B (Meta AI, 2022)1.5 × 10¹⁰1.5 × 10¹⁰2022usanifu haujatajwa
198FunSearch (Google DeepMind, 2023)~1.5 × 10¹⁰2023makadirio
199NVILA 15B (Nvidia, 2024)1.5 × 10¹⁰1.5 × 10¹⁰2024usanifu haujatajwa
200nekomata-14b (rinna, 2023)1.4 × 10¹⁰1.4 × 10¹⁰2023usanifu haujatajwa
201VILA1.5-13B (Nvidia, 2024)1.3 × 10¹⁰1.3 × 10¹⁰2024usanifu haujatajwa
202VILA-13B (Nvidia, 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023usanifu haujatajwa
203mT5-XXL (Google, 2020)1.3 × 10¹⁰1.3 × 10¹⁰2020mnene
204mT0-13B (Hugging Face, 2022)1.3 × 10¹⁰1.3 × 10¹⁰2022usanifu haujatajwa
205LLaVA (University of Wisconsin Madison, 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023mnene
206InstructBLIP (Salesforce Research, 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023usanifu haujatajwa
207Jais (Cerebras Systems, 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023usanifu haujatajwa
208FinGPT-13B (University of California Los Angeles (UCLA), 2023)~1.3 × 10¹⁰2023makadirio
209Ferret (Columbia University, 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023usanifu haujatajwa
210Skywork-13B (Kunlun Inc., 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023usanifu haujatajwa
211LLaVA 1.5 (University of Wisconsin Madison, 2023)1.3 × 10¹⁰1.3 × 10¹⁰2023mnene
212Volcano 13B (Korea University, 2023)~1.3 × 10¹⁰2023makadirio
213Aya (Cohere Labs (formerly Cohere for AI), 2024)~1.3 × 10¹⁰2024makadirio
214Kaiju Small (Character.ai, 2025)~1.3 × 10¹⁰2025makadirio
215ByT5-XXL (Google, 2021)~1.3 × 10¹⁰2021makadirio
216CoRe (Tsinghua University, 2023)~1.2 × 10¹⁰2023makadirio
217DALL-E (OpenAI, 2021)~1.2 × 10¹⁰2021makadirio
218Codex (OpenAI, 2021)~1.2 × 10¹⁰2021makadirio
219T5-11B (Google, 2019)1.1 × 10¹⁰1.1 × 10¹⁰2019mnene
220UnifiedQA (Allen Institute for AI, 2020)1.1 × 10¹⁰1.1 × 10¹⁰2020mnene
221Unicorn (Allen Institute for AI, 2021)1.1 × 10¹⁰1.1 × 10¹⁰2021usanifu haujatajwa
222PLATO-XL (Baidu, 2021)1.1 × 10¹⁰1.1 × 10¹⁰2021usanifu haujatajwa
223CoEdiT-xxl (University of Minnesota, 2023)~1.1 × 10¹⁰2023makadirio
224GQA-8-XXL (Google Research, 2023)1.1 × 10¹⁰1.1 × 10¹⁰2023usanifu haujatajwa
225XLMR-XXL (Facebook AI Research, 2021)1.1 × 10¹⁰1.1 × 10¹⁰2021usanifu haujatajwa
226Llama 3.2 11B (Meta AI, 2024)1.1 × 10¹⁰1.1 × 10¹⁰2024mnene
227ERNIE 3.0 (Baidu, 2021)1 × 10¹⁰1 × 10¹⁰2021mnene
228ERNIE-ViLG (Baidu, 2021)~1 × 10¹⁰2021makadirio
229Qwen-VL (Alibaba, 2023)~9.6 × 10⁹2023makadirio
230Generative BST (Facebook AI Research, 2021)9.4 × 10⁹9.4 × 10⁹2021usanifu haujatajwa
231Sparse all-MLP (Meta AI, 2022)9.4 × 10⁹9.4 × 10⁹2022mchanganyiko wa wataalamu (idadi hai haijachapishwa)
232CogVideo (Tsinghua University, 2022)~9.4 × 10⁹2022makadirio
233eDiff-I (Nvidia, 2022)~9.1 × 10⁹2022makadirio
234Eagle 2 (Nvidia, 2025)8.9 × 10⁹8.9 × 10⁹2025usanifu haujatajwa
235MoE-Multi (Jagiellonian University, 2017)8.7 × 10⁹8.7 × 10⁹2017mchanganyiko wa wataalamu (idadi hai haijachapishwa)
236Qwen-Audio-Chat (Alibaba, 2023)~8.5 × 10⁹2023makadirio
237Megatron-LM (Nvidia, 2019)~8.3 × 10⁹2019makadirio
238BigSSL (Google, 2021)~8 × 10⁹2021makadirio
239Nemotron-3-8B (Nvidia, 2023)8 × 10⁹8 × 10⁹2023usanifu haujatajwa
240Stable Diffusion 3 (Stability AI, 2024)8 × 10⁹8 × 10⁹2024mnene
241Qwen3 Embedding (Alibaba, 2025)8 × 10⁹8 × 10⁹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
242Imagen (Google Brain, 2022)~7.8 × 10⁹2022makadirio
243XGLM-7.5B (Meta AI, 2021)7.5 × 10⁹7.5 × 10⁹2021usanifu haujatajwa
244RETRO-7B (DeepMind, 2022)7.5 × 10⁹7.5 × 10⁹2022usanifu haujatajwa
245OpenVLA (Stanford University, 2024)7.2 × 10⁹7.2 × 10⁹2024usanifu haujatajwa
246mPLUG-Owl2 (Alibaba, 2023)~7.1 × 10⁹2023makadirio
247Goat-7B (National University of Singapore, 2023)~7 × 10⁹2023makadirio
248Llama 2-7B (Meta AI, 2023)7 × 10⁹7 × 10⁹2023mnene
249Llama Guard (Meta AI, 2023)7 × 10⁹7 × 10⁹2023mnene
250Qwen-VL-Max (Alibaba, 2024)7 × 10⁹7 × 10⁹2024mnene
251Mathstral (Mistral AI, 2024)7 × 10⁹7 × 10⁹2024usanifu haujatajwa
252Apollo 7B (Meta AI, 2024)7 × 10⁹7 × 10⁹2024usanifu haujatajwa
253Eurus-2-7B-PRIME (Tsinghua University, 2025)~7 × 10⁹2025makadirio
254INTELLECT-MATH (Prime Intellect, 2025)7 × 10⁹7 × 10⁹2025usanifu haujatajwa
255Incoder-6.7B (Facebook AI Research, 2023)6.7 × 10⁹6.7 × 10⁹2023usanifu haujatajwa
256ProGen2-xlarge (Salesforce Research, 2022)6.4 × 10⁹6.4 × 10⁹2022usanifu haujatajwa
257GPipe (Google, 2018)~6 × 10⁹2018makadirio
258InstructGPT 6B (OpenAI, 2022)6 × 10⁹6 × 10⁹2022mnene
259Vega v2 (Wuhan University, 2022)6 × 10⁹6 × 10⁹2022usanifu haujatajwa
260ChatGLM3-6B (Z.ai (Zhipu AI), 2023)~6 × 10⁹2023makadirio
261MolmoAct 2 (Allen Institute for AI, 2026)~5.5 × 10⁹2026makadirio
262T-NLRv5 XXL (Microsoft, 2021)5.4 × 10⁹5.4 × 10⁹2021usanifu haujatajwa
263π0.6 (Physical Intelligence, 2025)5.3 × 10⁹5.3 × 10⁹2025mchanganyiko wa wataalamu (idadi hai haijachapishwa)
264PaLI-3 (Google DeepMind, 2023)5 × 10⁹5 × 10⁹2023usanifu haujatajwa
265Mesh-TensorFlow Transformer 4.9B (Google Brain, 2018)4.9 × 10⁹4.9 × 10⁹2018mnene
266W.A.L.T (Stanford University, 2023)4.7 × 10⁹4.7 × 10⁹2023usanifu haujatajwa
267CogView (Tsinghua University, 2021)~4 × 10⁹2021makadirio
268Make-A-Scene (Meta AI, 2022)~4 × 10⁹2022makadirio
269ONE-PEACE (Alibaba, 2023)~4 × 10⁹2023makadirio
270Megatron-BERT (Nvidia, 2019)3.9 × 10⁹3.9 × 10⁹2019mnene
271DALL·E 2 (OpenAI, 2022)~3.5 × 10⁹2022makadirio
272Stable Diffusion XL (Stability AI, 2023)~3.4 × 10⁹2023makadirio
273MusicGen (Meta AI, 2023)~3.4 × 10⁹2023makadirio
274Gemini Nano-2 (Google DeepMind, 2023)3.3 × 10⁹3.3 × 10⁹2023usanifu haujatajwa
275Zidong Taichu (Chinese Academy of Sciences, 2021)3.2 × 10⁹3.2 × 10⁹2021usanifu haujatajwa
276DeepNet (Microsoft Research, 2022)3.2 × 10⁹3.2 × 10⁹2022usanifu haujatajwa
277MS-ensemble-speech-recognition (Microsoft, 2016)~3.2 × 10⁹2016makadirio
278BASIC-L (Google, 2021)~3.1 × 10⁹2021makadirio
279BASIC-L + Lion (Google, 2023)3.1 × 10⁹3.1 × 10⁹2023usanifu haujatajwa
280LEP-AD (King Abdullah University of Science and Technology (KAUST), 2023)3 × 10⁹3 × 10⁹2023usanifu haujatajwa
281ViT-G/14 (Google Research, 2021)3 × 10⁹3 × 10⁹2021usanifu haujatajwa
282ProtT5-XL-U50 (Technical University of Munich, 2021)3 × 10⁹3 × 10⁹2021usanifu haujatajwa
283Swin Transformer V2 (Microsoft Research Asia, 2021)3 × 10⁹3 × 10⁹2021usanifu haujatajwa
284LongT5 (Google Research, 2021)3 × 10⁹3 × 10⁹2021usanifu haujatajwa
285ReALM (Apple, 2024)3 × 10⁹3 × 10⁹2024usanifu haujatajwa
286Mesh-TensorFlow Transformer 2.9B (Google Brain, 2018)~2.9 × 10⁹2018makadirio
287T5-3B (Google, 2019)2.8 × 10⁹2.8 × 10⁹2019mnene
288DPO on Pythia-2.8B (Stanford University, 2023)2.8 × 10⁹2.8 × 10⁹2023mnene
289AFM-on-device (Apple, 2024)2.7 × 10⁹2.7 × 10⁹2024usanifu haujatajwa
290PolyCoder (Carnegie Mellon University (CMU), 2022)~2.7 × 10⁹2022makadirio
291Hybrid H3-2.7B (Stanford University, 2022)~2.7 × 10⁹2022makadirio
292GPT3-2.7B (Stanford University, 2023)2.7 × 10⁹2.7 × 10⁹2023usanifu haujatajwa
293Meena (Google Brain, 2020)2.6 × 10⁹2.6 × 10⁹2020mnene
294CPM-Large (Tsinghua University, 2020)2.6 × 10⁹2.6 × 10⁹2020mnene
295Nucleotide Transformer (Nvidia, 2023)~2.5 × 10⁹2023makadirio
296Fugatto 1 (Nvidia, 2024)2.5 × 10⁹2.5 × 10⁹2024usanifu haujatajwa
297CoAtNet (Google, 2021)2.4 × 10⁹2.4 × 10⁹2021usanifu haujatajwa
298GShard (Google, 2020)2.3 × 10⁹2.3 × 10⁹2020mnene
299SeamlessM4T (Facebook, 2023)2.3 × 10⁹2.3 × 10⁹2023usanifu haujatajwa
300Turing ULRv5 (Microsoft, 2021)2.2 × 10⁹2.2 × 10⁹2021usanifu haujatajwa
301CoCa (Google Research, 2022)2.1 × 10⁹2.1 × 10⁹2022usanifu haujatajwa
302MuseNet (OpenAI, 2019)~2 × 10⁹2019makadirio
303Infinity (ByteDance, 2024)2 × 10⁹2 × 10⁹2024usanifu haujatajwa
304Seq2Seq LSTM (Google, 2014)1.9 × 10⁹1.9 × 10⁹2014mnene
305BEIT-3 (Microsoft, 2022)~1.9 × 10⁹2022makadirio
306Ankh_large (Technical University of Munich, 2023)1.9 × 10⁹1.9 × 10⁹2023usanifu haujatajwa
307ViT-G/14 (Google Brain, 2021)1.8 × 10⁹1.8 × 10⁹2021usanifu haujatajwa
308ViT-G (University of Washington, 2022)1.8 × 10⁹1.8 × 10⁹2022usanifu haujatajwa
309Phenaki (University College London (UCL), 2022)~1.8 × 10⁹2022makadirio
310Gemini Nano-1 (Google DeepMind, 2023)1.8 × 10⁹1.8 × 10⁹2023usanifu haujatajwa
311DistBelief Vision (Google, 2012)~1.7 × 10⁹2012makadirio
312Whisper (OpenAI, 2022)~1.6 × 10⁹2022makadirio
313GPT-2 (OpenAI, 2019)~1.5 × 10⁹2019makadirio
314DeBERTa (Microsoft, 2021)1.5 × 10⁹1.5 × 10⁹2021usanifu haujatajwa
315AR-LDM (Alibaba, 2022)1.5 × 10⁹1.5 × 10⁹2022usanifu haujatajwa
316AudioLM (Google Research, 2023)~1.5 × 10⁹2023makadirio
317BLIP-2 (Salesforce Research, 2023)1.5 × 10⁹1.5 × 10⁹2023usanifu haujatajwa
318LDM-1.45B (Heidelberg University, 2021)1.4 × 10⁹1.4 × 10⁹2021usanifu haujatajwa
319Stable Diffusion (Runway, 2022)1.4 × 10⁹1.4 × 10⁹2022mnene
320SEER (Facebook AI Research, 2021)1.3 × 10⁹1.3 × 10⁹2021usanifu haujatajwa
321InstructGPT 1.3B (OpenAI, 2022)1.3 × 10⁹1.3 × 10⁹2022mnene
322Megatron-LM (Nvidia, 2019)1.2 × 10⁹1.2 × 10⁹2019mnene
323RDT-1B (Tsinghua University, 2024)~1.2 × 10⁹2024makadirio
324Gato (DeepMind, 2022)1.2 × 10⁹1.2 × 10⁹2022usanifu haujatajwa
325DINOv2 (Facebook AI Research, 2023)1.1 × 10⁹1.1 × 10⁹2023usanifu haujatajwa
326Diffusion Renderer (Nvidia, 2025)1.1 × 10⁹1.1 × 10⁹2025usanifu haujatajwa
327InternImage (Shanghai AI Lab, 2022)1.1 × 10⁹1.1 × 10⁹2022usanifu haujatajwa
328EVA-01 (Beijing Academy of Artificial Intelligence / BAAI, 2022)1 × 10⁹1 × 10⁹2022usanifu haujatajwa
