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Hunyuan-Vision-1.5-Thinking
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Hunyuan-Vision-1.5-Thinking is a closed-weights language model from Tencent, released September 2025.
Catalogue identity notes
Arena entry 'hunyuan-vision-1.5-thinking' (text, vision). Released 2025-09: date in the API snapshot id hunyuan-t1-vision-20250916. Tencent's Hunyuan-Vision-1.5 GitHub README points to LMArena's 'hunyuan-vision-1.5-thinking' and uses API model hunyuan-t1-vision-20250916; TokenHub maps HY-Vision-1.5-Thinking to that id. Weights not released as of 2026-09-28.
$ how it compares
The LLMs ranked either side of Hunyuan-Vision-1.5-Thinking, out of 1132 with a score, then more from Tencent.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 226 | Hunyuan-TurboS (20250416) | 63±3 | comparison only | ||
| 227 |  Granite 4.2 30B | 63±1 | api $0.28/M +local | ||
| 228 | Hunyuan-Vision-1.5-Thinking | 63±3 | api price unknown | ||
| 229 |  Sonar Pro | 63±5 | comparison only | ||
| 230 |  o1-preview | 63±1 | comparison only | ||
| more from Tencent | |||||
| 16 |  Hy4 preview (770B-A49B) | 79±1 | api $1.25/M +local | ||
| 57 | Hunyuan Hy3 (295B-A21B) | 74±1 | api $0.23/M +local | ||
| 139 | Hy3 preview (295B-A21B) | 68±1 | local | ||
$ what it's good at
chat & writing▁▁▁▄▆▅▆█▆▆▆▂ #116 of 466 * · 57% of its score · 1 test
Beats LongCat 2.0 (1.6T-A48B), Step 3.5 Flash (196B-A11B), GPT-5 mini here, though they rank higher overall. Trails Nemotron-Cascade-8B, Gemini 2.5 Flash, Mistral Large 3 (675B-A41B) here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LMArena (text) | 1394.9 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 238/379 | 57% |
vision & documents▁▁▃▂▁▃▄▃▆▇█▄ #93 of 150 * · 40% of its score · 1 test
Beats DeepSeek V4 Flash Vision (Exp) here, though they rank higher overall. Trails GPT-4o (2024-11-20), Mistral Small 4 (119B-A6.5B), Qwen3-VL 30B-A3B Thinking here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Arena vision (style controlled) | 1155.6 ✎ | ▁▁▂▂▂▂▄▅▅▆██ beats 51/145 | 40% |
$ where to run it
Through an API
api · Tencent Cloud TokenHub · price unknown · 40k context · cloud.tencent.com ↗
$ how the score was worked out · LMArena leaderboard dataset 97%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 LMArena leaderboard dataset | 2 | 97% |
| prior · pull toward the middle | 3% | |
| weighted average | = 63.0 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json