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.
- Top open-weight
GLM-5.3-Flash1363Z.ai
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 · Chinese
128 modelsSorted 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 · Chinese | License | ||
|---|---|---|---|---|---|
| Score↓ | Rank | Votes | |||
| 1 | 1416±39 | 1 | 224 | Proprietary | |
| 2 | 1400±20 | 2 | 1,037 | Proprietary | |
| 3 | 1394±34 | 3 | 302 | Proprietary | |
| 4 | 1391±35 | 4 | 284 | Proprietary | |
| 5 | 1384±36 | 5 | 257 | Proprietary | |
| 6 | 1377±22 | 6 | 847 | Proprietary | |
| 7 | 1375±22 | 7 | 818 | Proprietary | |
| 8 | 1373±23 | 8 | 784 | Proprietary | |
| 9 | 1371±18 | 9 | 1,504 | Proprietary | |
| 10 | 1370±17 | 10 | 1,687 | Proprietary | |
| 11 | 1370±17 | 11 | 1,681 | Proprietary | |
| 12 | 1368±34 | 12 | 290 | Proprietary | |
| 13 | 1367±18 | 13 | 1,487 | Proprietary | |
| 14 | 1364±13 | 14 | 3,186 | Proprietary | |
| 15 | 1363±23 | 15 | 699 | MIT | |
| 16 | 1361±37 | 16 | 259 | Proprietary | |
| 17 | 1360±17 | 17 | 1,777 | Proprietary | |
| 18 | 1358±26 | 18 | 541 | Proprietary | |
| 19 | 1357±26 | 19 | 536 | Proprietary | |
| 20 | 1357±17 | 20 | 1,603 | Proprietary | |
| 21 | 1355±18 | 21 | 1,388 | Proprietary | |
| 22 | 1354±16 | 22 | 1,846 | Proprietary | |
| 23 | 1348±22 | 23 | 767 | Proprietary | |
| 24 | 1347±28 | 24 | 493 | Proprietary | |
| 25 | 1346±20 | 25 | 1,027 | Modified MIT | |
| 26 | 1346±20 | 26 | 1,131 | Proprietary | |
| 27 | 1345±23 | 27 | 728 | Proprietary | |
| 28 | 1342±20 | 28 | 1,030 | Proprietary | |
| 29 | 1337±22 | 29 | 869 | Proprietary | |
| 30 | 1337±24 | 30 | 682 | Proprietary | |
| 31 | 1336±19 | 31 | 1,356 | Proprietary | |
| 32 | 1332±23 | 32 | 740 | Proprietary | |
| 33 | 1331±22 | 33 | 847 | Proprietary | |
| 34 | 1329±14 | 34 | 2,644 | Proprietary | |
| 35 | 1329±14 | 35 | 2,749 | Proprietary | |
| 36 | 1328±34 | 36 | 273 | Modified MIT | |
| 37 | 1327±42 | 37 | 199 | MIT | |
| 38 | 1326±14 | 38 | 2,734 | Apache 2.0 | |
| 39 | 1326±17 | 39 | 1,580 | MIT | |
| 40 | 1326±30 | 40 | 409 | Apache 2.0 | |
| 41 | 1324±16 | 41 | 1,767 | Modified MIT | |
| 42 | 1317±14 | 42 | 2,539 | Proprietary | |
| 43 | 1314±15 | 43 | 2,045 | Apache 2.0 | |
| 44 | 1313±24 | 44 | 677 | Proprietary | |
| 45 | 1312±17 | 45 | 1,609 | Apache 2.0 | |
| 46 | 1311±20 | 46 | 1,048 | MiniMax Community License | |
| 47 | 1311±27 | 47 | 524 | Proprietary | |
| 48 | 1307±17 | 48 | 1,736 | Proprietary | |
| 49 | 1305±18 | 49 | 1,351 | Proprietary | |
| 50 | 1304±16 | 50 | 1,833 | Proprietary | |
| 51 | 1301±20 | 51 | 1,011 | Apache 2.0 | |
| 52 | 1301±15 | 52 | 1,997 | Apache 2.0 | |
| 53 | 1300±13 | 53 | 4,797 | Proprietary | |
| 54 | 1300±17 | 54 | 1,722 | Proprietary | |
| 55 | 1294±25 | 55 | 631 | Proprietary | |
| 56 | TInkling-SmallThinking MachinesOpen | 1292±28 | 56 | 461 | Apache 2.0 |
| 57 | 1289±31 | 57 | 380 | Proprietary | |
| 58 | 1288±27 | 58 | 460 | Proprietary | |
| 59 | 1286±17 | 59 | 1,661 | Proprietary | |
| 60 | 1284±13 | 60 | 3,692 | Proprietary | |
| 61 | 1284±24 | 61 | 693 | Proprietary | |
| 62 | 1283±19 | 62 | 998 | Apache 2.0 | |
| 63 | 1278±29 | 63 | 494 | Proprietary | |
| 64 | 1278±16 | 64 | 1,989 | Proprietary | |
| 65 | 1270±17 | 65 | 1,437 | Proprietary | |
| 66 | 1270±23 | 66 | 671 | Proprietary | |
| 67 | 1270±21 | 67 | 813 | Proprietary | |
| 68 | 1268±37 | 68 | 253 | Proprietary | |
| 69 | 1267±17 | 69 | 2,052 | Proprietary | |
