Qwen3.5-Max-Preview
Made by Alibaba. Epoch AI does not state how it can be accessed. Appears strongest at writing among the models listed here.
In short
What it does well
- Writing: Top tier (19th of 77 listed models)
- Coding: Strong (36th of 77 listed models)
Where it falls short
The four main ratings show no weakness. That is not evidence it has none.
What we don't know yet
- Web-building votes: Not enough data
- Hard maths problems: Not enough data
- School-competition maths: Not enough data
- Graduate-level science questions: Not enough data
- Short factual questions: Not enough data
- Fixing real software bugs: Not enough data
- Difficult coding tasks: Not enough data
The four ratings
- Top tier
- Strong
- Middle
- Behind the leaders
- Not enough data
Ratings compare only the 77 models listed here, in quarters, best first. “Not enough data” means no result yet. It is never a low score.
- Writing
- Top tierHow often people preferred its answers to writing prompts. 1,464 on Arena's scale · Source for Qwen3.5-Max-Preview writing score (lmarena)
- Coding
- StrongHow often people preferred its answers to coding questions. 1,487 on Arena's scale · Source for Qwen3.5-Max-Preview coding score (lmarena)
- Maths
- Not enough dataNo result yet for hard maths problems.
- Knowledge
- Not enough dataNo result yet for short factual questions.
Evidence completeness: Thin evidence, 6 of 13 tests have a result.
Where it is relatively stronger or weaker
This compares each kind of request with the model's own overall position among the 77 listed models, using Arena's votes. It is about performance on different languages, kinds of request and topics, not about political or social bias.
Relatively stronger
- Medicine and health: 9th of 75 on medicine and health questions, against 27th of 77 overall. Source for Medicine and health
- Chinese: 11th of 76 on questions asked in Chinese, against 27th of 77 overall. Source for Chinese
Relatively weaker
No category stands out as clearly weaker than its overall position.
Show every category we can see
| Category | Position | Arena score | Votes | Source |
|---|---|---|---|---|
| Expert-level prompts Kind of request | 35th of 77 | 1,489 95% range 1,476 to 1,502 | 2,227 | Source for Expert-level prompts |
| Hard prompts Kind of request | 29th of 77 | 1,483 95% range 1,477 to 1,489 | 14,519 | Source for Hard prompts |
| Long prompts Kind of request | 28th of 77 | 1,476 95% range 1,469 to 1,483 | 8,947 | Source for Long prompts |
| Longer conversations Kind of request | 22nd of 77 | 1,478 95% range 1,468 to 1,488 | 3,825 | Source for Longer conversations |
| Chinese Language | 11th of 76 | 1,534 95% range 1,519 to 1,549 | 1,594 | Source for Chinese |
| English prompts Language | 27th of 77 | 1,475 95% range 1,469 to 1,482 | 10,155 | Source for English prompts |
| French Language | 28th of 72 | 1,484 95% range 1,462 to 1,507 | 749 | Source for French |
| German Language | 14th of 55 | 1,487 95% range 1,458 to 1,517 | 383 | Source for German |
| Korean Language | 21st of 54 | 1,438 95% range 1,409 to 1,467 | 411 | Source for Korean |
| Non-English prompts Language | 23rd of 77 | 1,465 95% range 1,459 to 1,471 | 12,427 | Source for Non-English prompts |
| Russian Language | 27th of 77 | 1,472 95% range 1,460 to 1,483 | 2,610 | Source for Russian |
| Spanish Language | 22nd of 70 | 1,470 95% range 1,449 to 1,491 | 807 | Source for Spanish |
| Entertainment, sport and media Topic | 19th of 77 | 1,456 95% range 1,446 to 1,465 | 4,282 | Source for Entertainment, sport and media |
| Law and government Topic | 24th of 76 | 1,484 95% range 1,469 to 1,498 | 1,743 | Source for Law and government |
| Medicine and health Topic | 9th of 75 | 1,498 95% range 1,483 to 1,513 | 1,648 | Source for Medicine and health |
| Science Topic | 17th of 77 | 1,498 95% range 1,488 to 1,507 | 3,730 | Source for Science |
| Software and IT Topic | 35th of 77 | 1,486 95% range 1,479 to 1,493 | 8,991 | Source for Software and IT |
Bias: what we can and can't see
Our sources do not measure political lean, stereotyping, flattery (agreeing with you too readily) or safety behaviour, so we cannot say how any model does on those. What we can show is above: where a model is relatively stronger or weaker across languages, kinds of request and topics. Also, people voting in Arena can favour answer style, such as length and formatting, and our numbers do not adjust for that. See what AI bias means and what these tests can tell you.
