Muse Wonder
Made by Meta. Epoch AI does not state how it can be accessed. Appears strongest at coding and writing among the models listed here.
In short
What it does well
- Coding: Top tier (8th of 77 listed models)
- Writing: Top tier (8th 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
- 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. 1,488 on Arena's scale · Source for Muse Wonder writing score (lmarena)
- Coding
- Top tierHow often people preferred its answers to coding questions. 1,518 on Arena's scale · Source for Muse Wonder 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 | 21st of 77 | 1,506 95% range 1,486 to 1,526 | 826 | Source for Expert-level prompts |
| Hard prompts Kind of request | 9th of 77 | 1,507 95% range 1,498 to 1,516 | 4,834 | Source for Hard prompts |
| Long prompts Kind of request | 10th of 77 | 1,495 95% range 1,484 to 1,506 | 3,397 | Source for Long prompts |
| Longer conversations Kind of request | 4th of 77 | 1,505 95% range 1,487 to 1,523 | 1,107 | Source for Longer conversations |
| Chinese Language | 14th of 76 | 1,531 95% range 1,508 to 1,554 | 647 | Source for Chinese |
| English prompts Language | 6th of 77 | 1,505 95% range 1,494 to 1,516 | 3,050 | Source for English prompts |
| French Language | 6th of 72 | 1,507 95% range 1,474 to 1,540 | 342 | Source for French |
| Non-English prompts Language | 6th of 77 | 1,490 95% range 1,481 to 1,499 | 4,690 | Source for Non-English prompts |
| Russian Language | 3rd of 77 | 1,518 95% range 1,500 to 1,536 | 1,077 | Source for Russian |
| Entertainment, sport and media Topic | 5th of 77 | 1,484 95% range 1,470 to 1,498 | 2,016 | Source for Entertainment, sport and media |
| Law and government Topic | 6th of 76 | 1,509 95% range 1,485 to 1,534 | 629 | Source for Law and government |
| Medicine and health Topic | 4th of 75 | 1,514 95% range 1,488 to 1,539 | 526 | Source for Medicine and health |
| Science Topic | 14th of 77 | 1,505 95% range 1,488 to 1,522 | 1,241 | Source for Science |
| Software and IT Topic | 8th of 77 | 1,515 95% range 1,504 to 1,527 | 2,785 | 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
- Homework and maths: no result on hard maths problems, so we cannot say. See which models the evidence does support.
- 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
- Meta
- 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) |
1,499 Arena score 95% range 1,492 to 1,506, 7,749 votes |
Top tier | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Wonder Arena text: overall preference score (lmarena) |
| Arena text: creative writing Arena 'text' leaderboard, category creative_writing |
1,488 Arena score 95% range 1,473 to 1,503, 1,736 votes |
Top tier | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Wonder Arena text: creative writing score (lmarena) |
| Arena text: coding Arena 'text' leaderboard, category coding |
1,518 Arena score 95% range 1,505 to 1,532, 1,902 votes |
Top tier | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Wonder Arena text: coding score (lmarena) |
| Arena text: maths Arena 'text' leaderboard, category math |
1,477 Arena score 95% range 1,450 to 1,505, 418 votes |
Strong | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Wonder Arena text: maths score (lmarena) |
| Arena text: following instructions Arena 'text' leaderboard, category instruction_following |
1,494 Arena score 95% range 1,482 to 1,505, 2,723 votes |
Top tier | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Wonder Arena text: following instructions score (lmarena) |
| Arena text: business and management Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations |
1,487 Arena score 95% range 1,471 to 1,504, 1,282 votes |
Top tier | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Wonder Arena text: business and management score (lmarena) |
| Arena WebDev: building web apps Arena 'webdev' leaderboard (Code Arena), category overall |
1,652 Arena score 95% range 1,641 to 1,663, 3,724 votes |
Top tier | effort: Max, bradley-terry rating | Muse Wonder (Max) lmarena · webdev/latest |
28 Oct 2026 | Source for Muse Wonder 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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