model_name stringlengths 3 46 | organization stringlengths 3 10 | license stringclasses 8
values | score float64 -0.21 0.21 | score_ci_lower float64 -0.23 0.19 | score_ci_upper float64 -0.19 0.23 | observation_count float64 216k 42.5M | session_count float64 7.71k 266k | rank int64 1 57 | category stringclasses 1
value | leaderboard_publish_date stringdate 2026-10-28 00:00:00 2026-10-28 00:00:00 |
|---|---|---|---|---|---|---|---|---|---|---|
Claude Opus 5.5 (Max) | anthropic | Proprietary | 0.209397 | 0.187882 | 0.230912 | 2,019,583 | 13,584 | 1 | overall | 2026-10-28 |
Gemini 4 Carbon (High) | google | Proprietary | 0.160387 | 0.150407 | 0.170367 | 3,581,185 | 26,511 | 2 | overall | 2026-10-28 |
Claude Sonnet 5.5 (Max) | anthropic | Proprietary | 0.138372 | 0.111865 | 0.164879 | 1,100,317 | 8,300 | 3 | overall | 2026-10-28 |
Claude Fable 5.1 (Max) | anthropic | Proprietary | 0.133523 | 0.114595 | 0.152452 | 2,176,172 | 17,347 | 4 | overall | 2026-10-28 |
GPT-6 Astra (Max) | openai | Proprietary | 0.129601 | 0.109425 | 0.149777 | 1,187,197 | 15,070 | 5 | overall | 2026-10-28 |
GPT-6.1 Sol (Max) | openai | Proprietary | 0.124667 | 0.113905 | 0.135429 | 2,491,780 | 28,883 | 6 | overall | 2026-10-28 |
Gemini 4 Argon (High) | google | Proprietary | 0.107272 | 0.099145 | 0.115399 | 5,552,564 | 50,974 | 7 | overall | 2026-10-28 |
GPT-6.1 Terra (Max) | openai | Proprietary | 0.10575 | 0.086151 | 0.125349 | 1,691,221 | 8,977 | 8 | overall | 2026-10-28 |
Muse Wonder Full (Max) | meta | Proprietary | 0.100896 | 0.091458 | 0.110335 | 3,922,185 | 26,753 | 9 | overall | 2026-10-28 |
Claude Fable 5 (High) | anthropic | Proprietary | 0.080371 | 0.069424 | 0.091317 | 3,344,866 | 50,866 | 10 | overall | 2026-10-28 |
GPT-6 Sol (Max) | openai | Proprietary | 0.079555 | 0.063242 | 0.095868 | 2,598,143 | 12,107 | 11 | overall | 2026-10-28 |
Claude Opus 5 (Max) | anthropic | Proprietary | 0.075659 | 0.063477 | 0.087842 | 4,435,133 | 31,777 | 12 | overall | 2026-10-28 |
Kimi K3.1 Pro (Max) | moonshot | Proprietary | 0.059556 | 0.043672 | 0.07544 | 3,350,156 | 14,300 | 13 | overall | 2026-10-28 |
GPT-5.6 Sol (xHigh) | openai | Proprietary | 0.047906 | 0.037595 | 0.058218 | 6,126,242 | 45,156 | 14 | overall | 2026-10-28 |
Muse Wonder (Max) | meta | Proprietary | 0.031376 | 0.016893 | 0.045859 | 1,808,022 | 12,530 | 15 | overall | 2026-10-28 |
Claude Sonnet 5 (High) | anthropic | Proprietary | 0.02941 | 0.01769 | 0.041129 | 4,886,376 | 41,456 | 16 | overall | 2026-10-28 |
MiMo-V2.6-Pro | xiaomi | MIT | 0.027706 | 0.01901 | 0.036402 | 4,802,357 | 46,354 | 17 | overall | 2026-10-28 |
DeepSeek-V4.1-Flash-20261017 (Max) | deepseek | MIT | 0.026749 | 0.020321 | 0.033176 | 13,758,007 | 54,255 | 18 | overall | 2026-10-28 |
Gemini 3.8 Flash (High) | google | Proprietary | 0.026495 | 0.018323 | 0.034668 | 7,867,776 | 52,730 | 19 | overall | 2026-10-28 |
Muse Spark 1.3 (Max) | meta | Proprietary | 0.025936 | 0.017782 | 0.03409 | 8,403,345 | 80,518 | 20 | overall | 2026-10-28 |
Grok 4.7 (xHigh) | xai | Proprietary | 0.023947 | 0.009388 | 0.038505 | 3,328,169 | 18,559 | 21 | overall | 2026-10-28 |
GPT-6 Luna (Max) | openai | Proprietary | 0.022257 | 0.018151 | 0.026364 | 34,619,592 | 217,544 | 22 | overall | 2026-10-28 |
DeepSeek-V4.1-Flash-20260910 (Max) | deepseek | MIT | 0.019122 | 0.015769 | 0.022474 | 42,504,300 | 266,436 | 23 | overall | 2026-10-28 |
Claude Haiku 5.5 (High) | anthropic | Proprietary | 0.014327 | 0.003826 | 0.024827 | 3,567,086 | 29,343 | 24 | overall | 2026-10-28 |
GLM-5.2 (Max) | zai | MIT | 0.012551 | 0.004894 | 0.020207 | 8,700,096 | 98,542 | 25 | overall | 2026-10-28 |
Hy4 preview | tencent | Apache 2.0 | 0.012239 | 0.005494 | 0.018984 | 10,555,916 | 98,590 | 26 | overall | 2026-10-28 |
Kimi K3 (Max) | moonshot | Kimi K3 license | 0.010787 | 0.005103 | 0.016471 | 15,590,153 | 160,249 | 27 | overall | 2026-10-28 |