Best-supported use cases
- Coding and building things: not ranked, because there is not enough data for the main test.
- Homework and maths: not ranked, because there is not enough data for the main test.
- Research and checking facts: not ranked, because there is not enough data for the main test.
Where an alternative might be more suitable
- Coding and building things: rated Strong on coding votes. Compare it with Claude Opus 5.5, the best-supported choice for this task.
- Homework and maths: no result on hard maths problems, so we cannot say. See which models the evidence does support.
- Business emails and everyday work: rated Strong on business-task votes. Compare it with Gemini 4 Argon, the best-supported choice for this task.
- Research and checking facts: no result on short factual questions, so we cannot say. See which models the evidence does support.
What it is
- Maker
- Alibaba
- Access, as listed by Epoch AI
- Not stated
- Licence, as listed by Arena
- Proprietary
- Last observation in our data
- 28 Oct 2026
- Data last changed
- 29 Oct 2026, 14:36 UTC
We have not verified an official product page for this model, so we do not link to one.
How you can use it
Proprietary. The model's files are not published, so it is generally available only through its maker or partners the maker chooses.
How you can reach it (an app, a website, a developer API or a third-party tool) and what that costs are not covered by our benchmark data. Where we could verify prices from the maker's own pages, they are shown under Price. See models, apps and harnesses and how AI pricing works.
Price
Price not independently verified
We have not been able to check this maker's own pricing page, so we show nothing for it.
We never infer subscription prices from API prices. New to “tokens” and “per million”? See how AI pricing works.
Good to remember
- Benchmarks are samples of tasks. None proves performance in every situation.
- Arena scores come from people choosing between answers. That measures preference, not correctness.
- Ratings are relative to the 77 models listed here. A different set would change them.
- Sources test models at different settings. Each result shows the setting used, and we do not adjust it.
The evidence, for the curious
Show all 13 tests with settings and sources
| Test | Result | Rating | Setting used | Source identifier | Observed | Links |
|---|---|---|---|---|---|---|
| Arena text: overall preference Arena 'text' leaderboard (Bradley-Terry rating, no style control) |
1,470 Arena score 95% range 1,466 to 1,475, 22,582 votes |
Strong | effort: not stated, bradley-terry rating | Qwen3.5-Max-Preview lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Max-Preview Arena text: overall preference score (lmarena) |
| Arena text: creative writing Arena 'text' leaderboard, category creative_writing |
1,464 Arena score 95% range 1,453 to 1,474, 3,319 votes |
Top tier | effort: not stated, bradley-terry rating | Qwen3.5-Max-Preview lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Max-Preview Arena text: creative writing score (lmarena) |
| Arena text: coding Arena 'text' leaderboard, category coding |
1,487 Arena score 95% range 1,479 to 1,495, 6,356 votes |
Strong | effort: not stated, bradley-terry rating | Qwen3.5-Max-Preview lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Max-Preview Arena text: coding score (lmarena) |
| Arena text: maths Arena 'text' leaderboard, category math |
1,474 Arena score 95% range 1,458 to 1,490, 1,426 votes |
Strong | effort: not stated, bradley-terry rating | Qwen3.5-Max-Preview lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Max-Preview Arena text: maths score (lmarena) |
| Arena text: following instructions Arena 'text' leaderboard, category instruction_following |
1,467 Arena score 95% range 1,459 to 1,474, 7,391 votes |
Strong | effort: not stated, bradley-terry rating | Qwen3.5-Max-Preview lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Max-Preview Arena text: following instructions score (lmarena) |
| Arena text: business and management Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations |
1,463 Arena score 95% range 1,454 to 1,472, 4,508 votes |
Strong | effort: not stated, bradley-terry rating | Qwen3.5-Max-Preview lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Max-Preview Arena text: business and management score (lmarena) |
| Arena WebDev: building web apps | Not enough data | |||||
| FrontierMath Tiers 1-3 (v2) | Not enough data | |||||
| OTIS Mock AIME 2024-2025 | Not enough data | |||||
| GPQA Diamond | Not enough data | |||||
| SimpleQA Verified | Not enough data | |||||
| SWE-bench Verified (Epoch runs) | Not enough data | |||||
| FrontierCode (reported by Cognition) | Not enough data | |||||
Missing evidence
Not enough data for these tests:
- Arena WebDev: building web apps
- FrontierMath Tiers 1-3 (v2)
- OTIS Mock AIME 2024-2025
- GPQA Diamond
- SimpleQA Verified
- SWE-bench Verified (Epoch runs)
- FrontierCode (reported by Cognition)
Missing results are not low scores and do not count against the model.
Where a source gives no public run log, we cannot show the run behind the score. See data sources.
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