DeepSeek-V4.1-Flash-20260910
Made by DeepSeek. Epoch AI does not state how it can be accessed. Appears strongest at coding among the models listed here.
In short
What it does well
- Coding: Top tier (18th of 77 listed models)
Where it falls short
- Writing: Middle (43rd 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
- MiddleHow often people preferred its answers to writing prompts. 1,437 on Arena's scale · Source for DeepSeek-V4.1-Flash-20260910 writing score (lmarena)
- Coding
- Top tierHow often people preferred its answers to coding questions. 1,501 on Arena's scale · Source for DeepSeek-V4.1-Flash-20260910 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
- Law and government: 57th of 76 on law and government questions, against 32nd of 77 overall. Source for Law and government
- French: 45th of 72 on questions asked in French, against 32nd of 77 overall. Source for French
Show every category we can see
| Category | Position | Arena score | Votes | Source |
|---|---|---|---|---|
| Expert-level prompts Kind of request | 23rd of 77 | 1,502 95% range 1,487 to 1,517 | 1,511 | Source for Expert-level prompts |
| Hard prompts Kind of request | 28th of 77 | 1,483 95% range 1,476 to 1,490 | 8,749 | Source for Hard prompts |
| Long prompts Kind of request | 30th of 77 | 1,474 95% range 1,465 to 1,482 | 5,880 | Source for Long prompts |
| Longer conversations Kind of request | 39th of 77 | 1,460 95% range 1,447 to 1,474 | 1,989 | Source for Longer conversations |
| Chinese Language | 41st of 76 | 1,502 95% range 1,483 to 1,520 | 1,032 | Source for Chinese |
| English prompts Language | 29th of 77 | 1,475 95% range 1,466 to 1,484 | 5,051 | Source for English prompts |
| French Language | 45th of 72 | 1,467 95% range 1,441 to 1,494 | 538 | Source for French |
| Non-English prompts Language | 35th of 77 | 1,450 95% range 1,443 to 1,457 | 8,602 | Source for Non-English prompts |
| Russian Language | 30th of 77 | 1,467 95% range 1,453 to 1,481 | 1,938 | Source for Russian |
| Spanish Language | 36th of 70 | 1,458 95% range 1,432 to 1,484 | 476 | Source for Spanish |
| Entertainment, sport and media Topic | 28th of 77 | 1,445 95% range 1,434 to 1,456 | 3,343 | Source for Entertainment, sport and media |
| Law and government Topic | 57th of 76 | 1,446 95% range 1,428 to 1,464 | 1,140 | Source for Law and government |
| Medicine and health Topic | 17th of 75 | 1,486 95% range 1,466 to 1,506 | 925 | Source for Medicine and health |
| Science Topic | 37th of 77 | 1,471 95% range 1,458 to 1,484 | 2,239 | Source for Science |
| Software and IT Topic | 19th of 77 | 1,496 95% range 1,487 to 1,504 | 5,363 | 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 Middle on writing 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
- DeepSeek
- Access, as listed by Epoch AI
- Not stated
- Licence, as listed by Arena
- MIT
- 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
Open weights. Arena lists its licence as MIT. In plain terms, the model's files are published under a licence that lets others run it, so it can be offered by more than one company, sometimes at lower cost. That does not guarantee that any particular app is free. Open licences differ, and some restrict commercial use, so check the licence terms before building a business on it.
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
See DeepSeek API models and pricing (checked 29 Oct 2026). Page opened and read. It gives developer (API) prices per 1M tokens, shown on model pages. The chat app (chat.deepseek.com) goes straight to a sign-in page and we did not sign in, so we make no statement about whether it is free.
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) |
1,465 Arena score 95% range 1,458 to 1,471, 13,657 votes |
Strong | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · text/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 Arena text: overall preference score (lmarena) |
| Arena text: creative writing Arena 'text' leaderboard, category creative_writing |
1,437 Arena score 95% range 1,425 to 1,449, 2,763 votes |
Middle | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · text/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 Arena text: creative writing score (lmarena) |
| Arena text: coding Arena 'text' leaderboard, category coding |
1,501 Arena score 95% range 1,491 to 1,511, 3,745 votes |
Top tier | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · text/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 Arena text: coding score (lmarena) |
| Arena text: maths Arena 'text' leaderboard, category math |
1,481 Arena score 95% range 1,460 to 1,503, 722 votes |
Strong | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · text/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 Arena text: maths score (lmarena) |
| Arena text: following instructions Arena 'text' leaderboard, category instruction_following |
1,474 Arena score 95% range 1,465 to 1,483, 4,775 votes |
Strong | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · text/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 Arena text: following instructions score (lmarena) |
| Arena text: business and management Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations |
1,462 Arena score 95% range 1,450 to 1,474, 2,402 votes |
Strong | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · text/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 Arena text: business and management score (lmarena) |
| Arena WebDev: building web apps Arena 'webdev' leaderboard (Code Arena), category overall |
1,619 Arena score 95% range 1,608 to 1,630, 3,510 votes |
Strong | effort: Max, bradley-terry rating | DeepSeek-V4.1-Flash-20260910 (Max) lmarena · webdev/latest |
28 Oct 2026 | Source for DeepSeek-V4.1-Flash-20260910 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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