| 70 | 1266±44 | 70 | 169 | Proprietary | |
| 71 | 1264±20 | 71 | 1,148 | Proprietary | |
| 72 | 1257±17 | 72 | 1,650 | Proprietary | |
| 73 | 1255±17 | 73 | 1,419 | Proprietary | |
| 74 | 1250±45 | 74 | 182 | Proprietary | |
| 75 | 1249±18 | 75 | 1,675 | Proprietary | |
| 76 | 1244±38 | 76 | 287 | Modified MIT | |
| 77 | 1240±26 | 77 | 569 | Apache 2.0 | |
| 78 | 1237±16 | 78 | 2,258 | Proprietary | |
| 79 | 1235±58 | 79 | 99 | Proprietary | |
| 80 | 1234±17 | 80 | 2,135 | Proprietary | |
| 81 | 1233±21 | 81 | 1,062 | Proprietary | |
| 82 | 1233±25 | 82 | 490 | Proprietary | |
| 83 | 1232±17 | 83 | 1,739 | Proprietary | |
| 84 | 1226±17 | 84 | 1,978 | Proprietary | |
| 85 | 1219±43 | 85 | 164 | Apache 2.0 | |
| 86 | 1218±17 | 86 | 1,934 | Proprietary | |
| 87 | 1217±41 | 87 | 166 | MIT | |
| 88 | 1214±18 | 88 | 1,600 | Proprietary | |
| 89 | 1194±19 | 89 | 1,655 | Proprietary | |
| 90 | 1190±16 | 90 | 2,176 | Proprietary | |
| 91 | 1187±44 | 91 | 395 | Proprietary | |
| 92 | 1186±18 | 92 | 1,778 | Proprietary | |
| 93 | 1176±63 | 93 | 77 | Proprietary | |
| 94 | 1176±43 | 94 | 189 | Proprietary | |
| 95 | 1174±47 | 95 | 163 | Proprietary | |
| 96 | 1164±21 | 96 | 1,020 | Gemma | |
| 97 | 1163±23 | 97 | 847 | Apache 2.0 | |
| 98 | 1161±25 | 98 | 599 | Proprietary | |
| 99 | 1155±21 | 99 | 1,251 | Apache 2.0 | |
| 100 | 1145±30 | 100 | 414 | Proprietary | |
| 101 | 1141±34 | 101 | 294 | Llama 4 | |
| 102 | 1137±44 | 102 | 370 | Proprietary | |
| 103 | 1132±38 | 103 | 1,472 | Proprietary | |
| 104 | 1119±38 | 104 | 514 | Proprietary | |
| 105 | 1107±55 | 105 | 119 | Qwen | |
| 106 | 1106±36 | 106 | 278 | Llama | |
| 107 | 1105±39 | 107 | 1,564 | Proprietary | |
| 108 | 1083±51 | 108 | 156 | MRL | |
| 109 | 1072±45 | 109 | 291 | Qwen | |
| 110 | OInternVL2 26BOpenGVLabOpen | 1065±48 | 110 | 287 | MIT |
| 111 | 1045±41 | 111 | 937 | Proprietary | |
| 112 | 1033±38 | 112 | 954 | Proprietary | |
| 113 | 1030±40 | 113 | 1,168 | Proprietary | |
| 114 | 1026±62 | 114 | 98 | Proprietary | |
| 115 | 1009±52 | 115 | 186 | Proprietary | |
| 116 | 999±46 | 116 | 298 | Apache 2.0 | |
| 117 | 994±40 | 117 | 1,038 | Proprietary | |
| 118 | 974±45 | 118 | 332 | Proprietary | |
| 119 | 960±41 | 119 | 950 | Proprietary | |
| 120 | 952±43 | 120 | 393 | Llama 3.2 | |
| 121 | 951±45 | 121 | 335 | Apache 2.0 | |
| 122 | OInternVL2 4BOpenGVLabOpen | 950±55 | 122 | 177 | MIT |
| 123 | 942±41 | 123 | 915 | Proprietary | |
| 124 | 936±55 | 124 | 182 | Apache 2.0 | |
| 125 | 916±41 | 125 | 1,019 | Proprietary | |
| 126 | LLLaVA 1.6 34BOpen | 915±47 | 126 | 415 | Apache 2.0 |
| 127 | 915±49 | 127 | 266 | Llama 3.2 | |
| 128 | 890±54 | 128 | 171 | Apache 2.0 | |
Scores: LMArena leaderboard-dataset (lmarena-ai on Hugging Face, CC-BY-4.0, vision config), Chinese published Oct 19, 2026. Please credit the source when citing.
Sources & methodology
- LMLMArena leaderboard dataset (Hugging Face, CC-BY-4.0)
Vision config, published Oct 19, 2026; 167 models on the overall board.
- Scores are Bradley-Terry Arena ratings fitted from human votes between two anonymous answers to the same image prompt.
- 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.
- Fields without public data (price, context length, release date…) are not shown; blanks are –. Nothing is estimated.
- Synced daily. JSON API: /api/public/vision-leaderboard.php
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.