329Unsupervised High-level Feature Learner (Google, 2012)~1 × 10⁹2012makadirio
330Conformer + Wav2vec 2.0 + Noisy Student (Google, 2020)1 × 10⁹1 × 10⁹2020mnene
331HuBERT (Facebook AI Research, 2021)~1 × 10⁹2021makadirio
332W2v-BERT (Google Brain, 2021)1 × 10⁹1 × 10⁹2021mnene
333AudioGen (Meta AI, 2023)~1 × 10⁹2023makadirio
334VideoMAE V2 (Nanjing University, 2023)1 × 10⁹1 × 10⁹2023usanifu haujatajwa
335TransE (Universite de Technologie de Compiègne – CNRS, 2013)~9.4 × 10⁸2013makadirio
336ImageBind (Meta AI, 2023)~9.3 × 10⁸2023makadirio
337Big Transfer (Google Brain, 2019)~9.3 × 10⁸2019makadirio
338Florence (Microsoft, 2021)8.9 × 10⁸8.9 × 10⁸2021usanifu haujatajwa
339NÜWA (Microsoft Research, 2021)8.7 × 10⁸8.7 × 10⁸2021usanifu haujatajwa
340MusicLM (Google, 2023)8.6 × 10⁸8.6 × 10⁸2023usanifu haujatajwa
341ResNeXt-101 32x48d (Facebook, 2018)8.3 × 10⁸8.3 × 10⁸2018mnene
342FixRes ResNeXt-101 WSL (Facebook AI, 2019)~8.3 × 10⁸2019makadirio
343ALIGN (Google Research, 2021)8.2 × 10⁸8.2 × 10⁸2021usanifu haujatajwa
344Statement Curriculum Learning (OpenAI, 2022)~7.7 × 10⁸2022makadirio
345CodeT5-large (Salesforce, 2022)~7.7 × 10⁸2022makadirio
346DITTO (Tsinghua University, 2022)7.5 × 10⁸7.5 × 10⁸2022usanifu haujatajwa
347FGN (Google DeepMind, 2025)7.2 × 10⁸7.2 × 10⁸2025usanifu haujatajwa
348data2vec (Meta AI, 2022)~7.1 × 10⁸2022makadirio
349Tranception (University of Oxford, 2022)7 × 10⁸7 × 10⁸2022usanifu haujatajwa
350Word2Vec (Google, 2013)~6.9 × 10⁸2013makadirio
351DiT-XL/2 (New York University (NYU), 2023)6.8 × 10⁸6.8 × 10⁸2023usanifu haujatajwa
352DiT-XL/2 + CADS (ETH Zurich, 2023)~6.8 × 10⁸2023makadirio
353OmegaPLM (Massachusetts Institute of Technology (MIT), 2022)6.7 × 10⁸6.7 × 10⁸2022usanifu haujatajwa
354XLM (Facebook, 2019)~6.7 × 10⁸2019makadirio
355ESM1b (Facebook AI Research, 2020)6.5 × 10⁸6.5 × 10⁸2020mnene
356Segment Anything Model (Meta AI, 2023)6.4 × 10⁸6.4 × 10⁸2023usanifu haujatajwa
357ViT-Huge/14 (Google Brain, 2020)6.3 × 10⁸6.3 × 10⁸2020mnene
358Masked Autoencoders ViT-H (Facebook AI Research, 2021)~6.3 × 10⁸2021makadirio
359Retrieval-Augmented Generator (Facebook, 2020)6.3 × 10⁸6.3 × 10⁸2020mnene
360DLDL (University of Oxford, 2016)~5.6 × 10⁸2016makadirio
361ADM (OpenAI, 2021)5.6 × 10⁸5.6 × 10⁸2021usanifu haujatajwa
362TrOCR (Beihang University, 2021)5.6 × 10⁸5.6 × 10⁸2021usanifu haujatajwa
363XLM-RoBERTa (Facebook AI, 2019)5.5 × 10⁸5.5 × 10⁸2019mnene
364LUKE (University of Washington, 2020)~4.8 × 10⁸2020makadirio
365EfficientNet-L2 (Google, 2019)~4.8 × 10⁸2019makadirio
366Noisy Student (Carnegie Mellon University (CMU), 2019)4.8 × 10⁸4.8 × 10⁸2019mnene
367Meta Pseudo Labels (Google Brain, 2021)~4.8 × 10⁸2021makadirio
368EMDR (Mila - Quebec AI (originally Montreal Institute for Learning Algorithms), 2021)4.4 × 10⁸4.4 × 10⁸2021usanifu haujatajwa
369NMT Transformer 437M (Google, 2019)4.4 × 10⁸4.4 × 10⁸2019mnene
370Adaptive Inputs + LayerDrop (Facebook AI Research, 2019)4.2 × 10⁸4.2 × 10⁸2019mnene
371ProtBERT-BFD (Technical University of Munich, 2021)4.2 × 10⁸4.2 × 10⁸2021usanifu haujatajwa
372OntoProtein (Zhejiang University (ZJU), 2022)~4.2 × 10⁸2022makadirio
373DeBERTaV3large + KEAR (Microsoft, 2022)4.2 × 10⁸4.2 × 10⁸2022usanifu haujatajwa
374BART-large (Facebook AI, 2019)~4.1 × 10⁸2019makadirio
375SigLIP 400M (Google DeepMind, 2023)4 × 10⁸4 × 10⁸2023usanifu haujatajwa
376BERT-Large-CAS (Amazon, 2019)~4 × 10⁸2019makadirio
377MoCo (Facebook AI, 2019)~3.8 × 10⁸2019makadirio
378SimCLR (Google Brain, 2020)~3.8 × 10⁸2020makadirio
379CLIP (OpenAI, 2021)3.7 × 10⁸3.7 × 10⁸2021usanifu haujatajwa
380RoBERTa Large (Facebook, 2019)3.5 × 10⁸3.5 × 10⁸2019mnene
381AbLang (University of Oxford, 2022)3.5 × 10⁸3.5 × 10⁸2022usanifu haujatajwa
382GPT-2 Medium (Stanford University, 2022)3.5 × 10⁸3.5 × 10⁸2022mnene
383VALL-E (Microsoft, 2023)~3.5 × 10⁸2023makadirio
384BERT-Large (Google, 2018)3.4 × 10⁸3.4 × 10⁸2018mnene
385XLNet (Carnegie Mellon University (CMU), 2019)3.4 × 10⁸3.4 × 10⁸2019mnene
386ERNIE-GEN (Baidu, 2020)~3.4 × 10⁸2020makadirio
387CamemBERT (Facebook, 2019)3.4 × 10⁸3.4 × 10⁸2019mnene
388ELECTRA (Stanford University, 2020)~3.4 × 10⁸2020makadirio
389German ELECTRA Large (deepset, 2020)3.4 × 10⁸3.4 × 10⁸2020mnene
390ALM 1.0 (Beijing Academy of Artificial Intelligence / BAAI, 2022)~3.4 × 10⁸2022makadirio
391MT-DNN (Microsoft, 2019)3.3 × 10⁸3.3 × 10⁸2019mnene
392Fusion in Encoder (Samsung, 2022)~3.3 × 10⁸2022makadirio
393wave2vec 2.0 LARGE (Facebook, 2020)3.2 × 10⁸3.2 × 10⁸2020mnene
394CPC v2 (DeepMind, 2019)~3 × 10⁸2019makadirio
395Transformer - LibriVox + Decoding/Rescoring (Facebook, 2019)3 × 10⁸3 × 10⁸2019mnene
396DDPM-IP (Utrecht University, 2023)~3 × 10⁸2023makadirio
397GNMT (Google, 2016)~2.8 × 10⁸2016makadirio
398base LM+GNN+kNN (Shannon.AI, 2021)2.7 × 10⁸2.7 × 10⁸2021usanifu haujatajwa
399YOLO (University of Washington, 2015)~2.7 × 10⁸2015makadirio
400Transformer-XL (Carnegie Mellon University (CMU), 2019)~2.6 × 10⁸2019makadirio
401Transformer-XL + RMS dynamic eval (University of Edinburgh, 2019)2.6 × 10⁸2.6 × 10⁸2019mnene
402Transformer-XL Large + Phrase Induction (Massachusetts Institute of Technology (MIT), 2019)~2.6 × 10⁸2019makadirio
403Segatron-XL large, M=384 + HCP (Microsoft Research, 2022)2.6 × 10⁸2.6 × 10⁸2022usanifu haujatajwa
404Denoising Diffusion Probabilistic Models (University of California (UC) Berkeley, 2021)2.6 × 10⁸2.6 × 10⁸2021usanifu haujatajwa
405Pangu-Weather (Huawei, 2023)2.6 × 10⁸2.6 × 10⁸2023usanifu haujatajwa
406SPN (Google Brain, 2018)2.5 × 10⁸2.5 × 10⁸2018mnene
407S4 (Stanford University, 2021)~2.5 × 10⁸2021makadirio
408Base LM + kNN LM + Continuous Cache (Stanford University, 2019)~2.5 × 10⁸2019makadirio
409ERNIE-Doc (Baidu, 2020)2.5 × 10⁸2.5 × 10⁸2020mnene
410Adaptive Input Transformer + RD (Microsoft Research Asia, 2021)~2.5 × 10⁸2021makadirio
411Transformer (Adaptive Input Embeddings) WT103 (Facebook AI Research, 2018)2.5 × 10⁸2.5 × 10⁸2018mnene
412TaLK Convolution (Carleton University, 2020)~2.4 × 10⁸2020makadirio
413ALBERT-xxlarge (Toyota Technological Institute at Chicago, 2020)~2.4 × 10⁸2020makadirio
414SRU++ Large (ASAPP, 2021)2.3 × 10⁸2.3 × 10⁸2021usanifu haujatajwa
415GR-2 (ByteDance, 2024)2.3 × 10⁸2.3 × 10⁸2024usanifu haujatajwa
416MaskGIT (Google Research, 2022)2.3 × 10⁸2.3 × 10⁸2022usanifu haujatajwa
417MetNet (Google, 2020)~2.3 × 10⁸2020makadirio
418FFN SwiGLU (Google, 2020)2.2 × 10⁸2.2 × 10⁸2020mnene
419CodeT5-base (Salesforce, 2021)~2.2 × 10⁸2021makadirio
420Transformer (Google Research, 2017)2.1 × 10⁸2.1 × 10⁸2017mnene
421Sandwich Transformer (Allen Institute for AI, 2019)~2.1 × 10⁸2019makadirio
422EfficientNetV2-XL (Google, 2021)2.1 × 10⁸2.1 × 10⁸2021usanifu haujatajwa
423Word2Vec (Google, 2013)~2.1 × 10⁸2013makadirio
424Multilingual DNN (Google, 2013)2.1 × 10⁸2.1 × 10⁸2013mnene
425DreamerV3 (DeepMind, 2023)~2 × 10⁸2023makadirio
426DL scaling speech (Baidu, 2017)~1.9 × 10⁸2017makadirio
427ResNeXt-101 Billion-scale (Facebook AI, 2019)~1.9 × 10⁸2019makadirio
428 (NTT Communication Science Laboratories, 2018)1.9 × 10⁸1.9 × 10⁸2018mnene
429TrellisNet (Carnegie Mellon University (CMU), 2018)1.8 × 10⁸1.8 × 10⁸2018mnene
430DL scaling LM (Baidu, 2017)~1.8 × 10⁸2017makadirio
431EXAONE Path 2.0 (LG AI Research, 2025)1.8 × 10⁸1.8 × 10⁸2025usanifu haujatajwa
432OpenAI Five Rerun (OpenAI, 2019)1.6 × 10⁸1.6 × 10⁸2019mnene
433OpenAI Five (OpenAI, 2019)1.6 × 10⁸1.6 × 10⁸2019mnene
4344 layer QRNN (Salesforce Research, 2018)~1.5 × 10⁸2018makadirio
435TransformerXL + spectrum control (University of California Los Angeles (UCLA), 2020)~1.5 × 10⁸2020makadirio
436AlphaGeometry (Google DeepMind, 2024)1.5 × 10⁸1.5 × 10⁸2024usanifu haujatajwa
437PermuteFormer (Peking University, 2021)~1.5 × 10⁸2021makadirio
438Fragment embedding (Stanford University, 2014)~1.4 × 10⁸2014makadirio
439OverFeat (New York University (NYU), 2013)1.4 × 10⁸1.4 × 10⁸2013mnene
440VGG19 (University of Oxford, 2014)~1.4 × 10⁸2014makadirio
441LRCN (UT Austin, 2014)~1.4 × 10⁸2014makadirio
442Transformer-XL DeFINE (University of Washington, 2019)~1.4 × 10⁸2019makadirio
443Deep Autoencoders (University of Toronto, 2011)1.4 × 10⁸1.4 × 10⁸2011mnene
444AlphaStar (DeepMind, 2019)1.4 × 10⁸1.4 × 10⁸2019mnene
445VGG16 (University of Oxford, 2014)1.4 × 10⁸1.4 × 10⁸2014mnene
446VGG-Face (University of Oxford, 2015)1.4 × 10⁸1.4 × 10⁸2015mnene
447SAF R-CNN (Beijing Institute of Technology, 2015)~1.4 × 10⁸2015makadirio
448Template Adaptation (University of Oxford, 2016)~1.4 × 10⁸2016makadirio
449LRR-4X (UC Irvine, 2016)~1.4 × 10⁸2016makadirio
450CMS-RCNN (IEEE, 2016)~1.4 × 10⁸2016makadirio
451QRNN (Salesforce Research, 2018)~1.4 × 10⁸2018makadirio
452Multiresolution CNN (Google, 2014)~1.3 × 10⁸2014makadirio
453FTW (DeepMind, 2018)~1.3 × 10⁸2018makadirio
454Feedback Transformer (LORIA, 2020)~1.3 × 10⁸2020makadirio
455KEPLER (Tsinghua University, 2020)1.3 × 10⁸1.3 × 10⁸2020mnene
456DL scaling Image (Baidu, 2017)1.2 × 10⁸1.2 × 10⁸2017mnene
457GloVe (Stanford University, 2014)~1.2 × 10⁸2014makadirio
458Conformer (Google, 2020)1.2 × 10⁸1.2 × 10⁸2020mnene
459GPT-1 (OpenAI, 2018)~1.2 × 10⁸2018makadirio
460ContextNet (Google, 2020)~1.1 × 10⁸2020makadirio
461SciBERT (Allen Institute for AI, 2019)1.1 × 10⁸1.1 × 10⁸2019mnene
