Qwen3.5-Flash
Made by Alibaba. Epoch AI does not state how it can be accessed. No Top tier or Strong results yet among the models listed here.
In short
What it does well
No Top tier or Strong ratings on the four main tests yet.
Where it falls short
- Coding: Behind the leaders (77th of 77 listed models)
- Writing: Behind the leaders (75th of 77 listed models)
What we don't know yet
- 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
- Behind the leadersHow often people preferred its answers to writing prompts. 1,343 on Arena's scale · Source for Qwen3.5-Flash writing score (lmarena)
- Coding
- Behind the leadersHow often people preferred its answers to coding questions. 1,412 on Arena's scale · Source for Qwen3.5-Flash 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: Partial evidence, 7 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
No category stands out as clearly stronger than its overall position.
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 | 76th of 77 | 1,407 95% range 1,399 to 1,416 | 5,847 | Source for Expert-level prompts |
| Hard prompts Kind of request | 76th of 77 | 1,403 95% range 1,399 to 1,408 | 40,121 | Source for Hard prompts |
| Long prompts Kind of request | 77th of 77 | 1,392 95% range 1,387 to 1,397 | 25,673 | Source for Long prompts |
| Longer conversations Kind of request | 77th of 77 | 1,393 95% range 1,386 to 1,399 | 10,990 | Source for Longer conversations |
| Chinese Language | 72nd of 76 | 1,446 95% range 1,436 to 1,456 | 3,673 | Source for Chinese |
| English prompts Language | 74th of 77 | 1,404 95% range 1,400 to 1,409 | 26,633 | Source for English prompts |
| French Language | 69th of 72 | 1,414 95% range 1,400 to 1,428 | 2,254 | Source for French |
| German Language | 54th of 55 | 1,391 95% range 1,372 to 1,409 | 1,072 | Source for German |
| Japanese Language | 50th of 54 | 1,368 95% range 1,345 to 1,392 | 666 | Source for Japanese |
| Korean Language | 54th of 54 | 1,343 95% range 1,324 to 1,362 | 1,075 | Source for Korean |
| Non-English prompts Language | 75th of 77 | 1,385 95% range 1,381 to 1,389 | 35,143 | Source for Non-English prompts |
| Russian Language | 76th of 77 | 1,380 95% range 1,372 to 1,387 | 7,213 | Source for Russian |
| Spanish Language | 66th of 70 | 1,399 95% range 1,385 to 1,413 | 2,054 | Source for Spanish |
| Entertainment, sport and media Topic | 77th of 77 | 1,347 95% range 1,341 to 1,354 | 12,636 | Source for Entertainment, sport and media |
| Law and government Topic | 72nd of 76 | 1,397 95% range 1,388 to 1,406 | 4,801 | Source for Law and government |
| Medicine and health Topic | 69th of 75 | 1,407 95% range 1,398 to 1,417 | 4,378 | Source for Medicine and health |
| Science Topic | 73rd of 77 | 1,415 95% range 1,409 to 1,422 | 9,836 | Source for Science |
| Software and IT Topic | 76th of 77 | 1,416 95% range 1,411 to 1,421 | 25,049 | 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
- 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
- Writing and creating content: rated Behind the leaders on writing votes. Compare it with Claude Opus 5.5, the best-supported choice for this task.
- Coding and building things: rated Behind the leaders 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 Behind the leaders 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
Epoch has rows with a similar name, but Epoch's own family name differs from Arena's, so Epoch results are not used for this model.
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) |
1,397 Arena score 95% range 1,393 to 1,401, 61,776 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena text: overall preference score (lmarena) |
| Arena text: creative writing Arena 'text' leaderboard, category creative_writing |
1,343 Arena score 95% range 1,336 to 1,350, 9,717 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena text: creative writing score (lmarena) |
| Arena text: coding Arena 'text' leaderboard, category coding |
1,412 Arena score 95% range 1,406 to 1,417, 17,729 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena text: coding score (lmarena) |
| Arena text: maths Arena 'text' leaderboard, category math |
1,408 Arena score 95% range 1,397 to 1,418, 3,388 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena text: maths score (lmarena) |
| Arena text: following instructions Arena 'text' leaderboard, category instruction_following |
1,375 Arena score 95% range 1,370 to 1,380, 20,269 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena text: following instructions score (lmarena) |
| Arena text: business and management Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations |
1,394 Arena score 95% range 1,388 to 1,401, 12,194 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · text/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena text: business and management score (lmarena) |
| Arena WebDev: building web apps Arena 'webdev' leaderboard (Code Arena), category overall |
1,244 Arena score 95% range 1,224 to 1,263, 1,321 votes |
Behind the leaders | effort: not stated, bradley-terry rating | Qwen3.5-Flash lmarena · webdev/latest |
28 Oct 2026 | Source for Qwen3.5-Flash Arena WebDev: building web apps score (lmarena) |
| 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:
- 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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