Muse Wonder vs Mistral Large
Mistral Large costs 3.3x less per output token than Muse Wonder ($6.00 vs $20.00 per million). Updated October 21, 2026; 26 benchmarks have a result for both.
Muse Wonder or Mistral Large: which to pick
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding.
Pick Mistral Large for output tokens 3.3x cheaper ($6.00 vs $20.00 per million).
- Shared results
- 26
- Muse Wonder only
- 34
- Mistral Large only
- 18
- Like-for-like categories
- 6 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Muse Wonder has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mistral Large has a AA Intelligence Index result, 5.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
Web design
Design Arena: websites
No call
Only Muse Wonder has a Design Arena: websites result, 1362.
Directional only
General
Vals Index
No call
Only Muse Wonder has a Vals Index result, 64.9%.
Directional only
Long documents
Listed context window
Muse Wonder
Muse Wonder takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large
Muse Wonder $0.014, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- Muse Wonder 71.9 from 3 benchmarks, Mistral Large not benchmarked.
- Widest category
- Intelligence, 49.7 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena Text: expert: Muse Wonder 1513 against Mistral Large 1208, 50.8 points apart on a 0 to 100 scale.
- Output price
- Muse Wonder $20.00 against Mistral Large $6.00 per million output tokens, 3.3x apart.
- Context window
- Muse Wonder takes 1.05M tokens, Mistral Large 128K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Muse Wonder | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 13 | 0 | ||
| All shared boards | 26 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| LMArena WebDev | 1652 | Not measured | Only Muse Wonder measured |
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| Terminal-Bench 4 (Vals AI) | 49.5% | Not measured | Only Muse Wonder measured |
| Vibe Code Bench (Vals AI) | 83.1% | Not measured | Only Muse Wonder measured |
| Code migration (Vals AI) | 62.5% | Not measured | Only Muse Wonder measured |
| IOI (Vals AI) | 66.9% | Not measured | Only Muse Wonder measured |
| SWE-bench Multimodal (Vals AI) | 45.6% | Not measured | Only Muse Wonder measured |
| Vibe Code Bench 1-100 (Vals AI) | 26.6% | Not measured | Only Muse Wonder measured |
| CyberBench (Vals AI) | 80.4% | Not measured | Only Muse Wonder measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| SciCode | 60.3% | Not measured | Only Muse Wonder measured |
| LMArena Text: coding | 1522 | 1275 | Muse Wonder |
| LMArena Text: software and IT | 1515 | 1274 | Muse Wonder |
| LMArena WebDev: React | 1641 | Not measured | Only Muse Wonder measured |
| LMArena WebDev: HTML | 1694 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 5.8 | Only Mistral Large measured |
| Epoch Capabilities Index | 161.8 | 122.1 | Muse Wonder |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1227 | Not measured | Only Muse Wonder measured |
| Finance Agent (Vals AI) | 56.6% | Not measured | Only Muse Wonder measured |
| Tax Agent Bench (Vals AI) | 36.3% | Not measured | Only Muse Wonder measured |
| Legal Research Bench (Vals AI) | 50.5% | Not measured | Only Muse Wonder measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 23.8% | Not measured | Only Muse Wonder measured |
| Excel Modeling Benchmark (Vals AI) | 67.1% | Not measured | Only Muse Wonder measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Muse Wonder measured |
| Terminal-Bench-Science (Vals AI) | 22.9% | Not measured | Only Muse Wonder measured |
| Vals Science Index | 39.1% | Not measured | Only Muse Wonder measured |
| CUA-bench (Vals AI) | 7.2% | Not measured | Only Muse Wonder measured |
| Vending-Bench 2 | $9,432 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.7% | Only Mistral Large measured |
| MysteryMechanism (Vals AI) | 27.5% | Not measured | Only Muse Wonder measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 35.1% | Only Mistral Large measured |