462DNABERT (Northeastern University, 2021)1.1 × 10⁸1.1 × 10⁸2021usanifu haujatajwa
463Contriever (Meta AI, 2021)~1.1 × 10⁸2021makadirio
464BERT-RBP (Waseda University, 2022)1.1 × 10⁸1.1 × 10⁸2022mnene
465RoFormer (Zhuiyi Technology, 2023)1.1 × 10⁸1.1 × 10⁸2023usanifu haujatajwa
466LSTM LM (RWTH Aachen University, 2012)~1 × 10⁸2012makadirio
467ReLU-Speech (Google, 2013)~1 × 10⁸2013makadirio
468STORM-B/8 (University of Southern California, 2024)1 × 10⁸1 × 10⁸2024usanifu haujatajwa
469Support Vector Machines (AT&T, 1995)~1 × 10⁸1995makadirio
470GPU DBNs (Stanford University, 2009)1 × 10⁸1 × 10⁸2009mnene
471MSA Transformer (Facebook AI Research, 2021)~1 × 10⁸2021makadirio
472YOLOX-X (Megvii Inc, 2021)~9.9 × 10⁷2021makadirio
473DeLighT (University of Washington, 2020)~9.9 × 10⁷2020makadirio
474ELMo (University of Washington, 2018)~9.4 × 10⁷2018makadirio
475AlphaFold 2 (DeepMind, 2020)~9.3 × 10⁷2020makadirio
476AlphaMissense (Google DeepMind, 2023)~9.3 × 10⁷2023makadirio
477Octo-Base (University of California (UC) Berkeley, 2024)9.3 × 10⁷9.3 × 10⁷2024usanifu haujatajwa
478PolyNet (Chinese University of Hong Kong (CUHK), 2016)~9.2 × 10⁷2016makadirio
479Transformer local-attention (Google Cloud, 2021)9 × 10⁷9 × 10⁷2021usanifu haujatajwa
480Transformer + Simple Recurrent Unit (ASAPP, 2018)9 × 10⁷9 × 10⁷2018mnene
481NASNet-A (Google Brain, 2017)~8.9 × 10⁷2017makadirio
482CLIP (OpenAI, 2021)~8.9 × 10⁷2021makadirio
483Detic (Meta AI, 2022)~8.8 × 10⁷2022makadirio
484MSRA (Microsoft Research, 2015)8.7 × 10⁷8.7 × 10⁷2015mnene
485BigBiGAN (Google, 2019)~8.6 × 10⁷2019makadirio
486ViT-Base/32 (Google Brain, 2020)~8.6 × 10⁷2020makadirio
487DeiT-B (Meta AI, 2021)8.6 × 10⁷8.6 × 10⁷2021usanifu haujatajwa
488CaLM (University of Oxford, 2022)~8.6 × 10⁷2022makadirio
489Tensor-Transformer (University of California (UC) Berkeley, 2020)8.5 × 10⁷8.5 × 10⁷2020mnene
490ResNeXt-101 (University of California San Diego, 2016)8.3 × 10⁷8.3 × 10⁷2016mnene
491RBM Image Classifier (University of Toronto, 2009)~8 × 10⁷2009makadirio
492Routing Transformer (Google Research, 2020)8 × 10⁷8 × 10⁷2020mnene
493Big-Little Net (IBM, 2018)~7.7 × 10⁷2018makadirio
494EfficientDet (Google Brain, 2020)~7.7 × 10⁷2020makadirio
495CODEFUSION (Microsoft, 2023)7.5 × 10⁷7.5 × 10⁷2023usanifu haujatajwa
496RNN LM (Johns Hopkins University, 2010)~7 × 10⁷2010makadirio
497R-CNN (University of California (UC) Berkeley, 2013)~6.9 × 10⁷2013makadirio
498Variational (University of Cambridge, 2015)6.6 × 10⁷6.6 × 10⁷2015mnene
499DistilBERT (Hugging Face, 2019)6.6 × 10⁷6.6 × 10⁷2019mnene
500Theseus 6/768 (University of California San Diego, 2020)6.6 × 10⁷6.6 × 10⁷2020mnene
501ResNet-152 (Microsoft, 2015)6 × 10⁷6 × 10⁷2015mnene
502AlexNet (University of Toronto, 2012)6 × 10⁷6 × 10⁷2012mnene
503DETR (Facebook, 2020)6 × 10⁷6 × 10⁷2020mnene
504YOLOv3 (University of Washington, 2018)~5.7 × 10⁷2018makadirio
505Inception-ResNet-V2 (Google, 2016)~5.6 × 10⁷2016makadirio
506Transformer ELMo (Allen Institute for AI, 2019)5.6 × 10⁷5.6 × 10⁷2019mnene
507Ubongo wa nzi wa matunda5.5 × 10⁷5.5 × 10⁷sinapsi
508NAS with base 8 and shared embeddings (Google Brain, 2016)5.4 × 10⁷5.4 × 10⁷2016mnene
509RetinaNet-R101 (Facebook AI Research, 2017)5.3 × 10⁷5.3 × 10⁷2017mnene
510AWD-LSTM+WT+Cache+IOG (NTT Communication Science Laboratories, 2017)5.3 × 10⁷5.3 × 10⁷2017mnene
511Hierarchical Scene Labeling (New York University (NYU), 2013)5.2 × 10⁷5.2 × 10⁷2013mnene
512VD-LSTM+REAL Large (Salesforce Research, 2016)5.1 × 10⁷5.1 × 10⁷2016mnene
513YOLOv2 (University of Washington, 2016)~5.1 × 10⁷2016makadirio
514Dropout-LSTM+Noise (Columbia University, 2018)~5.1 × 10⁷2018makadirio
515LSTM + dynamic eval (University of Edinburgh, 2017)~5 × 10⁷2017makadirio
516Dropout (University of Toronto, 2012)~4.9 × 10⁷2012makadirio
517Dropout: SVHN (University of Toronto, 2014)4.8 × 10⁷4.8 × 10⁷2014mnene
518DistBelief Speech (Google, 2012)~4.7 × 10⁷2012makadirio
519AlphaGo Zero (DeepMind, 2017)4.6 × 10⁷4.6 × 10⁷2017mnene
520Fine-tuned-AWD-LSTM-DOC (Samsung R&D Institute Russia, 2018)4.6 × 10⁷4.6 × 10⁷2018mnene
521CT-MoS (Google, 2020)4.5 × 10⁷4.5 × 10⁷2020mnene
522JFT (Google Research, 2017)4.5 × 10⁷4.5 × 10⁷2017mnene
523ResNet-101 (Microsoft, 2015)4.5 × 10⁷4.5 × 10⁷2015mnene
524HR-ResNet101 (Carnegie Mellon University (CMU), 2016)4.5 × 10⁷4.5 × 10⁷2016mnene
5253DMM-CNN (University of Southern California, 2016)4.5 × 10⁷4.5 × 10⁷2016mnene
526LaNet-L (Brown University, 2019)4.4 × 10⁷4.4 × 10⁷2019mnene
527ProBERTa (University of Illinois Urbana-Champaign (UIUC), 2020)4.4 × 10⁷4.4 × 10⁷2020mnene
528PreTrans-3L-250H (University of Toronto, 2013)~4.3 × 10⁷2013makadirio
529Inceptionv4 (Google, 2016)~4.3 × 10⁷2016makadirio
530GL-LWGC-AWD-MoS-LSTM + dynamic evaluation (Ben-Gurion University of the Negev, 2017)3.8 × 10⁷3.8 × 10⁷2017mnene
531U-Net (University of Freiburg, 2015)3.8 × 10⁷3.8 × 10⁷2015mnene
532NASv3 (Google Brain, 2016)~3.7 × 10⁷2016makadirio
533MuZero (DeepMind, 2019)~3.7 × 10⁷2019makadirio
534AWD-LSTM-MoS + dynamic evaluation (Carnegie Mellon University (CMU), 2017)~3.5 × 10⁷2017makadirio
535AWD-LSTM-MoS+PDR + dynamic evaluation (IBM, 2018)3.5 × 10⁷3.5 × 10⁷2018mnene
536AWD-LSTM-MoS + dynamic evaluation (Peking University, 2018)3.5 × 10⁷3.5 × 10⁷2018mnene
537AWD-LSTM + MoS + Partial Shuffled (University of Texas at Austin, 2019)3.5 × 10⁷3.5 × 10⁷2019mnene
538Mogrifier (d2, MoS2, MC) + dynamic eval (DeepMind, 2019)3.5 × 10⁷3.5 × 10⁷2019mnene
539Mogrifier RLSTM (DeepMind, 2022)3.5 × 10⁷3.5 × 10⁷2022usanifu haujatajwa
540RT-1 (Google, 2022)3.5 × 10⁷3.5 × 10⁷2022usanifu haujatajwa
541DenseNet-264 (Tsinghua University, 2016)3.4 × 10⁷3.4 × 10⁷2016mnene
542RetinaNet-R50 (Facebook AI Research, 2017)~3.4 × 10⁷2017makadirio
543Fraternal dropout + AWD-LSTM 3-layer (Jagiellonian University, 2017)~3.4 × 10⁷2017makadirio
544AWD-LSTM-DRILL + dynamic evaluation† (IDIAP, 2019)~3.4 × 10⁷2019makadirio
545AWD-LSTM - 3-layer LSTM (Salesforce Research, 2017)3.3 × 10⁷3.3 × 10⁷2017mnene
546TCAN (Nanjing University, 2020)3.3 × 10⁷3.3 × 10⁷2020mnene
547MMLSTM (Beijing University of Posts and Telecommunications, 2019)~3.2 × 10⁷2019makadirio
548Paragraph Vector (Google, 2014)3.2 × 10⁷3.2 × 10⁷2014mnene
549aLSTM (University of Manchester, 2018)3.2 × 10⁷3.2 × 10⁷2018mnene
550StyleGAN2 (Nvidia, 2019)3 × 10⁷3 × 10⁷2019mnene
551UDSMProt (Fraunhofer Heinrich Hertz Institute, 2019)~2.8 × 10⁷2019makadirio
552SENet (Chinese Academy of Sciences, 2017)~2.8 × 10⁷2017makadirio
553Perceiver IO (DeepMind, 2020)2.8 × 10⁷2.8 × 10⁷2020mnene
554Fractional Max-Pooling (University of Warwick, 2014)~2.7 × 10⁷2014makadirio
555Hierarchical Reasoning Model (Sapient Intelligence, 2025)2.7 × 10⁷2.7 × 10⁷2025usanifu haujatajwa
556RNN-WER (DeepMind, 2014)~2.6 × 10⁷2014makadirio
557StyleGAN (Nvidia, 2018)2.6 × 10⁷2.6 × 10⁷2018mnene
558PyramidNet (Korea Advanced Institute of Science and Technology (KAIST), 2017)~2.6 × 10⁷2017makadirio
559ResNeXt-50 (University of California San Diego, 2016)~2.5 × 10⁷2016makadirio
560AWD-LSTM (DeepMind, 2017)2.4 × 10⁷2.4 × 10⁷2017mnene
561Inception v3 (Google, 2015)~2.4 × 10⁷2015makadirio
562Mamba-24M (Carnegie Mellon University (CMU), 2023)2.3 × 10⁷2.3 × 10⁷2023usanifu haujatajwa
563WeNet (Amazon, 2019)~2.3 × 10⁷2019makadirio
564EN^2AS with performance reward (Beijing Institute of Technology, 2019)~2.3 × 10⁷2019makadirio
565NAS+ESS (Northeastern University (China), 2020)2.3 × 10⁷2.3 × 10⁷2020mnene
566Xception (Google, 2016)2.3 × 10⁷2.3 × 10⁷2016mnene
567MetaMimic (Google, 2018)~2.2 × 10⁷2018makadirio
568MMLSTM (Beijing University of Posts and Telecommunications, 2019)~2.1 × 10⁷2019makadirio
569Pointer Sentinel-LSTM (MetaMind Inc, 2016)2.1 × 10⁷2.1 × 10⁷2016mnene
570DiffDock (Massachusetts Institute of Technology (MIT), 2022)~2 × 10⁷2022makadirio
571EI-REHN-1000D (Korea Advanced Institute of Science and Technology (KAIST), 2017)1.9 × 10⁷1.9 × 10⁷2017mnene
572TC-DNN-BLSTM-DNN (Carnegie Mellon University (CMU), 2015)1.8 × 10⁷1.8 × 10⁷2015mnene
573OR-WideResNet (Duke University, 2017)1.8 × 10⁷1.8 × 10⁷2017mnene
574BP-DBN (University of Toronto, 2009)1.8 × 10⁷1.8 × 10⁷2009mnene
575ALBERT (Toyota Technological Institute at Chicago, 2019)1.8 × 10⁷1.8 × 10⁷2019mnene
576MedBERT (Peng Cheng Laboratory, 2021)~1.7 × 10⁷2021makadirio
577LCNP NORB (, 2009)1.7 × 10⁷1.7 × 10⁷2009mnene
578LF-MMI (Johns Hopkins University, 2016)1.7 × 10⁷1.7 × 10⁷2016mnene
579AlphaFold (DeepMind, 2020)~1.6 × 10⁷2020makadirio
580GNoME for crystal discovery (Google DeepMind, 2023)~1.6 × 10⁷2023makadirio
581ReLU (University of Toronto, 2010)~1.6 × 10⁷2010makadirio
582ProteinBERT (Hebrew University of Jerusalem, 2022)1.6 × 10⁷1.6 × 10⁷2022usanifu haujatajwa
583Eve (Harvard Medical School, 2021)~1.5 × 10⁷2021makadirio
584LCNP LabelMe (University of Bonn, 2009)1.4 × 10⁷1.4 × 10⁷2009mnene
585BatchNorm (Google, 2015)1.4 × 10⁷1.4 × 10⁷2015mnene
586Fold2Seq (IBM, 2021)~1.2 × 10⁷2021makadirio
587NPLM (University of Montreal / Université de Montréal, 2003)1.2 × 10⁷1.2 × 10⁷2003mnene
588LCNP MNIST (, 2009)1.2 × 10⁷1.2 × 10⁷2009mnene
589ISS (Duke University, 2017)1.1 × 10⁷1.1 × 10⁷2017mnene
590ResNet-1001 (Microsoft, 2016)~1 × 10⁷2016makadirio
591RNN+LDA+KN5+cache (Microsoft, 2012)~9 × 10⁶2012makadirio
592Gated HORNN (York University, 2016)~9 × 10⁶2016makadirio
