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Xem cách các công cụ AI được xếp hạng dựa trên độ linh hoạt, mức độ chính xác ngôn ngữ và hiệu quả xử lý trong các tác vụ văn bản

Rank  Rank Spread (Upper-Lower) Model Score 95% CI (±) Votes Organization License
1 1◄─►1
gemini-3-pro
1490 ±5 27.827 Google Proprietary
2 2◄─►4
grok-4.1-thinking
1477 ±5 27.985 xAI Proprietary
3 2◄─►8
gemini-3-flash
1472 ±6 13.245 Google Proprietary
4 2◄─►8
claude-opus-4-5-20251101-thinking-32k
1470 ±5 19.898 Anthropic Proprietary
5 3◄─►9
claude-opus-4-5-20251101
1467 ±5 21.241 Anthropic Proprietary
6 3◄─►9
grok-4.1
1465 ±5 32.015 xAI Proprietary
7 3◄─►10
gemini-3-flash (thinking-minimal)
1462 ±7 9.644 Google Proprietary
8 3◄─►15
ernie-5.0-0110
1459 ±9 4.829 Baidu Proprietary
9 5◄─►14
gpt-5.1-high
1458 ±5 24.439 OpenAI Proprietary
10 8◄─►18
gemini-2.5-pro
1451 ±3 87.641 Google Proprietary
11 8◄─►18
claude-sonnet-4-5-20250929-thinking-32k
1451 ±4 38.441 Anthropic Proprietary
12 7◄─►20
ernie-5.0-preview-1203
1450 ±7 9.709 Baidu Proprietary
13 8◄─►18
claude-sonnet-4-5-20250929
1450 ±4 35.025 Anthropic Proprietary
14 9◄─►18
claude-opus-4-1-20250805-thinking-16k
1449 ±4 50.061 Anthropic Proprietary
15 10◄─►20
claude-opus-4-1-20250805
1445 ±3 67.599 Anthropic Proprietary
16 8◄─►24
gpt-5.2
1445 ±9 5.187 OpenAI Proprietary
17 10◄─►22
gpt-4.5-preview-2025-02-27
1444 ±6 14.549 OpenAI Proprietary
18 14◄─►22
chatgpt-4o-latest-20250326
1442 ±3 74.853 OpenAI Proprietary
19 10◄─►25
glm-4.7
1441 ±7 9.556 Z.ai MIT
20 14◄─►33
gpt-5.2-high
1436 ±8 8.594 OpenAI Proprietary
21 16◄─►27
gpt-5.1
1435 ±5 26.241 OpenAI Proprietary
22 16◄─►28
gpt-5-high
1435 ±5 32.688 OpenAI Proprietary
23 18◄─►31
qwen3-max-preview
1434 ±5 27.894 Alibaba Proprietary
24 18◄─►32
o3-2025-04-16
1433 ±4 61.435 OpenAI Proprietary
25 19◄─►35
grok-4-1-fast-reasoning
1430 ±5 21.151 xAI Proprietary
26 20◄─►38
kimi-k2-thinking-turbo
1429 ±5 26.054 Moonshot Modified MIT
27 21◄─►44
gpt-5-chat
1426 ±4 31.883 OpenAI Proprietary
27 20◄─►46
ernie-5.0-preview-1103
1428 ±7 9.066 Baidu Proprietary
28 23◄─►45
glm-4.6
1425 ±4 33.537 Z.ai MIT
29 20◄─►45
qwen3-max-2025-09-23
1424 ±6 9.225 Alibaba Proprietary
30 24◄─►45
claude-opus-4-20250514-thinking-16k
1424 ±4 38.020 Anthropic Proprietary
31 22◄─►48
deepseek-v3.2-exp
1423 ±7 11.812 DeepSeek MIT
32 22◄─►48
deepseek-v3.2-exp-thinking
1423 ±7 9.017 DeepSeek MIT
33 26◄─►45
qwen3-235b-a22b-instruct-2507
1422 ±3 62.099 Alibaba Apache 2.0
34 22◄─►50
grok-4-fast-chat
1422 ±8 7.001 xAI Proprietary
35 26◄─►51
deepseek-v3.2-thinking
1420 ±6 15.802 DeepSeek MIT
36 27◄─►52
deepseek-v3.2
1418 ±5 20.503 DeepSeek MIT
37 27◄─►52
deepseek-r1-0528
1418 ±6 19.306 DeepSeek MIT
38 27◄─►53
kimi-k2-0905-preview
1418 ±6 11.981 Moonshot Modified MIT
39 25◄─►55
ernie-5.0-preview-1022
1417 ±9 4.643 Baidu Proprietary
40 27◄─►52
kimi-k2-0711-preview
1417 ±5 28.683 Moonshot Modified MIT
41 27◄─►53
deepseek-v3.1-thinking
1417 ±7 11.984 DeepSeek MIT
42 27◄─►53
deepseek-v3.1
1417 ±6 15.294 DeepSeek MIT
43 26◄─►57
deepseek-v3.1-terminus
1416 ±10 3.764 DeepSeek MIT
44 25◄─►57
deepseek-v3.1-terminus-thinking
1416 ±10 3.552 DeepSeek MIT
45 28◄─►55
qwen3-vl-235b-a22b-instruct
1415 ±6 11.700 Alibaba Apache 2.0
46 32◄─►53
claude-opus-4-20250514
1413 ±4 45.596 Anthropic Proprietary
47 32◄─►53
gpt-4.1-2025-04-14
1413 ±4 52.274 OpenAI Proprietary
48 34◄─►55
mistral-medium-2508
1412 ±3 55.868 Mistral Proprietary
48 39◄─►58
claude-haiku-4-5-20251001
1402 ±4 28.180 Anthropic Proprietary
49 32◄─►57
mistral-large-3
1411 ±5 16.782 Mistral Apache 2.0
49 39◄─►59
grok-4-fast-reasoning
1402 ±5 18.823 xAI Proprietary
50 34◄─►57
grok-3-preview-02-24
1410 ±4 33.991 xAI Proprietary
50 38◄─►56
gemini-2.5-flash
1408 ±3 79.419 Google Proprietary
50 36◄─►59
grok-4-0709
1409 ±4 42.343 xAI Proprietary
50 39◄─►60
gemini-2.5-flash-preview-09-2025
1405 ±4 31.666 Google Proprietary
50 42◄─►59
o1-2024-12-17
1401 ±4 28.039 OpenAI Proprietary
50 43◄─►61
qwen3-next-80b-a3b-instruct
1400 ±5 23.044 Alibaba Apache 2.0
50 34◄─►58
glm-4.5
1409 ±5 24.723 Z.ai MIT
Battle Count for Each Combination of Models (without Ties)
Confidence Intervals on Model Strength (Elo)
Elo scores computed from battle counts. Error bars = 95% CI via Bootstrapping.
Average Win Rate Against All Other Models (Uniform Sampling and No Ties)
Fraction of Model A Wins for All Non-tied A vs. B Battles