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score
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-0.2
0.21
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float64
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0.18
score_ci_upper
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observation_count
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199k
41.4M
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5.17k
259k
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1
50
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2026-10-23 00:00:00
2026-10-23 00:00:00
Claude Opus 5.5 (Max)
anthropic
Proprietary
0.207665
0.183861
0.231468
1,751,647
12,057
1
overall
2026-10-23
Claude Sonnet 5.5 (Max)
anthropic
Proprietary
0.139887
0.109532
0.170241
1,054,171
8,097
2
overall
2026-10-23
GPT-6 Astra (Max)
openai
Proprietary
0.139611
0.118818
0.160404
1,132,157
14,567
3
overall
2026-10-23
Claude Fable 5.1 (Max)
anthropic
Proprietary
0.139417
0.120077
0.158758
2,055,139
17,062
4
overall
2026-10-23
GPT-6.1 Sol (Max)
openai
Proprietary
0.136435
0.120135
0.152735
1,343,948
16,092
5
overall
2026-10-23
Gemini 4 Argon (High)
google
Proprietary
0.117481
0.108365
0.126597
4,974,530
45,840
6
overall
2026-10-23
GPT-6 Sol (Max)
openai
Proprietary
0.085668
0.068527
0.102809
2,137,040
10,305
7
overall
2026-10-23
Claude Opus 5 (Max)
anthropic
Proprietary
0.082182
0.065891
0.098472
3,331,922
24,440
8
overall
2026-10-23
Claude Fable 5 (High)
anthropic
Proprietary
0.077526
0.063496
0.091557
2,664,967
43,567
9
overall
2026-10-23
GPT-5.6 Sol (xHigh)
openai
Proprietary
0.060554
0.047171
0.073937
4,679,840
37,542
10
overall
2026-10-23
Claude Sonnet 5 (High)
anthropic
Proprietary
0.037509
0.020522
0.054495
3,759,502
33,991
11
overall
2026-10-23
Muse Wonder (Max)
meta
Proprietary
0.033058
0.017342
0.048774
1,498,241
11,134
12
overall
2026-10-23
MiMo-V2.6-Pro
xiaomi
MIT
0.033049
0.024957
0.041141
4,281,990
43,983
13
overall
2026-10-23
Gemini 3.8 Flash (High)
google
Proprietary
0.031711
0.020956
0.042466
5,854,973
39,719
14
overall
2026-10-23
Muse Spark 1.3 (Max)
meta
Proprietary
0.030547
0.022246
0.038849
7,934,311
78,017
15
overall
2026-10-23
Grok 4.7 (xHigh)
xai
Proprietary
0.030231
0.014484
0.045977
2,906,258
16,639
16
overall
2026-10-23
GPT-6 Luna (Max)
openai
Proprietary
0.02794
0.023707
0.032173
30,165,039
194,437
17
overall
2026-10-23
DeepSeek-V4.1-Flash-20260910 (Max)
deepseek
MIT
0.022544
0.019095
0.025994
41,366,427
259,479
18
overall
2026-10-23
MiMo-V2.6-Flash
xiaomi
MIT
0.021024
0.007766
0.034282
2,527,967
22,895
19
overall
2026-10-23
Hy4 preview
tencent
Apache 2.0
0.020167
0.013799
0.026535
9,861,457
93,764
20
overall
2026-10-23
GLM-5.2 (Max)
zai
MIT
0.016943
0.008782
0.025104
7,332,857
90,051
21
overall
2026-10-23
Kimi K3 (Max)
moonshot
Kimi K3 license
0.015683
0.008205
0.023162
13,076,043
139,480
22
overall
2026-10-23
GLM-5.3 (Max)
zai
MIT
0.012161
0.003782
0.02054
9,782,984
88,117
23
overall
2026-10-23
Claude Haiku 5.5 (High)
anthropic
Proprietary
0.011393
0.001096
0.021691
3,217,098
27,887
24
overall
2026-10-23
Qwen3.8-Max
alibaba
Proprietary
0.011316
0.005231
0.017402
7,288,963
75,307
25
overall
2026-10-23
Grok 4.6 (xHigh)
xai
Proprietary
0.006273
-0.004918
0.017463
3,536,569
29,832
26
overall