593AlphaGo Fan (DeepMind, 2015)~8.2 × 10⁶2015makadirio
594genCNN + dyn eval (Chinese Academy of Sciences, 2015)~8 × 10⁶2015makadirio
595Once for All (MIT-IBM Watson AI Lab, 2020)7.7 × 10⁶7.7 × 10⁶2020mnene
596Multi-cell LSTM (University of Hyderabad, 2018)~7.2 × 10⁶2018makadirio
597Feedforward NN (University of Montreal / Université de Montréal, 2010)7.1 × 10⁶7.1 × 10⁶2010mnene
598True-Regularization+Finetune+Dynamic-Eval (Mobvoi, 2019)7 × 10⁶7 × 10⁶2019mnene
599Neural LM (University of Montreal / Université de Montréal, 2000)6.9 × 10⁶6.9 × 10⁶2000mnene
600GoogLeNet / InceptionV1 (Google, 2014)6.8 × 10⁶6.8 × 10⁶2014mnene
601HyenaDNA (Stanford University, 2023)6.6 × 10⁶6.6 × 10⁶2023usanifu haujatajwa
602Dropout (University of Toronto, 2012)5.6 × 10⁶5.6 × 10⁶2012mnene
603SimpleNet (Sensifai, 2016)5.5 × 10⁶5.5 × 10⁶2016mnene
604AlphaX-1 (Facebook AI Research, 2019)5.4 × 10⁶5.4 × 10⁶2019mnene
6053DDFA (Chinese Academy of Sciences, 2015)5.4 × 10⁶5.4 × 10⁶2015mnene
606Deep CNN + COTS (IEEE, 2015)5 × 10⁶5 × 10⁶2015mnene
607DCNN (University of Maryland, 2015)5 × 10⁶5 × 10⁶2015mnene
608NLP from scratch (NEC Laboratories, 2011)~5 × 10⁶2011makadirio
609SPN-4+KN5 (Singapore University of Technology & Design, 2014)~5 × 10⁶2014makadirio
6106-Act Tether (Facebook AI Research, 2021)5 × 10⁶5 × 10⁶2021usanifu haujatajwa
611High Performance CNN (IDSIA, 2011)~4.9 × 10⁶2011makadirio
612MobileNet (Google, 2017)~4.2 × 10⁶2017makadirio
613NPLM (University of Montreal / Université de Montréal, 2003)4.1 × 10⁶4.1 × 10⁶2003mnene
614LMICA (, 2004)4.1 × 10⁶4.1 × 10⁶2004mnene
615PoE MNIST (University College London (UCL), 2000)3.9 × 10⁶3.9 × 10⁶2000mnene
616Dimensionality Reduction (University of Toronto, 2006)~3.8 × 10⁶2006makadirio
617GOAT (DeepMind, 2021)~3.5 × 10⁶2021makadirio
618MobileNetV2 (Google, 2018)~3.4 × 10⁶2018makadirio
619Big-Little Net (IBM, 2018)~3.3 × 10⁶2018makadirio
620DLWP (University of Washington, 2021)2.7 × 10⁶2.7 × 10⁶2021usanifu haujatajwa
621BIDAF (University of Washington, 2016)2.6 × 10⁶2.6 × 10⁶2016mnene
622DeepStack (University of Alberta, 2017)~2.5 × 10⁶2017makadirio
623KataGo (Jane Street, 2019)~2.5 × 10⁶2019makadirio
624ShuffleNet v1 (Megvii Inc, 2017)~2.4 × 10⁶2017makadirio
625ADAM (University of Amsterdam, 2014)2.4 × 10⁶2.4 × 10⁶2014mnene
626StyleGAN3-T (Nvidia, 2021)2.2 × 10⁶2.2 × 10⁶2021usanifu haujatajwa
627LSTM+NeuralCache (KU Leuven, 2018)~2.1 × 10⁶2018makadirio
628HLBL (University of Toronto, 2008)1.8 × 10⁶1.8 × 10⁶2008mnene
629ResNet-110 (Microsoft, 2015)~1.7 × 10⁶2015makadirio
630Dueling DQN (Google DeepMind, 2016)1.7 × 10⁶1.7 × 10⁶2016mnene
631DQN-2015 (Google, 2015)~1.7 × 10⁶2015makadirio
632Rational DQN Average (TU Darmstadt, 2021)~1.7 × 10⁶2021makadirio
633IBM-5 (IBM, 1993)~1.7 × 10⁶1993makadirio
634Deep Belief Nets (University of Toronto, 2006)~1.6 × 10⁶2006makadirio
635IMPALA (DeepMind, 2018)1.6 × 10⁶1.6 × 10⁶2018mnene
636StyleGAN3-R (Nvidia, 2021)1.6 × 10⁶1.6 × 10⁶2021usanifu haujatajwa
637Deep Multitask NLP Network (NEC Laboratories, 2008)~1.5 × 10⁶2008makadirio
638Double DQN (Google DeepMind, 2016)1.5 × 10⁶1.5 × 10⁶2016mnene
639CNN committee (IDSIA, 2011)~1.4 × 10⁶2011makadirio
640SqueezeNet (DeepScale, 2016)~1.2 × 10⁶2016makadirio
641Neocognitron (NHK Broadcasting Science Research Laboratories, 1980)1.1 × 10⁶1.1 × 10⁶1980mnene
642CURL (University of California (UC) Berkeley, 2020)~9.1 × 10⁵2020makadirio
643DQN (DeepMind, 2013)8.4 × 10⁵8.4 × 10⁵2013mnene
644EnhanceNet (Max Planck Institute for Intelligent Systems, 2016)8.1 × 10⁵8.1 × 10⁵2016mnene
645Image generation (University of Amsterdam, 2013)7.8 × 10⁵7.8 × 10⁵2013mnene
646Hanabi 4 player (DeepMind, 2019)7.6 × 10⁵7.6 × 10⁵2019mnene
647TA-CNN (Chinese University of Hong Kong (CUHK), 2014)~7.1 × 10⁵2014makadirio
648Robot Parkour (Shanghai Qi Zhi institute, 2023)5 × 10⁵5 × 10⁵2023usanifu haujatajwa
649LISSOM (University of Texas at Austin, 1995)~4.3 × 10⁵1995makadirio
650SPIDER2 (Griffith University, 2016)~4.1 × 10⁵2016makadirio
651Mixture of linear models (, 1994)~3.8 × 10⁵1994makadirio
652NPD (IEEE, 2014)3.1 × 10⁵3.1 × 10⁵2014mnene
653Pooling CNN (University of Bonn, 2010)2.9 × 10⁵2.9 × 10⁵2010mnene
654Pooling CNN (University of Bonn, 2010)2.7 × 10⁵2.7 × 10⁵2010mnene
655Two Stage Feature Extraction (New York University (NYU), 2009)2.6 × 10⁵2.6 × 10⁵2009mnene
656Vector Space Model (Stanford University, 2011)2.5 × 10⁵2.5 × 10⁵2011mnene
657HyperNEAT (University of Texas at Austin, 2014)~2.4 × 10⁵2014makadirio
658DNN EM segmentation (IDSIA, 2012)2.2 × 10⁵2.2 × 10⁵2012mnene
659Predictive Coding NN (Technical University of Munich, 1994)2.1 × 10⁵2.1 × 10⁵1994mnene
660Table Tennis Agent (Google DeepMind, 2024)~1.9 × 10⁵2024makadirio
661CNN Committee (IDSIA, 2011)~1.3 × 10⁵2011makadirio
662CNN Committee (IDSIA, 2011)~1.2 × 10⁵2011makadirio
663RECONTRA-uncategorized (, 1999)~1.1 × 10⁵1999makadirio
664BLSTM for handwriting (University of Bern, 2007)~1 × 10⁵2007makadirio
665SVM-CNN (New York University (NYU), 2006)9.1 × 10⁴9.1 × 10⁴2006mnene
666Invariant CNN (New York University (NYU), 2004)9.1 × 10⁴9.1 × 10⁴2004mnene
667SexNet compression (, 1990)7.3 × 10⁴7.3 × 10⁴1990mnene
668NeuroChess (, 1994)~7.2 × 10⁴1994makadirio
669RECONTRA-categorized (, 1999)~6.7 × 10⁴1999makadirio
670LeNet-5 (AT&T, 1998)6 × 10⁴6 × 10⁴1998mnene
671Swift (Intel Labs, 2023)~5.7 × 10⁴2023makadirio
672TCN (Carnegie Mellon University (CMU), 2018)4.2 × 10⁴4.2 × 10⁴2018mnene
673TRPO (University of California (UC) Berkeley, 2015)3.4 × 10⁴3.4 × 10⁴2015mnene
674SOM-CNN (, 1997)3.2 × 10⁴3.2 × 10⁴1997mnene
675NETtalk reimplementation (Oregon State University, 1990)2.7 × 10⁴2.7 × 10⁴1990mnene
676TD-Gammon (IBM, 1992)~2.5 × 10⁴1992makadirio
677Cognitron (Biological Cybernetics, 1975)2.2 × 10⁴2.2 × 10⁴1975mnene
678NetTalk (Princeton University, 1987)1.9 × 10⁴1.9 × 10⁴1987mnene
679CFSS (SenseTime, 2015)~1.7 × 10⁴2015makadirio
680MUSIC perceptron (, 1996)1.4 × 10⁴1.4 × 10⁴1996mnene
681AdaRNN (Beihang University, 2014)1.3 × 10⁴1.3 × 10⁴2014mnene
682Bidirectional RNN (Advanced Telecommunications Research Institute, 1997)~1.3 × 10⁴1997makadirio
683Decision tree (Mitsubishi Electric Research Labs, 2001)~1.2 × 10⁴2001makadirio
684LSTM (Technical University of Munich, 1997)1.1 × 10⁴1.1 × 10⁴1997mnene
685MLN-ASR (McGill University, 1988)1 × 10⁴1 × 10⁴1988mnene
686Hopfield network (California Institute of Technology, 1982)~9.9 × 10³1982makadirio
687Zip CNN (AT&T, 1989)9.8 × 10³9.8 × 10³1989mnene
688Hierarchical Cognitron (NHK Broadcasting Science Research Laboratories, 1984)~9.3 × 10³1984makadirio
689Weight Decay (, 1991)8.4 × 10³8.4 × 10³1991mnene
690Deep Blue (IBM, 1997)~8 × 10³1997makadirio
691Nematodi (C. elegans)7 × 10³7 × 10³sinapsi
692System 11 (Carnegie Mellon University (CMU), 1996)6.5 × 10³6.5 × 10³1996mnene
693ACF-WIDER (Chinese Academy of Sciences, 2014)6.1 × 10³6.1 × 10³2014mnene
694RankNet (Microsoft Research, 2005)5.7 × 10³5.7 × 10³2005mnene
695ANN Eye Tracker (, 1993)5.6 × 10³5.6 × 10³1993mnene
696JPMAX (, 1994)~4.4 × 10³1994makadirio
697Kohonen network (Helsinki University of Technology, 1981)~4.1 × 10³1981makadirio
698Speaker-independent vowel classification (University of Washington, 1989)3 × 10³3 × 10³1989mnene
699Pattern recognition and reading by machine (Sandia Corporation, 1959)~2.6 × 10³1959makadirio
700Handwritten digit recognition network (AT&T, 1989)2.6 × 10³2.6 × 10³1989mnene
701Boosting (Bell Laboratories, 1992)~2.6 × 10³1992makadirio
702Decision tree adaline (Tokyo Medical and Dental University, 1969)2.5 × 10³2.5 × 10³1969mnene
703LTE speaker verification system (IBM, 1966)~2.1 × 10³1966makadirio
704Ceramic-MLP (Sapienza Università di Roma, 1994)~1.9 × 10³1994makadirio
705SexNet classification (, 1990)~1.6 × 10³1990makadirio
706RAAM (, 1990)1.5 × 10³1.5 × 10³1990mnene
707Super-vector coding (University of Illinois Urbana-Champaign (UIUC), 2010)~1 × 10³2010makadirio
708Perceptron Mark I (Cornell Aeronautical Laboratory, 1957)~1 × 10³1957makadirio
709Perceptron (Cornell Aeronautical Laboratory, 1960)~1 × 10³1960makadirio
710Translation-invariant MLP (Carnegie Mellon University (CMU), 1987)8.2 × 10²8.2 × 10²1987mchanganyiko wa wataalamu (idadi hai haijachapishwa)
711Truck backer-upper (Stanford University, 1989)8.1 × 10²8.1 × 10²1989mnene
712Siamese-TDNN (Bell Laboratories, 1993)~7.4 × 10²1993makadirio
713MLP with back-propagation (University of California San Diego, 1986)7.2 × 10²7.2 × 10²1986mnene
714Cancer drug mechanism prediction (National Cancer Institute, 1992)~5.9 × 10²1992makadirio
715Distributed representation NN (Carnegie Mellon University (CMU), 1986)4.3 × 10²4.3 × 10²1986mnene
716Piecewise linear model (University of Kansas, 1973)3.6 × 10²3.6 × 10²1973mnene
717ASE+ACE (University of Massachusetts Amherst, 1983)~3.2 × 10²1983makadirio
718LSTM with forget gates (IDSIA, 1999)~2.8 × 10²1999makadirio
719Self Organizing System (Massachusetts Institute of Technology (MIT), 1955)~2.3 × 10²1955makadirio
720Theseus (Bell Laboratories, 1950)4 × 10¹4 × 10¹1950mnene
721SNARC (Harvard University, 1952)~4 × 10¹1952makadirio
722Bankruptcy-NN (, 1990)3.6 × 10¹3.6 × 10¹1990mnene
723GNN (University of Siena, 2008)3 × 10¹3 × 10¹2008mnene
724ADALINE (Stanford University, 1960)1.7 × 10¹1.7 × 10¹1960mnene
725Samuel Neural Checkers (IBM, 1959)~1.6 × 10¹1959makadirio