MiMo-V2.6-Flash | xiaomi | MIT | 0.010019 | -0.001432 | 0.02147 | 2,995,304 | 26,781 | 28 | overall | 2026-10-28 |
GLM-5.3 (Max) | zai | MIT | 0.009119 | 0.001392 | 0.016846 | 10,997,629 | 96,109 | 29 | overall | 2026-10-28 |
Grok 4.6 (xHigh) | xai | Proprietary | 0.004874 | -0.006461 | 0.01621 | 3,647,053 | 30,228 | 30 | overall | 2026-10-28 |
Qwen3.8-Max | alibaba | Proprietary | 0.004482 | -0.001934 | 0.010898 | 7,792,769 | 78,349 | 31 | overall | 2026-10-28 |
DeepSeek-V4-Pro (High, 20260813) | deepseek | MIT | -0.003005 | -0.020015 | 0.014005 | 913,441 | 7,713 | 32 | overall | 2026-10-28 |
Gemini 3.7 Flash (High) | google | Proprietary | -0.013461 | -0.022062 | -0.00486 | 6,040,757 | 63,572 | 33 | overall | 2026-10-28 |
GPT-5.6 Terra (xHigh) | openai | Proprietary | -0.013902 | -0.021718 | -0.006087 | 3,502,716 | 44,232 | 34 | overall | 2026-10-28 |
GPT-6 Luna (Medium) | openai | Proprietary | -0.014928 | -0.02153 | -0.008326 | 5,026,725 | 46,849 | 35 | overall | 2026-10-28 |
GLM-5.3-Flash | zai | MIT | -0.023263 | -0.029969 | -0.016556 | 12,979,678 | 95,014 | 36 | overall | 2026-10-28 |
Step 5 Preview | stepfun | Proprietary | -0.026798 | -0.040251 | -0.013345 | 2,555,544 | 16,596 | 37 | overall | 2026-10-28 |
MiniMax-M3.1-Flash | minimax | MiniMax Community License | -0.03963 | -0.055536 | -0.023723 | 1,960,235 | 11,230 | 38 | overall | 2026-10-28 |
Qwen3.8-Flash-Next | alibaba | qwen-community-1.0 | -0.040227 | -0.047412 | -0.033041 | 15,862,412 | 108,316 | 39 | overall | 2026-10-28 |
Gemini 3.1 Pro Preview | google | Proprietary | -0.044514 | -0.05782 | -0.031208 | 2,936,702 | 87,905 | 40 | overall | 2026-10-28 |
Qwen3.8-27B | alibaba | Apache 2.0 | -0.044597 | -0.052766 | -0.036429 | 7,988,882 | 63,935 | 41 | overall | 2026-10-28 |
Beam 1.0 501B A23B | reflection | Apache 2.0 | -0.049272 | -0.072468 | -0.026077 | 686,396 | 12,324 | 42 | overall | 2026-10-28 |
Mistral Large 4 | mistral | Proprietary | -0.060237 | -0.081451 | -0.039023 | 1,038,308 | 14,147 | 43 | overall | 2026-10-28 |
GPT-6 Luna (Low) | openai | Proprietary | -0.062307 | -0.070059 | -0.054554 | 2,438,006 | 35,721 | 44 | overall | 2026-10-28 |
Qwen3.7-Max | alibaba | Proprietary | -0.065863 | -0.077712 | -0.054014 | 2,254,697 | 43,030 | 45 | overall | 2026-10-28 |
Hy3 | tencent | Apache 2.0 | -0.073191 | -0.087675 | -0.058707 | 1,214,847 | 32,396 | 46 | overall | 2026-10-28 |
Qwen3.7-Plus | alibaba | Proprietary | -0.073682 | -0.090765 | -0.0566 | 1,252,907 | 24,320 | 47 | overall | 2026-10-28 |
Muse Spark 1.2 (xHigh) | meta | Proprietary | -0.07538 | -0.083807 | -0.066953 | 3,734,181 | 54,813 | 48 | overall | 2026-10-28 |
Muse Spark 1.1 | meta | Proprietary | -0.076693 | -0.083237 | -0.070149 | 8,395,973 | 150,607 | 49 | overall | 2026-10-28 |
MiMo-V2.5-Pro | xiaomi | MIT | -0.089327 | -0.099402 | -0.079251 | 2,506,654 | 49,682 | 50 | overall | 2026-10-28 |
MiniMax-M3 | minimax | MiniMax Community License | -0.101617 | -0.11347 | -0.089763 | 3,541,903 | 44,123 | 51 | overall | 2026-10-28 |
Mistral Medium 3.5 | mistral | Modified MIT | -0.126475 | -0.143261 | -0.109689 | 633,506 | 13,796 | 52 | overall | 2026-10-28 |
NVIDIA-Nemotron-3.5-Super-VL-120B-A12B (NVFP4) | nvidia | OpenMDW-1.1 | -0.149439 | -0.161488 | -0.137389 | 649,638 | 13,260 | 53 | overall | 2026-10-28 |
Nemotron 3 Ultra | nvidia | OpenMDW-1.1 | -0.157569 | -0.190381 | -0.124757 | 216,338 | 13,536 | 54 | overall | 2026-10-28 |
Inkling | thinky | Apache 2.0 | -0.157995 | -0.172634 | -0.143357 | 1,729,803 | 44,144 | 55 | overall | 2026-10-28 |
Inkling-Small | thinky | Apache 2.0 | -0.170102 | -0.18845 | -0.151754 | 552,386 | 14,622 | 56 | overall | 2026-10-28 |
Solar Pro 4 | upstage | Proprietary | -0.207949 | -0.229567 | -0.186331 | 522,529 | 10,836 | 57 | overall | 2026-10-28 |
Arena Leaderboard Dataset
Historical snapshots of the Arena leaderboard.