2026-10-23
GPT-5.6 Terra (xHigh)
openai
Proprietary
0.002176
-0.010998
0.01535
1,809,056
25,167
27
overall
2026-10-23
DeepSeek-V4-Pro (High, 20260813)
deepseek
MIT
-0.002664
-0.019941
0.014613
876,123
7,331
28
overall
2026-10-23
Gemini 3.7 Flash (High)
google
Proprietary
-0.012719
-0.02235
-0.003089
5,147,550
56,113
29
overall
2026-10-23
GLM-5.3-Flash
zai
MIT
-0.017724
-0.024446
-0.011001
12,217,332
92,133
30
overall
2026-10-23
Step 5 Preview
stepfun
Proprietary
-0.020333
-0.034711
-0.005956
2,291,199
15,412
31
overall
2026-10-23
Beam 1.0 501B A23B
reflection
Apache 2.0
-0.030434
-0.055116
-0.005753
668,800
12,147
32
overall
2026-10-23
Qwen3.8-Flash-Next
alibaba
qwen-community-1.0
-0.032744
-0.039712
-0.025776
15,138,193
105,281
33
overall
2026-10-23
Qwen3.8-27B
alibaba
Apache 2.0
-0.041006
-0.0489
-0.033112
7,746,551
62,625
34
overall
2026-10-23
Gemini 3.1 Pro Preview
google
Proprietary
-0.044461
-0.057646
-0.031276
2,894,640
87,676
35
overall
2026-10-23
GPT-6 Luna (Low)
openai
Proprietary
-0.045879
-0.056035
-0.035722
1,238,895
18,454
36
overall
2026-10-23
Mistral Large 4
mistral
Proprietary
-0.050636
-0.070403
-0.030869
1,020,687
14,080
37
overall
2026-10-23
Qwen3.7-Max
alibaba
Proprietary
-0.064297
-0.075865
-0.052729
2,212,031
42,729
38
overall
2026-10-23
Hy3
tencent
Apache 2.0
-0.067973
-0.082419
-0.053527
1,195,407
31,979
39
overall
2026-10-23
Muse Spark 1.1
meta
Proprietary
-0.068642
-0.075119
-0.062165
8,224,614
149,239
40
overall
2026-10-23
Muse Spark 1.2 (xHigh)
meta
Proprietary
-0.070204
-0.078511
-0.061898
3,554,123
53,539
41
overall
2026-10-23
Qwen3.7-Plus
alibaba
Proprietary
-0.074437
-0.092128
-0.056745
1,221,691
23,985
42
overall
2026-10-23
MiMo-V2.5-Pro
xiaomi
MIT
-0.086591
-0.096637
-0.076546
2,490,489
49,530
43
overall
2026-10-23
MiniMax-M3
minimax
MiniMax Community License
-0.100701
-0.112778
-0.088624
3,451,566
43,703
44
overall
2026-10-23
Mistral Medium 3.5
mistral
Modified MIT
-0.121273
-0.138604
-0.103942
587,350
13,468
45
overall
2026-10-23
NVIDIA-Nemotron-3.5-Super-VL-120B-A12B (NVFP4)
nvidia
OpenMDW-1.1
-0.135592
-0.155505
-0.115679
236,111
5,172
46
overall
2026-10-23
Nemotron 3 Ultra
nvidia
OpenMDW-1.1
-0.147077
-0.186515
-0.107639
198,631
13,313
47
overall
2026-10-23
Inkling
thinky
Apache 2.0
-0.148993
-0.163389
-0.134596
1,707,437
43,905
48
overall
2026-10-23
Inkling-Small
thinky
Apache 2.0
-0.16139
-0.17935
-0.143431
536,405
14,421
49
overall
2026-10-23
Solar Pro 4
upstage
Proprietary
-0.202482
-0.224077
-0.180887
501,187
10,622
50
overall
2026-10-23

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_control
  • vision, vision_style_control
  • search, search_style_control
  • document, document_style_control
  • webdev (Code Arena)
  • text_to_image
  • image_edit
  • text_to_video
  • image_to_video
  • video_edit
  • agent (Agent Arena aggregate), plus per-signal subsets: agent_bash_recovery_steps, agent_praise_complaint, agent_steerability, agent_task_outcome_explicit, agent_tool_hallucination

Splits

  • full: All historically published leaderboards
  • latest: 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.

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 (τ̂)
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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