Makundi ya pamoja

Chati hizi zinapanga jamii za wanyama, dini, mataifa, vyama na mashirika kwa njia mbili. Moja ni kwa wanachama. Nyingine ni kwa niuroni sawia, ambazo zinampa kila mwanachama uzito kulingana na sehemu ya muda wake wa kuamka ambao maagizo ya kundi yanauelekeza. Kanuni za kidini, sheria, kanuni za vyama na maelezo ya kazi vyote vinahesabiwa vivyo hivyo. Vyote ni seti za maagizo, kwa hiyo tunavipima kwa kanuni ileile. Jinsi muda unaoelekezwa unavyokadiriwa.

Wanachama wa kundi la kawaida × niuroni katika gamba au pallium ya kila mwanachama (ubongo mzima kwa wadudu), kwa kipimo cha logarithmiki. Nguzo zenye michirizi hutumia ukubwa wa kundi uliokadiriwa au idadi ya niuroni ya spishi jamaa.
  1. Jamii ya sokwe mtu▲17.4 × 10¹¹
  2. Koloni la chungu wakata-majani▼16.3 × 10¹¹
  3. Jamii ya bonobo▲24.4 × 10¹¹
  4. Kambi ya Wahadza (binadamu, kwa kulinganisha ukubwa)4.1 × 10¹¹
  5. Kundi la orca wa Bigg▼22.6 × 10¹¹
  6. Ukoo wa kike wa orca wakazi2.4 × 10¹¹
  7. Kundi la nyani wa savanna8.6 × 10¹⁰
  8. Muungano wa pomboo wenye pua ya chupa▲17.6 × 10¹⁰
  9. Kitengo cha kijamii cha nyangumi mbegu▲16.4 × 10¹⁰
  10. Koloni la nyuki wa asali▼25.8 × 10¹⁰
  11. Familia ya tembo5.6 × 10¹⁰
  12. Kundi la kunguru wa pinyon5.3 × 10¹⁰
  13. Ukoo wa fisi madoa2.2 × 10¹⁰
  14. Kundi la mbwa mwitu wa Afrika7.2 × 10⁹
  15. Kundi la mbwa mwitu4.2 × 10⁹
  16. Kundi la suricati1.7 × 10⁹
  17. Koloni la panya-fuko wasio na manyoya4.1 × 10⁸
Onyesha nambari
#KundiNiuroni katika kundiKatika shughuli ya kikundiWanachamaSehemu inayoelekezwaAina za miito
1Jamii ya sokwe mtu7.4 × 10¹¹2.5 × 10¹¹10034%—
2Koloni la chungu wakata-majani6.3 × 10¹¹5 × 10¹¹milioni 2.580%—
3Jamii ya bonobo4.4 × 10¹¹1.9 × 10¹¹5943%—
4Kambi ya Wahadza (binadamu, kwa kulinganisha ukubwa)4.1 × 10¹¹2.1 × 10¹¹2553%—
5Kundi la orca wa Bigg2.6 × 10¹¹2.4 × 10¹¹691%—
6Ukoo wa kike wa orca wakazi2.4 × 10¹¹1.7 × 10¹¹670%11
7Kundi la nyani wa savanna8.6 × 10¹⁰5.2 × 10¹⁰3060%9
8Muungano wa pomboo wenye pua ya chupa7.6 × 10¹⁰4.2 × 10¹⁰655%—
9Kitengo cha kijamii cha nyangumi mbegu6.4 × 10¹⁰4.1 × 10¹⁰865%—
10Koloni la nyuki wa asali5.8 × 10¹⁰4.9 × 10¹⁰60,00085%—
11Familia ya tembo5.6 × 10¹⁰3.2 × 10¹⁰1057%—
12Kundi la kunguru wa pinyon5.3 × 10¹⁰3.2 × 10¹⁰10060%—
13Ukoo wa fisi madoa2.2 × 10¹⁰6.7 × 10⁹4530%11
14Kundi la mbwa mwitu wa Afrika7.2 × 10⁹4.8 × 10⁹1467%11
15Kundi la mbwa mwitu4.2 × 10⁹2.6 × 10⁹863%—
16Kundi la suricati1.7 × 10⁹1 × 10⁹1557%12
17Koloni la panya-fuko wasio na manyoya4.1 × 10⁸2.9 × 10⁸7870%—

Jinsi makundi yanavyopewa alama.

Wafuasi, kwa kipimo cha logarithmiki. Madhehebu na harakati zinaonyeshwa tofauti na dini zinazozijumuisha. Nguzo imara ni hesabu; nguzo zenye michirizi ni makadirio.
  1. Ukristo▲1bilioni 2.27
  2. Uislamu▼1bilioni 2.02
  3. Uhindubilioni 1.18
  4. Dini za kienyejimilioni 400
  5. Ubuddhamilioni 324.19
  6. Dini za jadi za Kiafrika▲1milioni 98.73
  7. Shinto▲1milioni 87.92
  8. Usikhi▲1milioni 25
  9. Uyahudi▼3milioni 14.78
  10. Utao▲1milioni 8
  11. Imani ya Baháʼí▲1milioni 8
  12. Falun Gong▲1milioni 7
  13. Ujaini▼3milioni 4.45
  14. Uspiritistimilioni 3.8
  15. Cao Đàimilioni 2.5
  16. Tenrikyomilioni 1.12
  17. Brahma Kumarismilioni 1
Onyesha nambari
#DiniWanachamaKufuata maagizo yakeSehemu inayoelekezwaSaa kwa wiki
1Ukristobilioni 2.271.7 × 10¹⁸0.88%0.9 h
2Uislamubilioni 2.028.9 × 10¹⁸5.1%5.4 h
3Uhindubilioni 1.181.6 × 10¹⁸1.6%1.6 h
4Dini za kienyejimilioni 4002 × 10¹⁷0.59% (mbadala)0.6 h
5Ubuddhamilioni 324.197.5 × 10¹⁶0.27%0.3 h
6Dini za jadi za Kiafrikamilioni 98.735 × 10¹⁶0.59% (mbadala)0.6 h
7Shintomilioni 87.924.5 × 10¹⁶0.59% (mbadala)0.6 h
8Usikhimilioni 253.7 × 10¹⁶1.7%1.8 h
9Uyahudimilioni 14.785.3 × 10¹⁶4.2%4.4 h
10Utaomilioni 84.1 × 10¹⁵0.59% (mbadala)0.6 h
11Imani ya Baháʼímilioni 84.1 × 10¹⁵0.59% (mbadala)0.6 h
12Falun Gongmilioni 73.6 × 10¹⁵0.59% (mbadala)0.6 h
13Ujainimilioni 4.451.8 × 10¹⁶4.6%4.8 h
14Uspiritistimilioni 3.81.9 × 10¹⁵0.59% (mbadala)0.6 h
15Cao Đàimilioni 2.51.3 × 10¹⁵0.59% (mbadala)0.6 h
16Tenrikyomilioni 1.125.7 × 10¹⁴0.59% (mbadala)0.6 h
17Brahma Kumarismilioni 15.1 × 10¹⁴0.59% (mbadala)0.6 h

Kila desturi, sehemu na chanzo.