| Humanity's Last Exam (Artificial Analysis run) | 50.1% | 3.5% | Muse Wonder |
| LMArena Text: hard prompts | 1506 | 1257 | Muse Wonder |
| LMArena Text: expert | 1513 | 1208 | Muse Wonder |
| LMArena Text: hard prompts in English | 1506 | 1268 | Muse Wonder |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| ProofBench | 84.0% | Not measured | Only Muse Wonder measured |
| LMArena Text: math | 1486 | 1261 | Muse Wonder |
| LMArena Text: mathematical work | 1514 | 1257 | Muse Wonder |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1506 | 1260 | Muse Wonder |
| LMArena Text: medicine and healthcare | 1512 | 1255 | Muse Wonder |
| LMArena Text: legal and government | 1505 | 1275 | Muse Wonder |
| LMArena Text: business and finance | 1483 | 1238 | Muse Wonder |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| Design Arena: websites | 1362 | Not measured | Only Muse Wonder measured |
| Design Arena: UI components | 1374 | Not measured | Only Muse Wonder measured |
| Design Arena: game dev | 1377 | Not measured | Only Muse Wonder measured |
| Design Arena: data viz | 1321 | Not measured | Only Muse Wonder measured |
| Design Arena: 3D | 1426 | Not measured | Only Muse Wonder measured |
| Design Arena: all code categories | 1371 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index130
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| Vals Index | 64.9% | Not measured | Only Muse Wonder measured |
| Public Benefits Bench (Vals AI) | 70.2% | Not measured | Only Muse Wonder measured |
| Long context reasoning (AA-LCR) | 80.7% | Not measured | Only Muse Wonder measured |
| DTBench | 95.2% | 60.8% | Muse Wonder |
| LMCA | 56.8% | Not measured | Only Muse Wonder measured |
| LMArena Text | 1502 | 1265 | Muse Wonder |
| LMArena Text: instruction following | 1491 | 1249 | Muse Wonder |
| LMArena Text: creative writing | 1491 | 1242 | Muse Wonder |
| LMArena Text: English | 1507 | 1284 | Muse Wonder |
| LMArena Text: non-English | 1492 | 1235 | Muse Wonder |
| LMArena Text: Chinese | 1537 | 1239 | Muse Wonder |
| LMArena Text: German | Not measured | 1242 | Only Mistral Large measured |
| LMArena Text: Japanese | Not measured | 1170 | Only Mistral Large measured |
| LMArena Text: Korean | Not measured | 1202 | Only Mistral Large measured |
| LMArena Text: French | 1523 | 1325 | Muse Wonder |
| LMArena Text: Spanish | Not measured | 1268 | Only Mistral Large measured |
| LMArena Text: Russian | 1522 | 1252 | Muse Wonder |
| LMArena Text: Polish | Not measured | 1157 | Only Mistral Large measured |
| LMArena Text: multi-turn | 1510 | 1260 | Muse Wonder |
| LMArena Text: longer queries | 1493 | 1261 | Muse Wonder |
| LMArena Text: writing and language | 1496 | 1261 | Muse Wonder |
| LMArena Text: entertainment and media | 1482 | 1230 | Muse Wonder |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Wonder | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Large costs less
Repository review
50K input + 3K output tokens
Mistral Large costs less
Agent loop
200K input + 10K output tokens
Mistral Large costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Meta Muse Wonder | Mistral Large |
|---|---|---|
| Maker | Meta | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | October 12, 2026 | February 26, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $4.00 | $2.00 |
| Output $/Mtok | $20.00 | $6.00 |
| Coding index | 71.9 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Wonder better than Mistral Large for coding?
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding. Pick Mistral Large for output tokens 3.3x cheaper ($6.00 vs $20.00 per million).
Which is cheaper, Muse Wonder or Mistral Large?
Muse Wonder costs $4.00 per million input tokens and $20.00 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Wonder or Mistral Large?
Muse Wonder, with 1.05M tokens against 128K.
How many benchmarks is the Muse Wonder vs Mistral Large comparison based on?
26 benchmarks have a result for both models as of October 21, 2026. Muse Wonder's coding index rests on 3 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.