Muse Wonder vs Qwen3.5-122B-A10B
Qwen3.5-122B-A10B costs 9.6x less per output token than Muse Wonder ($2.08 vs $20.00 per million). Updated October 22, 2026; 31 benchmarks have a result for both.
Muse Wonder or Qwen3.5-122B-A10B: which to pick
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Qwen3.5-122B-A10B has none, so the two cannot be ranked on coding.
Pick Qwen3.5-122B-A10B for output tokens 9.6x cheaper ($2.08 vs $20.00 per million).
- Shared results
- 31
- Muse Wonder only
- 29
- Qwen3.5-122B-A10B only
- 20
- Like-for-like categories
- 5 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 Qwen3.5-122B-A10B has a AA Intelligence Index result, 17.7.
Directional only
Web design
Design Arena: websites
No call
Only Muse Wonder has a Design Arena: websites result, 1363.
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 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-122B-A10B
Muse Wonder $0.014, Qwen3.5-122B-A10B $0.0013 per turn.
List prices
At a glance
- Coding index
- Muse Wonder 71.9 from 3 benchmarks, Qwen3.5-122B-A10B not benchmarked.
- Widest category
- Coding, 28.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: Muse Wonder 1652 against Qwen3.5-122B-A10B 1361, 41.6 points apart on a 0 to 100 scale.
- Output price
- Muse Wonder $20.00 against Qwen3.5-122B-A10B $2.08 per million output tokens, 9.6x apart.
- Context window
- Muse Wonder takes 1.05M tokens, Qwen3.5-122B-A10B 262K.
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 | Qwen3.5-122B-A10B | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 15 | 0 | ||
| All shared boards | 31 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| LMArena WebDev | 1652 | 1361 | Muse Wonder |
| AA Coding Index | Not measured | 43.3 | Only Qwen3.5-122B-A10B 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 |
| SciCode | 60.3% | 39.7% | Muse Wonder |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 31.1% | Only Qwen3.5-122B-A10B measured |
| LMArena Text: coding | 1522 | 1436 | Muse Wonder |
| LMArena Text: software and IT | 1515 | 1436 | Muse Wonder |
| LMArena WebDev: React | 1641 | 1353 | Muse Wonder |
| LMArena WebDev: HTML | 1694 | 1351 | Muse Wonder |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 17.7 | Only Qwen3.5-122B-A10B measured |
| Epoch Capabilities Index | 161.8 | Not measured | Only Muse Wonder measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1258 | 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 |
| τ²-Bench Telecom | Not measured | 93.6% | Only Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 27.5% | Not measured | Only Muse Wonder measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.7% | Only Qwen3.5-122B-A10B measured |
| Humanity's Last Exam (Artificial Analysis run) | 50.1% | 25.2% | Muse Wonder |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts | 1506 | 1421 | Muse Wonder |
| LMArena Text: expert | 1513 | 1431 | Muse Wonder |
| LMArena Text: hard prompts in English | 1506 | 1431 | Muse Wonder |
| LMArena Vision: diagrams | Not measured | 1249 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: homework | Not measured | 1261 | Only Qwen3.5-122B-A10B measured |
| 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 | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| ProofBench | 84.0% | Not measured | Only Muse Wonder measured |
| LMArena Text: math | 1486 | 1431 | Muse Wonder |
| LMArena Text: mathematical work | 1514 | 1431 | Muse Wonder |
| Neither model has a result on the other 11 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| LMArena Text: science | 1506 | 1432 | Muse Wonder |
| LMArena Text: medicine and healthcare | 1512 | 1423 | Muse Wonder |
| LMArena Text: legal and government | 1505 | 1422 | Muse Wonder |
| LMArena Text: business and finance | 1483 | 1414 | Muse Wonder |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| Design Arena: websites | 1363 | Not measured | Only Muse Wonder measured |
| Design Arena: UI components | 1380 | Not measured | Only Muse Wonder measured |
| Design Arena: game dev | 1379 | Not measured | Only Muse Wonder measured |
| Design Arena: data viz | 1312 | Not measured | Only Muse Wonder measured |
| Design Arena: 3D | 1428 | Not measured | Only Muse Wonder measured |
| Design Arena: all code categories | 1372 | 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 index150
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | Leader |
|---|---|---|---|
| Vals Index | 64.9% | Not measured | Only Muse Wonder measured |
| Public Benefits Bench (Vals AI) | 70.2% | Not measured | Only Muse Wonder measured |
| IFBench | Not measured | 75.7% | Only Qwen3.5-122B-A10B measured |
| Long context reasoning (AA-LCR) | 80.7% | 76.3% | Muse Wonder |
| DTBench | 95.2% | 84.3% | Muse Wonder |
| LMCA | 56.8% | 32.2% | Muse Wonder |
| LMArena Text | 1502 | 1417 | Muse Wonder |
| LMArena Text: instruction following | 1491 | 1399 | Muse Wonder |
| LMArena Text: creative writing | 1491 | 1368 | Muse Wonder |
| LMArena Vision | Not measured | 1244 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: English | 1507 | 1428 | Muse Wonder |
| LMArena Text: non-English | 1492 | 1401 | Muse Wonder |
| LMArena Text: Chinese | 1537 | 1463 | Muse Wonder |
| LMArena Text: German | Not measured | 1425 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Japanese | Not measured | 1367 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Korean | Not measured | 1353 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: French | 1523 | 1443 | Muse Wonder |
| LMArena Text: Spanish | Not measured | 1425 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Russian | 1522 | 1400 | Muse Wonder |
| LMArena Text: Polish | Not measured | 1398 | Only Qwen3.5-122B-A10B measured |
| LMArena Text: multi-turn | 1510 | 1416 | Muse Wonder |
| LMArena Text: longer queries | 1493 | 1410 | Muse Wonder |
| LMArena Text: writing and language | 1496 | 1387 | Muse Wonder |
| LMArena Text: entertainment and media | 1482 | 1366 | Muse Wonder |
| LMArena Vision: English | Not measured | 1249 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: Chinese | Not measured | 1301 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: reading text | Not measured | 1251 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: humor | Not measured | 1243 | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: creative writing | Not measured | 1220 | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Wonder | Qwen3.5-122B-A10B | 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
Qwen3.5-122B-A10B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-122B-A10B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 12, 2026 | February 25, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $4.00 | $0.26 |
| Output $/Mtok | $20.00 | $2.08 |
| Coding index | 71.9 | Not benchmarked |
| Independent measurements behind it | 3 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Wonder better than Qwen3.5-122B-A10B for coding?
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Qwen3.5-122B-A10B has none, so the two cannot be ranked on coding. Pick Qwen3.5-122B-A10B for output tokens 9.6x cheaper ($2.08 vs $20.00 per million).
Which is cheaper, Muse Wonder or Qwen3.5-122B-A10B?
Muse Wonder costs $4.00 per million input tokens and $20.00 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Wonder or Qwen3.5-122B-A10B?
Muse Wonder, with 1.05M tokens against 262K.
How many benchmarks is the Muse Wonder vs Qwen3.5-122B-A10B comparison based on?
31 benchmarks have a result for both models as of October 22, 2026. Muse Wonder's coding index rests on 3 independent benchmarks and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.