Idadi ya watu, kwa kipimo cha logarithmiki. Nguzo imara ni hesabu; nguzo zenye michirizi ni makadirio.
  1. India▲1bilioni 1.46
  2. China▼1bilioni 1.41
  3. Marekanimilioni 341.78
  4. Indonesiamilioni 285.72
  5. Pakistan▲5milioni 255.22
  6. Nigeria▲1milioni 237.53
  7. Brazili▼2milioni 212.81
  8. Bangladesh▲5milioni 175.69
  9. Urusi▼3milioni 143.51
  10. Ethiopia▲7milioni 135.47
  11. Meksiko▼2milioni 131.95
  12. Japani▲11milioni 123.37
  13. Misri▼2milioni 118.37
  14. Ufilipinomilioni 116.79
  15. DR Kongo▼3milioni 112.83
Onyesha nambari
#TaifaWakaziKufuata maagizo yakeSehemu inayoelekezwaSaa kwa wiki
1Indiabilioni 1.462.5 × 10¹⁸2%2.1 h
2Chinabilioni 1.415 × 10¹⁸4.1%4.3 h
3Marekanimilioni 341.781.6 × 10¹⁸5.6%5.8 h
4Indonesiamilioni 285.721 × 10¹⁸4.2%4.4 h
5Pakistanmilioni 255.225.7 × 10¹⁷2.6%2.7 h
6Nigeriamilioni 237.536.6 × 10¹⁷3.2%3.4 h
7Brazilimilioni 212.818.7 × 10¹⁷4.8%5 h
8Bangladeshmilioni 175.694.6 × 10¹⁷3%3.1 h
9Urusimilioni 143.517.5 × 10¹⁷6.1%6.4 h
10Ethiopiamilioni 135.473.9 × 10¹⁷3.4%3.5 h
11Meksikomilioni 131.955.9 × 10¹⁷5.2%5.5 h
12Japanimilioni 123.372.8 × 10¹⁷2.7%2.8 h
13Misrimilioni 118.375.5 × 10¹⁷5.4%5.7 h
14Ufilipinomilioni 116.794.4 × 10¹⁷4.4%4.6 h
15DR Kongomilioni 112.834.7 × 10¹⁷4.8%5.1 h
16Vietnammilioni 101.64.2 × 10¹⁷4.8%5 h
17Iranmilioni 92.423.5 × 10¹⁷4.3%4.6 h
18Uturukimilioni 85.884.3 × 10¹⁷5.8%6 h
19Ujerumanimilioni 83.492.9 × 10¹⁷4%4.2 h
20Thailandmilioni 71.622.4 × 10¹⁷3.9%4.1 h
21Tanzaniamilioni 70.552.2 × 10¹⁷3.6%3.8 h
22Uingerezamilioni 69.492.8 × 10¹⁷4.6%4.8 h
23Ufaransamilioni 68.723.1 × 10¹⁷5.3%5.5 h
24Afrika Kusinimilioni 64.752.9 × 10¹⁷5.1%5.4 h
25Italiamilioni 58.922.1 × 10¹⁷4.2%4.4 h
26Kenyamilioni 57.532.3 × 10¹⁷4.7%5 h
27Myanmarmilioni 54.851.9 × 10¹⁷4%4.2 h
28Kolombiamilioni 53.431.7 × 10¹⁷3.7%3.9 h
29Korea Kusinimilioni 51.681.4 × 10¹⁷3%3.2 h
30Sudanmilioni 51.661.5 × 10¹⁷3.4%3.6 h
31Ugandamilioni 51.381.5 × 10¹⁷3.4%3.6 h
32Uhispaniamilioni 49.361.8 × 10¹⁷4.2%4.3 h
33Aljeriamilioni 47.443.2 × 10¹⁷7.9%8.3 h
34Irakimilioni 47.021.1 × 10¹⁷2.8%2.9 h
35Ajentinamilioni 45.851.7 × 10¹⁷4.4%4.6 h
36Afghanistanmilioni 43.841.8 × 10¹⁷4.8%5 h
37Yemenmilioni 41.771.3 × 10¹⁷3.7%3.9 h
38Kanadamilioni 41.652 × 10¹⁷5.5%5.8 h
39Angolamilioni 39.041.4 × 10¹⁷4.2%4.4 h
40Ukrainemilioni 38.982.1 × 10¹⁷6.2%6.5 h
41Morokomilioni 38.431.5 × 10¹⁷4.5%4.7 h
42Uzbekistanmilioni 37.052 × 10¹⁷6.3%6.6 h
43Saudi Arabiamilioni 36.971.4 × 10¹⁷4.3%4.6 h
44Polandmilioni 36.442.1 × 10¹⁷6.7%7 h
45Malaysiamilioni 35.981.8 × 10¹⁷5.8%6.1 h
46Msumbijimilioni 35.631.5 × 10¹⁷4.8%5.1 h
47Ghanamilioni 35.061.2 × 10¹⁷3.9%4.1 h
48Perumilioni 34.581.4 × 10¹⁷4.8%5 h
49Madagaskamilioni 32.749.4 × 10¹⁶3.3%3.5 h
50Côte d’Ivoiremilioni 32.719.5 × 10¹⁶3.4%3.5 h
51Kamerunmilioni 29.889.8 × 10¹⁶3.8%4 h
52Nepalmilioni 29.621.1 × 10¹⁷4.2%4.4 h
53Venezuelamilioni 28.521.5 × 10¹⁷6.1%6.4 h
54Nigermilioni 27.926.4 × 10¹⁶2.6%2.8 h
55Australiamilioni 27.611.1 × 10¹⁷4.7%5 h
56Korea Kaskazinimilioni 26.576.6 × 10¹⁷29%30.1 h
57Syriamilioni 25.629.8 × 10¹⁶4.4%4.6 h
58Malimilioni 25.24.9 × 10¹⁶2.3%2.4 h
59Burkina Fasomilioni 24.075.7 × 10¹⁶2.8%2.9 h
60Taiwanmilioni 23.311 × 10¹⁷5%5.3 h
61Malawimilioni 22.221 × 10¹⁷5.4%5.6 h
62Zambiamilioni 21.9110 × 10¹⁶5.3%5.5 h
63Sri Lankamilioni 21.761.1 × 10¹⁷6%6.3 h
64Chadimilioni 214.9 × 10¹⁶2.7%2.9 h
65Kazakhstanmilioni 20.841.4 × 10¹⁷7.6%7.9 h
66Chilemilioni 19.866.2 × 10¹⁶3.6%3.8 h
67Somaliamilioni 19.651.5 × 10¹⁶0.88%0.9 h
68Romaniamilioni 19.027.5 × 10¹⁶4.6%4.8 h
69Senegalmilioni 18.935.9 × 10¹⁶3.6%3.8 h
70Guatemalamilioni 18.696 × 10¹⁶3.7%3.9 h
71Ekuadomilioni 18.296.6 × 10¹⁶4.2%4.4 h
72Uholanzimilioni 18.097.6 × 10¹⁶4.9%5.1 h
73Kambodiamilioni 17.857.4 × 10¹⁶4.8%5.1 h
74Zimbabwemilioni 16.956.1 × 10¹⁶4.2%4.4 h
75Guineamilioni 15.13.1 × 10¹⁶2.4%2.5 h
76Beninmilioni 14.814.4 × 10¹⁶3.4%3.6 h
77Rwandamilioni 14.577 × 10¹⁶5.6%5.8 h
78Burundimilioni 14.395.2 × 10¹⁶4.2%4.4 h
79Boliviamilioni 12.585.8 × 10¹⁶5.4%5.6 h
80Tunisiamilioni 12.356.4 × 10¹⁶6%6.3 h
81Sudan Kusinimilioni 12.194.4 × 10¹⁶4.2%4.4 h
82Ubelgijimilioni 11.944.5 × 10¹⁶4.3%4.5 h
83Haitimilioni 11.911.9 × 10¹⁶1.8%1.9 h
84Yordanimilioni 11.524.9 × 10¹⁶5%5.2 h
85Jamhuri ya Dominikamilioni 11.524.9 × 10¹⁶4.9%5.2 h
86Falme za Kiarabumilioni 11.513.1 × 10¹⁶3.1%3.2 h
87Hondurasmilioni 11.013.2 × 10¹⁶3.3%3.5 h
88Cubamilioni 10.941.6 × 10¹⁷17%17.4 h
89Chekiamilioni 10.895.8 × 10¹⁶6.2%6.5 h
90Urenomilioni 10.85.1 × 10¹⁶5.5%5.7 h
91Tajikistanmilioni 10.795.3 × 10¹⁶5.7%6 h
92Papua New Guineamilioni 10.764.3 × 10¹⁶4.6%4.8 h
93Uswidimilioni 10.66.8 × 10¹⁶7.5%7.8 h
94Ugirikimilioni 10.414.9 × 10¹⁶5.4%5.7 h
95Azerbaijanmilioni 10.256.2 × 10¹⁶7%7.4 h
96Israelimilioni 10.126.4 × 10¹⁶7.3%7.7 h
97Hungariamilioni 9.515.7 × 10¹⁶6.9%7.3 h
98Austriamilioni 9.212.5 × 10¹⁶3.2%3.4 h
99Uswisimilioni 9.093.9 × 10¹⁶5%5.3 h
100Belarusmilioni 9.097.9 × 10¹⁶10%10.6 h
101Sierra Leonemilioni 8.824.9 × 10¹⁶6.5%6.8 h
102Togomilioni 8.593 × 10¹⁶4%4.2 h
103Laosmilioni 7.873.2 × 10¹⁶4.8%5 h
104Turkmenistanmilioni 7.624.2 × 10¹⁶6.5%6.8 h
105Libyamilioni 7.463.9 × 10¹⁶6.1%6.4 h
106Kyrgyzstanmilioni 7.344.1 × 10¹⁶6.5%6.8 h
107Paraguaymilioni 7.012.9 × 10¹⁶4.8%5.1 h
108Nikaraguamilioni 7.012.8 × 10¹⁶4.6%4.8 h
109Serbiamilioni 6.554.1 × 10¹⁶7.2%7.5 h
110Jamhuri ya Kongomilioni 6.481.7 × 10¹⁶3%3.1 h
111Bulgariamilioni 6.433.3 × 10¹⁶5.9%6.2 h
112El Salvadormilioni 6.373.2 × 10¹⁶5.8%6.1 h
113Singaporemilioni 6.111.9 × 10¹⁶3.6%3.7 h
114Denmarkmilioni 6.013.9 × 10¹⁶7.6%8 h
115Lebanonmilioni 5.851.5 × 10¹⁶3%3.1 h
116Liberiamilioni 5.731.5 × 10¹⁶3.1%3.3 h
117Ufinimilioni 5.653.2 × 10¹⁶6.6%6.9 h
118Norwemilioni 5.613.7 × 10¹⁶7.6%8 h
119Jamhuri ya Afrika ya Katimilioni 5.511.7 × 10¹⁶3.5%3.7 h
120Omanimilioni 5.492.9 × 10¹⁶6.2%6.5 h
121Ayalandimilioni 5.483.4 × 10¹⁶7.2%7.6 h
122Slovakiamilioni 5.413.1 × 10¹⁶6.7%7 h
123Palestinamilioni 5.412 × 10¹⁶4.3%4.5 h
124New Zealandmilioni 5.322.7 × 10¹⁶5.9%6.2 h
125Mauritaniamilioni 5.322 × 10¹⁶4.3%4.5 h
126Kosta Rikamilioni 5.152.6 × 10¹⁶5.9%6.2 h
127Kuwaitmilioni 4.872.7 × 10¹⁶6.5%6.8 h
128Panamamilioni 4.572.3 × 10¹⁶5.9%6.2 h
129Georgiamilioni 3.942.1 × 10¹⁶6.1%6.4 h
130Kroatiamilioni 3.882.2 × 10¹⁶6.7%7 h
131Eritreamilioni 3.611.5 × 10¹⁶5%5.2 h
132Mongoliamilioni 3.572.2 × 10¹⁶7%7.3 h
133Uruguaymilioni 3.381.7 × 10¹⁶5.9%6.2 h
134Bosnia na Herzegovinamilioni 3.141.6 × 10¹⁶5.9%6.2 h
135Namibiamilioni 3.091.8 × 10¹⁶6.9%7.2 h
136Armeniamilioni 3.091.7 × 10¹⁶6.5%6.8 h
137Qatarmilioni 2.979.6 × 10¹⁵3.8%3.9 h
138Lithuaniamilioni 2.891.8 × 10¹⁶7.4%7.7 h
139Jamaicamilioni 2.841.2 × 10¹⁶5%5.2 h
140Gambiamilioni 2.821.1 × 10¹⁶4.5%4.7 h
141Gabonmilioni 2.599.9 × 10¹⁵4.4%4.6 h
142Botswanamilioni 2.561.3 × 10¹⁶5.7%6 h
143Lesothomilioni 2.369.5 × 10¹⁵4.7%4.9 h
144Moldovamilioni 2.361.5 × 10¹⁶7.3%7.6 h
145Albaniamilioni 2.351.2 × 10¹⁶5.7%6 h
146Guinea-Bissaumilioni 2.255.7 × 10¹⁵2.9%3.1 h
147Sloveniamilioni 2.131.2 × 10¹⁶6.6%6.9 h
148Guinea ya Ikwetamilioni 1.944 × 10¹⁵2.4%2.5 h
149Latviamilioni 1.851.2 × 10¹⁶7.6%7.9 h
150Makedonia Kaskazinimilioni 1.829.2 × 10¹⁵5.9%6.2 h
151Baharenimilioni 1.65.9 × 10¹⁵4.3%4.5 h
152Kosovomilioni 1.588 × 10¹⁵5.9%6.2 h
153Timor-Lestemilioni 1.428 × 10¹⁵6.6%6.9 h
154Kupromilioni 1.375.5 × 10¹⁵4.7%4.9 h
155Trinidad na Tobagomilioni 1.379.3 × 10¹⁵7.9%8.2 h
156Estoniamilioni 1.378.3 × 10¹⁵7%7.4 h
157Eswatinimilioni 1.267.5 × 10¹⁵6.9%7.2 h
158Mauritiusmilioni 1.245.1 × 10¹⁵4.8%5 h
159Djiboutimilioni 1.184.6 × 10¹⁵4.5%4.8 h
160Fiji933,1545.6 × 10¹⁵7%7.4 h
161Komoro882,8473.5 × 10¹⁵4.6%4.8 h
162Visiwa vya Solomon838,6453.2 × 10¹⁵4.4%4.6 h
163Guyana835,9864.6 × 10¹⁵6.4%6.7 h
164Bhutan796,6825.8 × 10¹⁵8.5%8.9 h
165Luxembourg686,9702.4 × 10¹⁵4%4.2 h
166Suriname639,8503.7 × 10¹⁵6.7%7.1 h
167Montenegro623,1294.3 × 10¹⁵8.1%8.5 h
168Malta579,7043.1 × 10¹⁵6.2%6.5 h
169Maldives529,6764.7 × 10¹⁵10%10.8 h
170Cape Verde527,3263.3 × 10¹⁵7.2%7.6 h
171Brunei466,3303.6 × 10¹⁵8.9%9.3 h
172Belize422,9241.1 × 10¹⁵2.9%3.1 h
173Bahama403,0332.2 × 10¹⁵6.4%6.7 h
174Aisilandi392,4042.5 × 10¹⁵7.4%7.7 h
175Vanuatu335,1692 × 10¹⁵6.9%7.3 h
176Barbados282,6231.5 × 10¹⁵6%6.3 h
177São Tomé na Príncipe240,2541.1 × 10¹⁵5.4%5.7 h
178Samoa219,3061.1 × 10¹⁵5.7%5.9 h
179Saint Lucia180,1499.3 × 10¹⁴6%6.3 h
180Kiribati136,4887.6 × 10¹⁴6.4%6.7 h
181Shelisheli122,7308.9 × 10¹⁴8.4%8.8 h
182Grenada117,3037.3 × 10¹⁴7.2%7.5 h
183Mikronesia113,6835.7 × 10¹⁴5.8%6.1 h
184Tonga103,7425.9 × 10¹⁴6.6%6.9 h
185Saint Vincent na Grenadines99,9244.9 × 10¹⁴5.7%5.9 h
186Antigua na Barbuda94,2096.5 × 10¹⁴8%8.3 h
187Andorra82,9043.9 × 10¹⁴5.5%5.8 h
188Dominika65,8712.3 × 10¹⁴4.1%4.3 h
189Saint Kitts na Nevis46,9222.1 × 10¹⁴5.2%5.5 h
190Liechtenstein41,0242 × 10¹⁴5.7%5.9 h
191Monaco38,3412.3 × 10¹⁴6.9%7.3 h
192Visiwa vya Marshall36,2823.3 × 10¹⁴10%10.9 h
193San Marino34,1091.3 × 10¹⁴4.6%4.8 h
194Palau17,6631.6 × 10¹⁴10%11 h
195Nauru12,0259.3 × 10¹³9%9.4 h
196Tuvalu9,4928 × 10¹³9.8%10.2 h

Kinachohesabiwa, na kisichohesabiwa.

