Muse Spark 1.3
Made by Meta, released 2 Sep 2026. Epoch AI lists its access as “API access”. Appears strongest at coding and writing among the models listed here.
In short
What it does well
- Coding: Top tier (11th of 77 listed models)
- Writing: Top tier (18th of 77 listed models)
- Maths: Strong (18th of 43 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
- 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 Muse Spark 1.3 writing score (lmarena)
- Coding
- Top tierHow often people preferred its answers to coding questions. 1,509 on Arena's scale · Source for Muse Spark 1.3 coding score (lmarena)
- Maths
- StrongHow many very hard maths problems it solved. 74.4% · Source for Muse Spark 1.3 maths score (epoch)
- Knowledge
- Not enough dataNo result yet for short factual questions.
Evidence completeness: Partial evidence, 9 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 | 16th of 77 | 1,510 95% range 1,498 to 1,523 | 2,392 | Source for Expert-level prompts |
| Hard prompts Kind of request | 11th of 77 | 1,503 95% range 1,496 to 1,509 | 14,300 | Source for Hard prompts |
| Long prompts Kind of request | 15th of 77 | 1,488 95% range 1,481 to 1,495 | 9,859 | Source for Long prompts |
| Longer conversations Kind of request | 13th of 77 | 1,488 95% range 1,477 to 1,499 | 3,324 | Source for Longer conversations |
| Chinese Language | 20th of 76 | 1,526 95% range 1,512 to 1,541 | 1,744 | Source for Chinese |
| English prompts Language | 11th of 77 | 1,494 95% range 1,487 to 1,501 | 8,632 | Source for English prompts |
| French Language | 4th of 72 | 1,508 95% range 1,485 to 1,530 | 748 | Source for French |
| German Language | 5th of 55 | 1,504 95% range 1,471 to 1,536 | 328 | Source for German |
| Japanese Language | 17th of 54 | 1,472 95% range 1,440 to 1,504 | 388 | Source for Japanese |
| Korean Language | 2nd of 54 | 1,494 95% range 1,463 to 1,525 | 394 | Source for Korean |
| Non-English prompts Language | 9th of 77 | 1,482 95% range 1,476 to 1,488 | 13,491 | Source for Non-English prompts |
| Russian Language | 10th of 77 | 1,495 95% range 1,483 to 1,506 | 3,005 | Source for Russian |
| Spanish Language | 11th of 70 | 1,488 95% range 1,465 to 1,510 | 747 | Source for Spanish |
| Entertainment, sport and media Topic | 17th of 77 | 1,459 95% range 1,450 to 1,467 | 5,723 | Source for Entertainment, sport and media |
| Law and government Topic | 13th of 76 | 1,496 95% range 1,482 to 1,511 | 1,819 | Source for Law and government |
| Medicine and health Topic | 13th of 75 | 1,493 95% range 1,477 to 1,509 | 1,515 | Source for Medicine and health |
| Science Topic | 13th of 77 | 1,506 95% range 1,496 to 1,517 | 3,600 | Source for Science |
| Software and IT Topic | 10th of 77 | 1,508 95% range 1,501 to 1,516 | 8,240 | 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
- 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: rated Strong on hard maths problems. Compare it with GPT-6.1 Sol, 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
- Meta
- Release date (Epoch AI)
- 2 Sep 2026
- Access, as listed by Epoch AI
- API access
- Licence, as listed by Arena
- Proprietary
- Maker's country (Epoch AI)
- United States of America
- Last observation in our data
- 28 Oct 2026
- Data last changed
- 29 Oct 2026, 14:36 UTC
Arena lists 'Max'; Epoch's runs of this model use 'xhigh'. Epoch's SimpleQA row is for Muse Spark 1.2, a different model, and is deliberately not used.
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. Epoch AI lists access as “API access”. 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) |
1,491 Arena score 95% range 1,485 to 1,496, 22,134 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena text: overall preference score (lmarena) |
| Arena text: creative writing Arena 'text' leaderboard, category creative_writing |
1,464 Arena score 95% range 1,454 to 1,473, 4,874 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena text: creative writing score (lmarena) |
| Arena text: coding Arena 'text' leaderboard, category coding |
1,509 Arena score 95% range 1,501 to 1,518, 5,707 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena text: coding score (lmarena) |
| Arena text: maths Arena 'text' leaderboard, category math |
1,501 Arena score 95% range 1,483 to 1,518, 1,125 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena text: maths score (lmarena) |
| Arena text: following instructions Arena 'text' leaderboard, category instruction_following |
1,478 Arena score 95% range 1,470 to 1,485, 7,871 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena text: following instructions score (lmarena) |
| Arena text: business and management Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations |
1,486 Arena score 95% range 1,476 to 1,496, 3,980 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · text/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena text: business and management score (lmarena) |
| Arena WebDev: building web apps Arena 'webdev' leaderboard (Code Arena), category overall |
1,656 Arena score 95% range 1,649 to 1,664, 10,796 votes |
Top tier | effort: Max, bradley-terry rating | Muse Spark 1.3 (Max) lmarena · webdev/latest |
28 Oct 2026 | Source for Muse Spark 1.3 Arena WebDev: building web apps score (lmarena) |
| FrontierMath Tiers 1-3 (v2) FrontierMath Tiers 1-3 v2 (private set), benchmark released 2026-06-12 |
74.4% share of problems solved standard error ±2.6 points |
Strong | effort: xhigh, best score across scorers | muse-spark-1.3_xhigh epoch · frontiermath_tiers_1_3_v2.csv |
16 Sep 2026 | Source for Muse Spark 1.3 FrontierMath Tiers 1-3 (v2) score (epoch) No public run log in the data file. |
| OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025, benchmark released 2024-12-19 |
99.2% share of problems solved standard error ±0.6 points |
Top tier | effort: xhigh, best score across scorers | muse-spark-1.3_xhigh epoch · otis_mock_aime_2024_2025.csv |
17 Sep 2026 | Source for Muse Spark 1.3 OTIS Mock AIME 2024-2025 score (epoch) No public run log in the data file. |
| 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:
- 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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