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Agents · steerability

Agent Arena signal scores from the official dataset. Each signal is a separate measurement; it is not a success percentage.

58 entries · IPS score · Higher is better

Source publication: 2026-11-04. Retrieved 2026-11-05.

Source: Arena (lmarena-ai) · CC-BY-4.0.

Ranks use confidence bounds. Several models can share a rank; the rows within a shared rank are displayed by score.

Agents · steerability · IPS score
Significance rankModel / evaluated variantIPS score95% confidence intervalObservations
1Gemini 4 Carbon (High)google0.1931930.186058 – 0.200328208,968
1Claude Opus 5.5 (Max)anthropic0.1842830.164043 – 0.20452336,292
2Claude Fable 5.1 (Max)anthropic0.1531560.134094 – 0.17221873,015
2GPT-6.1 Terra (Max)openai0.1518240.137996 – 0.165653118,771
3GPT-6 Astra (Max)openai0.1433370.124192 – 0.16248147,375
3Gemini 4 Argon (High)google0.1351830.125582 – 0.144784262,052
3GPT-6.1 Sol (Max)openai0.1328920.121901 – 0.14388296,131
3Claude Sonnet 5.5 (Max)anthropic0.1239930.094852 – 0.15313417,559
8Muse Wonder Full (Max)meta0.1065080.095924 – 0.117091186,836
8GPT-6 Sol (Max)openai0.0998330.08273 – 0.11693767,078
8Claude Fable 5 (High)anthropic0.087920.074152 – 0.101689167,982
10Hy4tencent0.0660520.045166 – 0.08693835,444
11Kimi K3.1 Pro (Max)moonshot0.0655120.049588 – 0.081435136,888
11GPT-5.6 Sol (xHigh)openai0.0634160.049535 – 0.077296166,297
12Claude Opus 5 (Max)anthropic0.0531550.037246 – 0.069064104,038
14GPT-6 Luna (Max)openai0.0419430.036211 – 0.0476741,200,732
12Claude Sonnet 5 (High)anthropic0.0402540.023141 – 0.057368107,206
15DeepSeek-V4.1-Flash-20261017 (Max)deepseek0.0342440.026822 – 0.041665463,497
15Muse Spark 1.3 (Max)meta0.0339890.022938 – 0.045039473,413
14Claude Haiku 5.5 (High)anthropic0.0331420.020522 – 0.045761271,177
14Muse Wonder (Max)meta0.031220.013051 – 0.04939109,293
17MiMo-V2.6-Flashxiaomi0.0213730.007531 – 0.035216125,021
20MiMo-V2.6-Proxiaomi0.010054-0.002537 – 0.022645209,174
21GPT-5.6 Terra (xHigh)openai0.008166-0.002695 – 0.019027223,809
22GPT-6 Luna (Medium)openai0.003787-0.003537 – 0.01111469,939
22Kimi K3 (Max)moonshot0.001345-0.007038 – 0.009729551,540
22Hy4 previewtencent0.000677-0.009153 – 0.010508362,751
21Grok 4.6 (xHigh)xai0.000129-0.016779 – 0.017037120,399
22Gemini 3.8 Flash (High)google-0.002402-0.014105 – 0.009301267,511
23Qwen3.8-Maxalibaba-0.0025-0.012048 – 0.007049375,140
23GLM-5.2 (Max)zai-0.006041-0.017911 – 0.005829287,454
23GLM-5.3 (Max)zai-0.008613-0.019923 – 0.002696489,052
22Step 5 Previewstepfun-0.009274-0.028186 – 0.00963867,903
21DeepSeek-V4-Pro (High, 20260813)deepseek-0.010767-0.034778 – 0.01324428,886
23Grok 4.7 (xHigh)xai-0.017538-0.038141 – 0.00306596,104
27Hy3tencent-0.027983-0.047968 – -0.00799952,740
32GPT-6 Luna (Low)openai-0.028594-0.038498 – -0.01869306,594
32Qwen3.8-Flash-Nextalibaba-0.0296-0.040368 – -0.018832372,894
32MiniMax-M3.1-Flashminimax-0.040991-0.063658 – -0.01832443,964
34GLM-5.3-Flashzai-0.042344-0.053246 – -0.031442682,288
35Qwen3.8-27Balibaba-0.050645-0.064499 – -0.036791262,266
33Mistral Large 4mistral-0.053439-0.084036 – -0.02284220,703
38Gemini 3.7 Flash (High)google-0.05688-0.070904 – -0.042857297,633
38Gemini 3.1 Pro Previewgoogle-0.073129-0.100267 – -0.045991102,576
38Beam 1.0 501B A23Breflection-0.082169-0.118022 – -0.04631744,666
44MiniMax-M3minimax-0.106421-0.126475 – -0.08636786,817
44Spark-X2.6synlan-0.109344-0.131329 – -0.08735944,682
44Qwen3.7-Maxalibaba-0.110615-0.132567 – -0.088663102,402
44Qwen3.7-Plusalibaba-0.112893-0.139593 – -0.08619347,955
44Muse Spark 1.2 (xHigh)meta-0.114659-0.129305 – -0.100013299,841
47Muse Spark 1.1meta-0.141376-0.154434 – -0.128318473,139
46MiMo-V2.5-Proxiaomi-0.143846-0.164302 – -0.123391101,141
49Mistral Medium 3.5mistral-0.162347-0.19221 – -0.13248538,186
50Solar Pro 4upstage-0.170117-0.205238 – -0.13499733,962
52NVIDIA-Nemotron-3.5-Super-VL-120B-A12B (NVFP4)nvidia-0.171352-0.185482 – -0.157222117,690
46Nemotron 3 Ultranvidia-0.183118-0.243841 – -0.1223957,695
53Inklingthinky-0.205075-0.238765 – -0.17138550,902
56Inkling-Smallthinky-0.257505-0.293946 – -0.22106438,000

What this ranking can tell you

  • The population is the models in this source board, including variants and models without an available API price.
  • Ranks use the published confidence bounds: one plus the number of models whose lower bound exceeds this model’s upper bound. Shared ranks are not proof of equal performance.

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