Wanachama kama chama kinavyoripoti, kwa kipimo cha logarithmiki. Nguzo imara ni hesabu; nguzo zenye michirizi ni makadirio au madai.
  1. Bharatiya Janata Party (India)▲1milioni 140
  2. Chama cha Kikomunisti cha China▼1milioni 101.29
  3. Democratic Party (Marekani)▲13milioni 44.9
  4. Republican Party (Marekani)▲16milioni 38
  5. Indian National Congress▼2milioni 26
  6. AIADMK (India)▼2milioni 20.04
  7. DMK (India)▼2milioni 20
  8. Prosperity Party (Ethiopia)▼1milioni 15.7
  9. TVK (India)▼1milioni 15
  10. Chama Cha Mapinduzi (Tanzania)▼1milioni 13
  11. All Progressives Congress (Nigeria)▼1milioni 12.9
  12. AK Party (Uturuki)▼1milioni 11.71
  13. Morena (Meksiko)▼1milioni 11.63
  14. Telugu Desam Party (India)▼1milioni 10.05
  15. Cambodian People’s Party▼1milioni 7
Onyesha nambari
#ChamaWanachamaKufuata maagizo yakeSehemu inayoelekezwaSaa kwa wiki
1Bharatiya Janata Party (India)milioni 1406.3 × 10¹⁶0.52% (mbadala)0.6 h
2Chama cha Kikomunisti cha Chinamilioni 101.298.2 × 10¹⁶0.94%1 h
3Democratic Party (Marekani)milioni 44.92.3 × 10¹⁵0.06%0.1 h
4Republican Party (Marekani)milioni 382 × 10¹⁵0.06%0.1 h
5Indian National Congressmilioni 261.2 × 10¹⁶0.52% (mbadala)0.6 h
6AIADMK (India)milioni 20.049 × 10¹⁵0.52% (mbadala)0.6 h
7DMK (India)milioni 209 × 10¹⁵0.52% (mbadala)0.6 h
8Prosperity Party (Ethiopia)milioni 15.77 × 10¹⁵0.52% (mbadala)0.6 h
9TVK (India)milioni 156.7 × 10¹⁵0.52% (mbadala)0.6 h
10Chama Cha Mapinduzi (Tanzania)milioni 135.8 × 10¹⁵0.52% (mbadala)0.6 h
11All Progressives Congress (Nigeria)milioni 12.95.8 × 10¹⁵0.52% (mbadala)0.6 h
12AK Party (Uturuki)milioni 11.715.2 × 10¹⁵0.52% (mbadala)0.6 h
13Morena (Meksiko)milioni 11.635.2 × 10¹⁵0.52% (mbadala)0.6 h
14Telugu Desam Party (India)milioni 10.054.5 × 10¹⁵0.52% (mbadala)0.6 h
15Cambodian People’s Partymilioni 73.1 × 10¹⁵0.52% (mbadala)0.6 h
16Workers’ Party of Koreamilioni 6.187.6 × 10¹⁵1.4%1.5 h
17FRELIMO (Msumbiji)milioni 62.7 × 10¹⁵0.52% (mbadala)0.6 h
18Chama cha Kikomunisti cha Vietnammilioni 5.62.1 × 10¹⁵0.44%0.5 h
19Democratic Party of Koreamilioni 52.2 × 10¹⁵0.52% (mbadala)0.6 h
20People Power Party (Korea Kusini)milioni 4.442 × 10¹⁵0.52% (mbadala)0.6 h
21PSUV (Venezuela)milioni 4.241.9 × 10¹⁵0.52% (mbadala)0.6 h
22ZANU-PF (Zimbabwe)milioni 4.061.8 × 10¹⁵0.52% (mbadala)0.6 h
23UMNO (Malaysia)milioni 3.251.5 × 10¹⁵0.52% (mbadala)0.6 h
24Justicialist Party (Ajentina)milioni 3.11.4 × 10¹⁵0.52% (mbadala)0.6 h
25Colorado Party (Paraguay)milioni 31.3 × 10¹⁵0.52% (mbadala)0.6 h
26United Russiamilioni 2.61.2 × 10¹⁵0.52% (mbadala)0.6 h
27UzLiDeP (Uzbekistan)milioni 2.311 × 10¹⁵0.52% (mbadala)0.6 h
28PLD (Jamhuri ya Dominika)milioni 2.189.7 × 10¹⁴0.52% (mbadala)0.6 h
29MDB (Brazili)milioni 2.029 × 10¹⁴0.52% (mbadala)0.6 h
30CHP (Uturuki)milioni 1.888.4 × 10¹⁴0.52% (mbadala)0.6 h
31Radical Civic Union (Ajentina)milioni 1.798 × 10¹⁴0.52% (mbadala)0.6 h
32Workers’ Party, PT (Brazili)milioni 1.677.5 × 10¹⁴0.52% (mbadala)0.6 h
33PRM (Jamhuri ya Dominika)milioni 1.556.9 × 10¹⁴0.52% (mbadala)0.6 h
34Authentic Radical Liberal Party (Paraguay)milioni 1.556.9 × 10¹⁴0.52% (mbadala)0.6 h
35Partido Federal ng Pilipinasmilioni 1.56.7 × 10¹⁴0.52% (mbadala)0.6 h
36PAS (Malaysia)milioni 1.35.8 × 10¹⁴0.52% (mbadala)0.6 h
37PRD (Brazili)milioni 1.295.8 × 10¹⁴0.52% (mbadala)0.6 h
38Progressistas (Brazili)milioni 1.295.8 × 10¹⁴0.52% (mbadala)0.6 h
39PSDB (Brazili)milioni 1.265.6 × 10¹⁴0.52% (mbadala)0.6 h
40PKR (Malaysia)milioni 1.155.2 × 10¹⁴0.52% (mbadala)0.6 h
41Economic Freedom Fighters (Afrika Kusini)milioni 1.094.9 × 10¹⁴0.52% (mbadala)0.6 h
42PDT (Brazili)milioni 1.074.8 × 10¹⁴0.52% (mbadala)0.6 h
43União Brasilmilioni 1.074.8 × 10¹⁴0.52% (mbadala)0.6 h
44CPI(M) (India)milioni 1.024.6 × 10¹⁴0.52% (mbadala)0.6 h
45Liberal Democratic Party (Japani)milioni 14.5 × 10¹⁴0.52% (mbadala)0.6 h
46FLN (Aljeria)milioni 14.5 × 10¹⁴0.52% (mbadala)0.6 h
47Liberal Party, PL (Brazili)952,8814.3 × 10¹⁴0.52% (mbadala)0.6 h
48Chama cha Kikomunisti cha Cuba700,0002.7 × 10¹⁴0.44%0.5 h
49African National Congress688,4543.1 × 10¹⁴0.52% (mbadala)0.6 h
50Conservative Party of Canada678,7082.7 × 10¹⁴0.46%0.5 h
51CDU (Ujerumani)364,2021.6 × 10¹⁴0.52% (mbadala)0.6 h
52SPD (Ujerumani)357,1161.6 × 10¹⁴0.52% (mbadala)0.6 h
53Labour Party (Uingereza)333,2351.6 × 10¹⁴0.55%0.6 h
54Liberal Party of Canada163,8366.5 × 10¹³0.46%0.5 h
55Greens (Ujerumani)155,2967 × 10¹³0.52% (mbadala)0.6 h
56CSU (Ujerumani)125,1535.6 × 10¹³0.52% (mbadala)0.6 h
57Conservative Party (Uingereza)123,0003.7 × 10¹³0.35%0.4 h
58New Democratic Party (Kanada)100,5424 × 10¹³0.46%0.5 h
59AfD (Ujerumani)51,3352.3 × 10¹³0.52% (mbadala)0.6 h

Mikutano, tafiti na vyanzo.

Wafanyakazi katika ripoti ya mwaka au orodha ya karibuni zaidi, kwa kipimo cha mstari.
  1. Walmartmilioni 2.1
  2. Amazon▲1milioni 1.58
  3. State Grid▼1milioni 1.36
  4. China National Petroleummilioni 1.03
  5. JD.com951,420
  6. BYD▲1869,622
  7. Accenture▼1779,000
  8. Allied Universal▲3770,000
  9. China Post Group▼1719,448
  10. Reli za Urusi (RZD)▲2677,363
  11. Volkswagen Group▲6662,942
  12. Foxconn (Hon Hai)▼2633,167
  13. Schwarz Group▲16604,000
  14. Compass Group▲18590,000
  15. Tata Consultancy Services▼6584,510
Onyesha nambari
#ShirikaWafanyakaziKufuata maagizo yakeSaa kwa wikiSehemu inayoelekezwa
1Walmartmilioni 2.16.3 × 10¹⁶36.3 h (Marekani)35%
2Amazonmilioni 1.584.7 × 10¹⁶36.3 h (Marekani)35%
3State Gridmilioni 1.365.5 × 10¹⁶49 h (China)47%
4China National Petroleummilioni 1.034.1 × 10¹⁶49 h (China)47%
5JD.com951,4203.8 × 10¹⁶49 h (China)47%
6BYD869,6223.5 × 10¹⁶49 h (China)47%
7Accenture779,0003.7 × 10¹⁶57.58 h (India)55%
8Allied Universal770,0002.3 × 10¹⁶36.52 h (Marekani)35%
9China Post Group719,4482.9 × 10¹⁶49 h (China)47%
10Reli za Urusi (RZD)677,3632.2 × 10¹⁶39.96 h (Urusi)38%
11Volkswagen Group662,9422 × 10¹⁶35.95 h (Ujerumani)34%
12Foxconn (Hon Hai)633,1672.5 × 10¹⁶49 h (China)47%
13Schwarz Group604,0001.6 × 10¹⁶31.49 h (Ujerumani)30%
14Compass Group590,0001.5 × 10¹⁶31.7 h (Marekani)30%
15Tata Consultancy Services584,5102.8 × 10¹⁶58.23 h (India)56%
16DHL Group583,9981.7 × 10¹⁶35.81 h (Ujerumani)34%
17Sinopec513,4342.1 × 10¹⁶49 h (China)47%
18Gazprom501,0001.7 × 10¹⁶40.47 h (Urusi)39%
19FedEx474,2001.6 × 10¹⁶39.98 h (Marekani)38%
20Home Depot470,0001.4 × 10¹⁶36.3 h (Marekani)35%
21China Mobile468,4961.9 × 10¹⁶49 h (China)47%
22UPS460,0001.5 × 10¹⁶39.98 h (Marekani)38%
23Agricultural Bank of China457,8351.8 × 10¹⁶49 h (China)47%
24Concentrix455,0001.7 × 10¹⁶46.71 h (Ufilipino)45%
25Teleperformance446,7162.2 × 10¹⁶58.89 h (India)56%
26Jardine Matheson443,0001.5 × 10¹⁶41.93 h (Indonesia)40%
27Sodexo426,4641.1 × 10¹⁶31.7 h (Marekani)30%
28Capgemini423,4002 × 10¹⁶58.23 h (India)56%
29Reliance Industries419,9112.1 × 10¹⁶59.57 h (India)57%
30Edeka417,5001.1 × 10¹⁶31.49 h (Ujerumani)30%
31Luxshare Precision416,1971.7 × 10¹⁶49 h (China)47%
32Target415,0001.2 × 10¹⁶36.3 h (Marekani)35%
33Marriott International414,0001.1 × 10¹⁶31.7 h (Marekani)30%
34Bosch412,4001.2 × 10¹⁶35.95 h (Ujerumani)34%
35ICBC409,7581.6 × 10¹⁶49 h (China)47%
36Kroger403,0001.2 × 10¹⁶36.3 h (Marekani)35%
37China Resources397,3981.6 × 10¹⁶49 h (China)47%
38Magnit394,0001.3 × 10¹⁶39.69 h (Urusi)38%
39Toyota390,9271.3 × 10¹⁶39.6 h (Japani)38%
40UnitedHealth Group390,0001.2 × 10¹⁶36.87 h (Marekani)35%
41X5 Group389,0001.3 × 10¹⁶39.69 h (Urusi)38%
42Berkshire Hathaway387,8001.2 × 10¹⁶37.75 h (Marekani)36%
43AVIC384,0001.5 × 10¹⁶49 h (China)47%
44Ahold Delhaize384,0001.1 × 10¹⁶36.3 h (Marekani)35%
45China Telecom381,4361.5 × 10¹⁶49 h (China)47%
46Starbucks381,0009.9 × 10¹⁵31.7 h (Marekani)30%
47Rewe Group380,0009.8 × 10¹⁵31.49 h (Ujerumani)30%
48China Construction Bank378,3441.5 × 10¹⁶49 h (China)47%
49TJX Companies377,0001.1 × 10¹⁶36.3 h (Marekani)35%
50China State Construction Engineering370,2721.5 × 10¹⁶49 h (China)47%
51FEMSA368,7761.4 × 10¹⁶47.09 h (Meksiko)45%
52Japan Post Holdings360,0001.2 × 10¹⁶41.6 h (Japani)40%
53Tesco354,7449.3 × 10¹⁵31.81 h (Uingereza)30%
54Cognizant351,6001.7 × 10¹⁶58.23 h (India)56%
55NTT344,1961.1 × 10¹⁶40.2 h (Japani)38%
56Costco341,0001 × 10¹⁶36.3 h (Marekani)35%
57Infosys328,5941.6 × 10¹⁶58.23 h (India)56%
58ISS325,0001.6 × 10¹⁶58.89 h (India)56%
59Securitas322,0009.7 × 10¹⁵36.52 h (Marekani)35%
60HCA Healthcare320,0009.7 × 10¹⁵36.87 h (Marekani)35%
61Rosneft320,0001.1 × 10¹⁶40.47 h (Urusi)39%
62JPMorgan Chase318,5121.1 × 10¹⁶40.14 h (Marekani)38%
63Siemens318,0009.4 × 10¹⁵35.95 h (Ujerumani)34%
64Bank of China313,7461.3 × 10¹⁶49 h (China)47%
65Walgreens Boots Alliance312,0009.3 × 10¹⁵36.3 h (Marekani)35%
66PepsiCo306,0001 × 10¹⁶40.7 h (Marekani)39%
67China Railway Construction (CRCC)304,9271.2 × 10¹⁶49 h (China)47%
68CHN Energy (China Energy Investment)303,4181.2 × 10¹⁶49 h (China)47%
69China Railway Group (CREC)302,5271.2 × 10¹⁶49 h (China)47%
70CK Hutchison300,0008.6 × 10¹⁵35.08 h (Uingereza)33%
71CVS Health300,0008.9 × 10¹⁵36.3 h (Marekani)35%

