All rankings / Coding and agents

Agents · praise and complaints

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 · praise and complaints · IPS score
Significance rankModel / evaluated variantIPS score95% confidence intervalObservations
1Claude Opus 5.5 (Max)anthropic0.4291380.350451 – 0.5078251,761
1Gemini 4 Carbon (High)google0.4012040.373168 – 0.4292410,208
1GPT-6 Astra (Max)openai0.3274260.251388 – 0.4034632,577
1Claude Sonnet 5.5 (Max)anthropic0.2971190.189183 – 0.405054906
3Claude Fable 5.1 (Max)anthropic0.2797180.210859 – 0.3485763,286
3GPT-6.1 Sol (Max)openai0.274180.23419 – 0.314175,246
3Gemini 4 Argon (High)google0.2286610.199718 – 0.25760312,485
5GPT-6.1 Terra (Max)openai0.173160.124935 – 0.2213855,399
7Muse Wonder Full (Max)meta0.1626150.132263 – 0.1929678,487
8Claude Fable 5 (High)anthropic0.1505190.114535 – 0.18650314,520
8Claude Opus 5 (Max)anthropic0.1192390.078104 – 0.1603758,202
8GPT-6 Sol (Max)openai0.1045670.053437 – 0.1556982,974
10Kimi K3.1 Pro (Max)moonshot0.0845860.044398 – 0.1247735,688
8Hy4tencent0.0732770.012746 – 0.1338072,084
11GPT-5.6 Sol (xHigh)openai0.0571360.024533 – 0.0897413,030
12Gemini 3.8 Flash (High)google0.0526420.027479 – 0.07780614,974
12MiMo-V2.6-Proxiaomi0.0475310.019632 – 0.07542911,318
12GLM-5.3 (Max)zai0.0437490.019977 – 0.06752130,739
12Grok 4.7 (xHigh)xai0.028642-0.016926 – 0.0742094,637
13GLM-5.2 (Max)zai0.023170.000209 – 0.04613125,273
13Muse Spark 1.3 (Max)meta0.021459-0.003868 – 0.04678722,469
14DeepSeek-V4.1-Flash-20261017 (Max)deepseek0.0191340.001722 – 0.03654620,235
14Kimi K3 (Max)moonshot0.013673-0.00356 – 0.03090547,105
12DeepSeek-V4-Pro (High, 20260813)deepseek0.007327-0.044369 – 0.0590221,608
16Qwen3.8-Maxalibaba0.002303-0.017554 – 0.02215921,636
16Hy4 previewtencent0.002149-0.019223 – 0.0235218,086
14Muse Wonder (Max)meta-0.002547-0.043264 – 0.038174,607
15MiMo-V2.6-Flashxiaomi-0.004816-0.036304 – 0.0266716,895
16Claude Sonnet 5 (High)anthropic-0.010621-0.04571 – 0.02446810,020
20GPT-6 Luna (Max)openai-0.011909-0.025529 – 0.0017151,440
19GPT-5.6 Terra (xHigh)openai-0.015536-0.03881 – 0.00773913,527
16Gemini 3.1 Pro Previewgoogle-0.01573-0.052227 – 0.02076827,127
18Grok 4.6 (xHigh)xai-0.018784-0.052966 – 0.0153989,204
19Gemini 3.7 Flash (High)google-0.021198-0.045039 – 0.00264323,463
26GLM-5.3-Flashzai-0.041176-0.060267 – -0.02208434,330
23Claude Haiku 5.5 (High)anthropic-0.041512-0.07253 – -0.0104939,012
23Step 5 Previewstepfun-0.05228-0.09329 – -0.011273,676
27Qwen3.8-Flash-Nextalibaba-0.055707-0.076563 – -0.03485220,972
18Beam 1.0 501B A23Breflection-0.058608-0.130476 – 0.0132592,370
27Qwen3.8-27Balibaba-0.059754-0.084265 – -0.03524316,954
34GPT-6 Luna (Medium)openai-0.067973-0.08351 – -0.05243619,400
27MiniMax-M3.1-Flashminimax-0.075768-0.121125 – -0.0304112,768
33Hy3tencent-0.087397-0.124632 – -0.0501635,277
36Qwen3.7-Maxalibaba-0.094479-0.12537 – -0.06358713,141
40GPT-6 Luna (Low)openai-0.104209-0.123519 – -0.084912,382
37Qwen3.7-Plusalibaba-0.113007-0.151859 – -0.0741566,885
36Mistral Large 4mistral-0.118175-0.170074 – -0.0662761,228
41Muse Spark 1.2 (xHigh)meta-0.128443-0.149827 – -0.1070617,621
41Muse Spark 1.1meta-0.134359-0.149585 – -0.11913343,694
41MiMo-V2.5-Proxiaomi-0.140347-0.164706 – -0.11598913,202
46MiniMax-M3minimax-0.160778-0.187038 – -0.13451812,413
46Mistral Medium 3.5mistral-0.185879-0.222649 – -0.1491083,307
41Nemotron 3 Ultranvidia-0.190939-0.263249 – -0.1186291,290
49Spark-X2.6synlan-0.194626-0.226611 – -0.1626412,513
52NVIDIA-Nemotron-3.5-Super-VL-120B-A12B (NVFP4)nvidia-0.222581-0.241094 – -0.2040676,427
52Inkling-Smallthinky-0.227703-0.263055 – -0.1923513,487
52Solar Pro 4upstage-0.24175-0.281444 – -0.2020562,314
52Inklingthinky-0.246344-0.272172 – -0.22051610,406

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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