Vision Model Leaderboard: Best Vision-Language Models

Ranked by LMArena Vision Arena scores: users upload an image, ask a question, and vote between two anonymous models’ answers.

#1 CaptioningData Oct 19, 2026

In LMArena Vision Arena data published Oct 19, 2026, Anthropic’s Claude Fable 5 (High) ranks #1 of 167 models with 1325 (14,714 votes).

Full leaderboard · Captioning

34 models

Sorted by LMArena score by default; ± is half the 95% confidence interval. Category columns show the model’s score on that sub-board; – means no score.

# Model LMArena · Captioning License
Score Rank Votes
1 Mistral Small 3.2 (2506)Mistral AIOpen 1059±49 34 177 Apache 2.0
2 Mistral Medium 3 (2505)Mistral AI 1094±49 33 160 Proprietary
3 Gemini 2.0 Flash (001)Google 1130±61 32 106 Proprietary
4 Mistral Medium 3.1 (2508)Mistral AI 1145±30 31 403 Proprietary
5 Gemma 3 27B ITGoogleOpen 1151±39 30 258 Gemma
6 Mistral Small 3.1 24B Instruct (2503)Mistral AIOpen 1153±38 29 258 Apache 2.0
7 GPT-5.1OpenAI 1165±49 28 123 Proprietary
8 Qwen3.5-27BAlibabaOpen 1170±81 27 61 Apache 2.0
9 GPT-4.1 mini (2025-04-14)OpenAI 1174±32 25 394 Proprietary
10 GPT-5.2OpenAI 1174±55 26 107 Proprietary
11 Gemini 2.5 Flash-Lite Preview (Thinking, 06-17)Google 1184±32 24 384 Proprietary
12 o4-mini (2025-04-16)OpenAI 1204±30 22 423 Proprietary
13 GPT-5 (High)OpenAI 1204±32 23 356 Proprietary
14 GPT-4.1 (2025-04-14)OpenAI 1207±31 21 422 Proprietary
15 o3 (2025-04-16)OpenAI 1210±28 20 540 Proprietary
16 GPT-5 ChatOpenAI 1212±32 19 375 Proprietary
17 GPT-5 mini (High)OpenAI 1217±37 18 283 Proprietary
18 Gemma 4 31BGoogleOpen 1218±54 17 106 Apache 2.0
19 ChatGPT-4o Latest (20250326)OpenAI 1224±36 16 273 Proprietary
20 Qwen3.5-397B-A17BAlibabaOpen 1230±57 15 78 Apache 2.0
21 Gemini 3 Flash (Minimal)Google 1241±43 14 173 Proprietary
22 Grok 4 (0709)xAI 1245±34 13 351 Proprietary
23 GPT-5.1 (High)OpenAI 1252±55 12 101 Proprietary
24 Kimi K2.5 (Thinking)Moonshot AIOpen 1257±48 11 125 Modified MIT
25 Gemini 3.1 Flash-Lite PreviewGoogle 1259±64 10 73 Proprietary
26 GLM-5V-TurboZ.ai 1264±73 9 53 Proprietary
27 GPT-5.2 (High)OpenAI 1267±58 8 94 Proprietary
28 Gemini 2.5 FlashGoogle 1277±24 7 582 Proprietary
29 Qwen3-VL-235B-A22B-InstructAlibabaOpen 1281±45 5 146 Apache 2.0
30 Gemini 3 FlashGoogle 1281±39 6 191 Proprietary
31 Gemma 4 26B A4BGoogleOpen 1297±70 4 63 Apache 2.0
32 Gemini 2.5 ProGoogle 1304±23 3 796 Proprietary
33 Gemini 3 ProGoogle 1325±35 2 218 Proprietary
34 Gemini 3.1 Pro PreviewGoogle 1345±49 1 137 Proprietary

Scores: LMArena leaderboard-dataset (lmarena-ai on Hugging Face, CC-BY-4.0, vision config), Captioning published Oct 19, 2026. Please credit the source when citing.

Sources & methodology

  1. Scores are Bradley-Terry Arena ratings fitted from human votes between two anonymous answers to the same image prompt.
  2. Categories (OCR, diagrams, homework, captioning, Chinese/English…) are separate LMArena boards computed on prompts of that type, not a breakdown of the overall score; ranks can differ a lot.
  3. Fields without public data (price, context length, release date…) are not shown; blanks are –. Nothing is estimated.
  4. Synced daily. JSON API: /api/public/vision-leaderboard.php

This week

Collecting data: 1/7 days recorded; weekly changes appear after 7 days

Synced automatically once a day; ranks are compared only between real snapshots, never backfilled.

FAQ

What is the best vision-language model right now?

In LMArena Vision Arena data published Oct 19, 2026, Anthropic’s Claude Fable 5 (High) ranks #1 of 167 models with 1325 (14,714 votes).

What is each vendor’s best vision model?

Top overall entry per vendor: Anthropic Claude Fable 5 (High) (1325, #1), Google Gemini 3.8 Flash (High) (1315, #7), Alibaba Qwen3.8-Max (1313, #10), Meta Muse Spark 1.3 (Max) (1308, #12), OpenAI GPT-5.4 (High) (1303, #18).

Which model is best at OCR?

On LMArena’s OCR board (123 models), Claude Fable 5 (High) is #1 with 1337.

What is the best open-weight vision model?

50 open-weight models are listed; the top one is GLM-5.3-Flash (1294, MIT).

How is this different from benchmarks like MMMU?

MMMU and similar benchmarks auto-score a fixed question set; this board comes from blind human votes on people’s own images and questions, reflecting real-use preference. They are not convertible.