Saa na vyanzo.

Wanyama na viumbe wengine

Kutoka seli moja isiyo na niuroni hadi ubongo wa binadamu. Idadi za niuroni zimepimwa pale zinapopatikana.

Hakuna niuroni

  • Escherichia coliEscherichia coli0 imepimwaSeli moja isiyo na niuroni. Huelekea kwenye chakula na ina kumbukumbu ya kikemikali inayodumu sekunde chache.
  • Ukungu wa utePhysarum polycephalum0 imepimwaSeli moja kubwa isiyo na niuroni. Hutatua labirinti na hukuza mitandao bora ya usafirishaji.
  • Mmea nyetiMimosa pudica0 imepimwaMmea ambao majani yake hujikunja yakiguswa. Utafiti mmoja uliripoti kwamba hujifunza kupuuza miguso isiyo na madhara. Uchambuzi wa baadaye ulipinga hilo.
  • SponjiPorifera (k.m. Amphimedon queenslandica)0 imepimwaMnyama asiye na niuroni wala sinapsi ambaye bado hujikunja mwili mzima kwa njia iliyoratibiwa.

Mitandao ya neva, bila ubongo

  • HydraHydra vulgaristakriban 3,000 hadi 5,000 makadirioKiumbe mdogo wa maji baridi wa kundi la cnidaria. Anadhibitiwa na mtandao wa neva uliotawanyika na hana ubongo.
  • Jellyfish wa boksiTripedalia cystophoraHakuna hesabu iliyochapishwaJellyfish wa boksi hana ubongo wa kati, lakini alionyesha kujifunza kwa kuhusisha.

Wanyama wasio na uti wa mgongo wenye ubongo

  • Mnyoo duaraCaenorhabditis elegans302 imepimwaMnyoo wa urefu wa takriban milimita moja mwenye niuroni 302 kamili. Ndiye mnyama wa kwanza ambaye mchoro kamili wa nyaya zake ulichorwa.
  • Inzi wa matundaDrosophila melanogaster139,255 imepimwaMchoro kamili mkubwa zaidi wa nyaya za ubongo uliochorwa hadi sasa, unaojumuisha takriban niuroni 139,000.
  • Nyuki wa asaliApis melliferatakriban milioni 1 makadirioTakriban niuroni milioni moja, na nyuki wanaweza kujifunza dhana dhahania kama sawa na tofauti.
  • Chungu (Camponotus / Formica)Camponotus spp.Hakuna hesabu iliyochapishwaUbongo mdogo unaoshughulikia uelekezaji wa umbali mrefu kwa kuhesabu hatua (ujumlishaji wa njia) na kukumbuka alama za mahali.
  • Buibui anayeruka wa PortiaPortia fimbriata / labiataHakuna hesabu iliyochapishwaBuibui anayeruka anayepanga njia za kuzunguka. Huchukua njia zinazomwongoza mbali na windo lake na nje ya macho yake.
  • Kaa wa pwani / kamba-majiCarcinus maenas; Procambarus / Astacus spp.Hakuna hesabu iliyochapishwaKaa na kamba-maji. Mapitio ya serikali ya 2021 yalipata ushahidi mkubwa kwamba kaa halisi wana uwezo wa kuhisi.
  • Pweza wa kawaidaOctopus vulgarismilioni 500 makadirioNiuroni zake nyingi ziko katika mikono yake. Mapitio ya 2021 yalipata ushahidi wenye nguvu sana kwamba ana uwezo wa kuhisi.

Samaki na amfibia

  • ZebrafishDanio rerioHakuna hesabu iliyochapishwaSamaki mdogo anayetumika sana katika neurosayansi. Niuroni zake hazijahesabiwa kikamilifu. Ubongo wa mtu mzima una takriban seli milioni 10.
  • Samaki msafishajiLabroides dimidiatusHakuna hesabu iliyochapishwaSamaki wa miamba aliyefaulu toleo la jaribio la alama ya kioo. Watu hawakubaliani kuhusu kinachoonyeshwa na hilo.
  • ChuraAnura (k.m. Xenopus / Rana)Hakuna hesabu iliyochapishwaAzimio la New York la 2024 linasema kuna uwezekano halisi wa uzoefu wa fahamu kwa amfibia.

Ndege

  • Njiwa wa mwambaColumba liviamilioni 310 imepimwaMamia ya mamilioni ya niuroni katika ubongo mdogo. Njiwa wanaweza kupanga picha tata katika makundi.
  • Kunguru mkubwaCorvus coraxbilioni 2.17 imepimwaZaidi ya niuroni bilioni mbili, zilizosongamana. Kunguru hukumbuka washindani mmojammoja.
  • Kunguru wa New CaledoniaCorvus moneduloidesHakuna hesabu iliyochapishwaHutengeneza zana zenye ndoana kutoka vijiti na waya. Niuroni zake hazijahesabiwa.
  • Kasuku wa kijivu wa AfrikaPsittacus erithacusbilioni 1.57 imepimwaTakriban niuroni bilioni 1.6. Miongo ya utafiti wa maabara kuhusu hisia ya idadi na uainishaji.

Mammals

  • PanyaMus musculusmilioni 70.9 imepimwaTakriban niuroni milioni 71. Panya huonyesha sura za uso za maumivu zinazoweza kupimwa.
  • PanyaRattus norvegicusmilioni 200 imepimwaTakriban niuroni milioni 200. Panya huwaachilia wenzao waliofungiwa.
  • Paka wa nyumbaniFelis catusbilioni 1.22 imepimwaTakriban niuroni milioni 250 katika gamba la ubongo.
  • Mbwa wa nyumbaniCanis familiarisbilioni 1.8 hadi 2.6, kutegemea mbwa imepimwaHadi takriban niuroni milioni 600 za gamba, kutegemea mbwa. Hiyo ni zaidi ya paka.
  • Nguruwe wa nyumbaniSus scrofa domesticusbilioni 2.22 imepimwaNguruwe hujifunza kioo kinaonyesha nini na kukitumia kupata chakula.
  • Pomboo mwenye pua ya chupaTursiops truncatusHakuna hesabu iliyochapishwaHufaulu majaribio ya kujitambua kwenye kioo. Hakuna idadi ya niuroni iliyopimwa kwa pomboo mwenye pua ya chupa.
  • Tembo wa AfrikaLoxodonta africanabilioni 257 imepimwaNiuroni bilioni 257, mara tatu ya binadamu, karibu zote katika cerebellum.
  • Sokwe mtuPan troglodytestakriban bilioni 28 (imetabiriwa kutoka kanuni za kuongeza ukubwa, haijahesabiwa) makadirioMmoja wa jamaa zetu wawili walio hai walio karibu zaidi (pamoja na bonobo). Anafaulu jaribio la kioo.
  • BinadamuHomo sapiensbilioni 86.1 imepimwaNiuroni bilioni 86, bilioni 16 kati yake katika gamba la ubongo. Sisi ndio spishi pekee ambayo wanachama wake wanaweza kutoa ripoti za maneno kuhusu uzoefu wao.

Mifumo ya pamoja

Vikundi vinavyofanya maamuzi ambayo mwanachama mmoja hawezi kuyafanya peke yake. Husomwa kama akili ya pamoja, si kama akili.

  • Makoloni ya chunguMakoloni huchagua kiota bora kwa sababu kila chungu hufuata kizingiti cha akidi. Hakuna chungu kinacholinganisha maeneo kwa ujumla.
  • Makundi ya nyuki wa asaliMakundi huchagua pango bora kupitia ushindani kati ya wapelelezi na akidi. Ishara za kusimamisha hutoa ukandamizaji wa pande zote, unaovunja mkwamo.
  • Makundi ya shorweKila ndege hufuatilia idadi maalum ya jirani (takriban 6-7), si kila ndege aliye ndani ya umbali maalum. Hii inaitwa mwingiliano wa kitopolojia, si wa kimetriki.
  • Makundi ya samakiMakundi hutumia kanuni za akidi kuamua. Makundi makubwa yanaweza kuhisi miteremko ya kimazingira ambayo samaki mmoja hawezi kuihisi.

Mifumo bandia

Aina za akili za mashine, zilizopangwa kwa jinsi zinavyofanya kazi. Hakuna mfumo wa sasa unaochukuliwa kuwa mgombea madhubuti wa fahamu.

  • Mifumo ya wataalamu inayotegemea kanuniProgramu zinazoweka maarifa ya mtaalamu wa fani kama kanuni dhahiri za kama-basi. Injini ya makisio hutumia kanuni hizo kwa mfuatano kufikia hitimisho, kwa kawaida pamoja na maelezo ya hoja yake.
  • Injini za utafutaji wa mti wa mchezo (chesi)Programu zinazohesabu mfuatano wa hatua zinazowezekana hadi kina kisichobadilika na kutoa alama kwa nafasi zinazotokea kwa kutumia kitendakazi cha tathmini kilichotengenezwa kwa mkono. Hukata matawi yasiyoweza kubadilisha uchaguzi (minimax pamoja na alpha-beta pruning).
  • Mawakala wa kujifunza kwa uimarishaji wa kinaMitandao ya neva iliyofunzwa kwa kujaribu na kukosea ili kuongeza ishara ya zawadi. Hujifunza sera au kitendakazi cha thamani kwa kuingiliana na mazingira, mara nyingi yaliyoigwa kama mchezo.
  • Modeli kubwa za lughaMitandao ya neva ya Transformer iliyofunzwa kutabiri tokeni inayofuata katika mkusanyiko mkubwa sana wa maandishi, kisha mara nyingi hurekebishwa kwa maoni ya binadamu.
  • Roboti zenye miiliMashine zenye vihisi na viendeshaji zinazotenda katika ulimwengu wa kimwili. Mara nyingi hutumia udhibiti wa kuitikia wa tabaka badala ya modeli kuu ya dunia, kwa hiyo tabia hujitokeza kutoka mzunguko kati ya mwili na mazingira.
  • Maunzi ya neuromorphicChipu ambazo saketi zake huiga niuroni na sinapsi zinazotoa mipigo. Zinaendeshwa na matukio na hutumia nguvu kidogo, tofauti na muundo wa kawaida wa kichakataji na kumbukumbu.

Akili za kudhania

Akili zilizopendekezwa katika maandiko ya kisayansi na kifalsafa. Hakuna aliyewahi kuona hata moja.

  • Uigaji wa ubongo mzimahaijaonekanaKuchanganua ubongo kwa undani mdogo na kuendesha modeli yake ya programu.
  • Akili zilizoigwa katika uigaji wa mababuhaijaonekanaMkanganyiko wa pande tatu wa Bostrom: ama karibu hakuna ustaarabu unaofikia hatua ya baada ya binadamu, au karibu hakuna unaoendesha uigaji wa mababu, au karibu hakika tunaishi ndani ya mmoja.
  • Ubongo wa BoltzmannhaijaonekanaWaangalizi wanaofanana na ubongo wanaotokea kutokana na mabadiliko nadra ya joto au ya kwanta.
  • Kupakia akili kwa kubadilisha taratibuhaijaonekanaKubadilisha niuroni moja baada ya nyingine kwa sehemu bandia zenye kazi inayofanana.
  • Akili kuuhaijaonekanaAkili ya kudhania inayozidi sana utendaji wa binadamu karibu katika nyanja zote. Kitabu cha Bostrom kinachambua njia za kuifikia (uigaji wa ubongo mzima, utambuzi wa kibiolojia, AI), aina zake na matatizo ya udhibiti.

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