Muse Wonder vs Qwen2.5 Coder 32B Instruct
Qwen2.5 Coder 32B Instruct costs 20.0x less per output token than Muse Wonder ($1.00 vs $20.00 per million). Updated October 22, 2026; 24 benchmarks have a result for both.
Muse Wonder or Qwen2.5 Coder 32B Instruct: which to pick
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Qwen2.5 Coder 32B Instruct has none, so the two cannot be ranked on coding.
Pick Qwen2.5 Coder 32B Instruct for output tokens 20.0x cheaper ($1.00 vs $20.00 per million).
- Shared results
- 24
- Muse Wonder only
- 36
- Qwen2.5 Coder 32B Instruct only
- 11
- 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 Qwen2.5 Coder 32B Instruct has a AA Intelligence Index result, 6.7.
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 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 Coder 32B Instruct
Muse Wonder $0.014, Qwen2.5 Coder 32B Instruct $0.0012 per turn.
List prices
At a glance
- Coding index
- Muse Wonder 71.9 from 3 benchmarks, Qwen2.5 Coder 32B Instruct not benchmarked.
- Widest category
- Intelligence, 53.0 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena Text: entertainment and media: Muse Wonder 1482 against Qwen2.5 Coder 32B Instruct 1150, 55.2 points apart on a 0 to 100 scale.
- Output price
- Muse Wonder $20.00 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 20.0x apart.
- Context window
- Muse Wonder takes 1.05M tokens, Qwen2.5 Coder 32B Instruct 33K.
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 | Qwen2.5 Coder 32B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 11 | 0 | ||
| All shared boards | 24 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 16.4% | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | Not measured | 47.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena WebDev | 1652 | Not measured | Only Muse Wonder 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 | 29.5% | Only Qwen2.5 Coder 32B Instruct measured |
| SciCode | 60.3% | Not measured | Only Muse Wonder measured |
| LMArena Text: coding | 1522 | 1276 | Muse Wonder |
| LMArena Text: software and IT | 1515 | 1261 | 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 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 6.7 | Only Qwen2.5 Coder 32B Instruct measured |
| Epoch Capabilities Index | 161.8 | 119.5 | Muse Wonder |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1243 | 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 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 27.5% | Not measured | Only Muse Wonder measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 41.7% | Only Qwen2.5 Coder 32B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 50.1% | 3.5% | Muse Wonder |
| LMArena Text: hard prompts | 1506 | 1251 | Muse Wonder |
| LMArena Text: expert | 1513 | 1221 | Muse Wonder |
| LMArena Text: hard prompts in English | 1506 | 1269 | Muse Wonder |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| ProofBench | 84.0% | Not measured | Only Muse Wonder measured |
| GSM8K | Not measured | 93.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1486 | 1251 | Muse Wonder |
| LMArena Text: mathematical work | 1514 | 1243 | Muse Wonder |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 63.5% | Only Qwen2.5 Coder 32B Instruct measured |
| MMLU | Not measured | 79.1% | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 70.5% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1506 | 1221 | Muse Wonder |
| LMArena Text: medicine and healthcare | 1512 | 1187 | Muse Wonder |
| LMArena Text: legal and government | 1505 | 1257 | Muse Wonder |
| LMArena Text: business and finance | 1483 | 1224 | Muse Wonder |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1362 | Not measured | Only Muse Wonder measured |
| Design Arena: UI components | 1379 | Not measured | Only Muse Wonder measured |
| Design Arena: game dev | 1376 | Not measured | Only Muse Wonder measured |
| Design Arena: data viz | 1317 | Not measured | Only Muse Wonder measured |
| Design Arena: 3D | 1427 | 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 index110
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | 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% | Not measured | Only Muse Wonder measured |
| LMCA | 56.8% | Not measured | Only Muse Wonder measured |
| HellaSwag | Not measured | 83.0% | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | Not measured | 80.8% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1502 | 1230 | Muse Wonder |
| LMArena Text: instruction following | 1491 | 1223 | Muse Wonder |
| LMArena Text: creative writing | 1491 | 1174 | Muse Wonder |
| LMArena Text: English | 1507 | 1248 | Muse Wonder |
| LMArena Text: non-English | 1492 | 1205 | Muse Wonder |
| LMArena Text: Chinese | 1537 | 1222 | Muse Wonder |
| LMArena Text: French | 1523 | Not measured | Only Muse Wonder measured |
| LMArena Text: Russian | 1522 | 1228 | Muse Wonder |
| LMArena Text: multi-turn | 1510 | 1222 | Muse Wonder |
| LMArena Text: longer queries | 1493 | 1251 | Muse Wonder |
| LMArena Text: writing and language | 1496 | 1191 | Muse Wonder |
| LMArena Text: entertainment and media | 1482 | 1150 | Muse Wonder |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Wonder | Qwen2.5 Coder 32B Instruct | 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
Qwen2.5 Coder 32B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 Coder 32B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 Coder 32B Instruct 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 | Qwen2.5 Coder 32B Instruct |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 12, 2026 | November 11, 2024 |
| Context window | 1.05M | 33K |
| Input $/Mtok | $4.00 | $0.66 |
| Output $/Mtok | $20.00 | $1.00 |
| 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 Qwen2.5 Coder 32B Instruct for coding?
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Qwen2.5 Coder 32B Instruct has none, so the two cannot be ranked on coding. Pick Qwen2.5 Coder 32B Instruct for output tokens 20.0x cheaper ($1.00 vs $20.00 per million).
Which is cheaper, Muse Wonder or Qwen2.5 Coder 32B Instruct?
Muse Wonder costs $4.00 per million input tokens and $20.00 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Wonder or Qwen2.5 Coder 32B Instruct?
Muse Wonder, with 1.05M tokens against 33K.
How many benchmarks is the Muse Wonder vs Qwen2.5 Coder 32B Instruct comparison based on?
24 benchmarks have a result for both models as of October 22, 2026. Muse Wonder's coding index rests on 3 independent benchmarks and Qwen2.5 Coder 32B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.