Usage
from datasets import load_dataset
# Load all historical text style control data
ds = load_dataset("lmarena-ai/leaderboard-dataset", "text_style_control", split="full")
# Load the current text style control leaderboard
ds = load_dataset("lmarena-ai/leaderboard-dataset", "text_style_control", split="latest")
# Filter to overall category
ds = load_dataset("lmarena-ai/leaderboard-dataset", "text_style_control", split="latest",
filters=[("category", "==", "overall")]
)
# Track a specific model's rating over time
ds = load_dataset("lmarena-ai/leaderboard-dataset", "text_style_control", split="full",
filters=[("category", "==", "overall"), ("model_name", "==", "gpt-4o-2024-05-13")],
columns=["model_name", "rating", "rank", "leaderboard_publish_date"]
)
# Load raw (non-style-controlled) text ratings
ds = load_dataset("lmarena-ai/leaderboard-dataset", "text", split="full")
# Load the current Agent Arena leaderboard
ds = load_dataset("lmarena-ai/leaderboard-dataset", "agent", split="latest")
Subsets
Each arena is a separate subset, arenas with style control have an additional subset with a _style_control suffix .
text,text_style_controlvision,vision_style_controlsearch,search_style_controldocument,document_style_controlwebdev(Code Arena)text_to_imageimage_edittext_to_videoimage_to_videovideo_editagent(Agent Arena aggregate), plus per-signal subsets:agent_bash_recovery_steps,agent_bash_reliability,agent_praise_complaint,agent_steerability,agent_task_outcome_explicit,agent_tool_hallucination
Splits
full: All historically published leaderboardslatest: Only the most recently published leaderboards
Notes
- On January 9, 2024, the rating system was updated from Elo to Bradley-Terry.
- On May 16, 2025, style control was made the default for text and vision arenas and the offset was adjusted to put the style control leaderboard on the same rating scale as non style control.
- On July 23, 2025, frequency-based re-weighting was implemented.
- Search and Webdev Arena data starts from their releases on the arena.ai (then lmarena.ai) on August 7 and November 12 2025 respectively.
- Agent Arena data starts from its release on June 4, 2026.
- On October 12, 2026, the Agent Arena bash signal was switched from bash recovery to bash reliability.
For a complete record of all leaderboard methodology changes, see the Leaderboard Changelog.
Schema
| Column | Type | Description |
|---|---|---|
| model_name | string | Model identifier |
| organization | string | Model creator/organization |
| license | string | Model license |
| rating | float | Arena Score |
| rating_lower | float | Lower confidence bound |
| rating_upper | float | Upper confidence bound |
| variance | float | Rating variance |
| vote_count | int | Number of battles for this model |
| rank | int | Rank within this leaderboard |
| category | string | Leaderboard category (e.g., overall, coding, math) |
| leaderboard_publish_date | string | Date that this score was published (YYYY-MM-DD) |
Agent Arena subsets use IPS scores instead of Bradley-Terry:
| Column | Type | Description |
|---|---|---|
| model_name | string | Model identifier |
| organization | string | Model creator/organization |
| license | string | Model license |
| score | float | IPS score (ฯฬ) |
| score_ci_lower | float | Lower 95% confidence bound |
| score_ci_upper | float | Upper 95% confidence bound |
| observation_count | int | Signal observations for this model |
| session_count | int | Distinct sessions (aggregate subset only) |
| rank | int | Rank within this leaderboard |
| category | string | Leaderboard category |
| leaderboard_publish_date | string | Date that this score was published (YYYY-MM-DD) |
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