gpt-oss-120b vs Muse Wonder
gpt-oss-120b costs 40.0x less per output token than Muse Wonder ($0.50 vs $20.00 per million). Updated October 22, 2026; 36 benchmarks have a result for both.
gpt-oss-120b or Muse Wonder: which to pick
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding.
Pick gpt-oss-120b for output tokens 40.0x cheaper ($0.50 vs $20.00 per million).
- Shared results
- 36
- gpt-oss-120b only
- 45
- Muse Wonder only
- 24
- Like-for-like categories
- 8 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 gpt-oss-120b has a AA Intelligence Index result, 11.6.
Directional only
Agentic work
AA Agentic Index
No call
Only gpt-oss-120b has a AA Agentic Index result, 3.7.
Directional only
Reasoning
GPQA Diamond
No call
Only gpt-oss-120b has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-120b has a MMLU Pro result, 79.2%.
Directional only
Web design
Design Arena: websites
Muse Wonder
Muse Wonder leads, 1362 against 967.
Same board, both measured
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
gpt-oss-120b $0.0003, Muse Wonder $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- gpt-oss-120b not benchmarked, Muse Wonder 71.9 from 3 benchmarks.
- Widest category
- Agentic work, 59.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: 3D: gpt-oss-120b 901 against Muse Wonder 1427, 65.8 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.50 against Muse Wonder $20.00 per million output tokens, 40.0x apart.
- Context window
- gpt-oss-120b takes 131K tokens, Muse Wonder 1.05M.
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 | gpt-oss-120b | Bars | Muse Wonder | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 0 | 15 | ||
| All shared boards | 0 | 36 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified | 26.0% | Not measured | Only gpt-oss-120b measured |
| LMArena WebDev | Not measured | 1652 | Only Muse Wonder measured |
| AA Coding Index | 30.4 | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | 83.2% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified (Vals AI) | 33.6% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 49.5% | Only Muse Wonder measured |
| Vibe Code Bench (Vals AI) | Not measured | 83.1% | Only Muse Wonder measured |
| Code migration (Vals AI) | Not measured | 62.5% | Only Muse Wonder measured |
| IOI (Vals AI) | Not measured | 66.9% | Only Muse Wonder measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 45.6% | Only Muse Wonder measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 26.6% | Only Muse Wonder measured |
| CyberBench (Vals AI) | Not measured | 80.4% | Only Muse Wonder measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | Not measured | Only gpt-oss-120b measured |
| SciCode | 34.0% | 60.3% | Muse Wonder |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench | 18.7% | Not measured | Only gpt-oss-120b measured |
| WeirdML | 48.2% | Not measured | Only gpt-oss-120b measured |
| ALE-Bench | 575.6 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: coding | 1379 | 1522 | Muse Wonder |
| LMArena Text: software and IT | 1387 | 1515 | Muse Wonder |
| LMArena WebDev: React | Not measured | 1641 | Only Muse Wonder measured |
| LMArena WebDev: HTML | Not measured | 1694 | Only Muse Wonder measured |
| SciCode | 7.7% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | Not measured | Only gpt-oss-120b measured |
| Epoch Capabilities Index | 139.8 | 161.8 | Muse Wonder |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | Not measured | Only gpt-oss-120b measured |
| Design Arena: spreadsheets | Not measured | 1243 | Only Muse Wonder measured |
| Finance Agent (Vals AI) | Not measured | 56.6% | Only Muse Wonder measured |
| Tax Agent Bench (Vals AI) | Not measured | 36.3% | Only Muse Wonder measured |
| Legal Research Bench (Vals AI) | Not measured | 50.5% | Only Muse Wonder measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 23.8% | Only Muse Wonder measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 67.1% | Only Muse Wonder measured |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Muse Wonder measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 22.9% | Only Muse Wonder measured |
| Vals Science Index | Not measured | 39.1% | Only Muse Wonder measured |
| CUA-bench (Vals AI) | Not measured | 7.2% | Only Muse Wonder measured |
| τ²-Bench Telecom | 65.8% | Not measured | Only gpt-oss-120b measured |
| APEX-Agents | 4.4% | Not measured | Only gpt-oss-120b measured |
| METR time horizons | 56.6% | Not measured | Only gpt-oss-120b measured |
| Vending-Bench 2 | -$22 | $9,432 | Muse Wonder |
| BrowseComp-Plus | 67.0% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only gpt-oss-120b measured |
| MysteryMechanism (Vals AI) | Not measured | 27.5% | Only Muse Wonder measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | Not measured | Only gpt-oss-120b measured |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | 50.1% | Muse Wonder |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only gpt-oss-120b measured |
| SimpleBench | 22.1% | Not measured | Only gpt-oss-120b measured |
| Mystery game puzzles | 2.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: hard prompts | 1364 | 1506 | Muse Wonder |
| LMArena Text: expert | 1356 | 1513 | Muse Wonder |
| LMArena Text: hard prompts in English | 1368 | 1506 | Muse Wonder |
| Kagi LLM Benchmark | 58.6% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| AIME | 92.6% | Not measured | Only gpt-oss-120b measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only gpt-oss-120b measured |
| MGSM (Vals AI) | 92.0% | Not measured | Only gpt-oss-120b measured |
| AA Math Index | 93.4 | Not measured | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | 93.4% | Not measured | Only gpt-oss-120b measured |
| OTIS Mock AIME | 88.9% | Not measured | Only gpt-oss-120b measured |
| ProofBench | Not measured | 84.0% | Only Muse Wonder measured |
| LMArena Text: math | 1389 | 1486 | Muse Wonder |
| LMArena Text: mathematical work | 1386 | 1514 | Muse Wonder |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | Not measured | Only gpt-oss-120b measured |
| LegalBench (Vals AI) | 75.9% | Not measured | Only gpt-oss-120b measured |
| CaseLaw (Vals AI) | 48.8% | Not measured | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 58.2% | Not measured | Only gpt-oss-120b measured |
| TaxEval (Vals AI) | 71.6% | Not measured | Only gpt-oss-120b measured |
| MedQA (Vals AI) | 91.4% | Not measured | Only gpt-oss-120b measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: science | 1382 | 1506 | Muse Wonder |
| LMArena Text: medicine and healthcare | 1388 | 1512 | Muse Wonder |
| LMArena Text: legal and government | 1355 | 1505 | Muse Wonder |
| LMArena Text: business and finance | 1359 | 1483 | Muse Wonder |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| Design Arena: websites | 967 | 1362 | Muse Wonder |
| Design Arena: UI components | 924 | 1379 | Muse Wonder |
| Design Arena: game dev | 992 | 1376 | Muse Wonder |
| Design Arena: data viz | 987 | 1317 | Muse Wonder |
| Design Arena: 3D | 901 | 1427 | Muse Wonder |
| Design Arena: all code categories | 962 | 1371 | Muse Wonder |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
| Benchmark | gpt-oss-120b | Muse Wonder | Leader |
|---|---|---|---|
| Vals Index | Not measured | 64.9% | Only Muse Wonder measured |
| Public Benefits Bench (Vals AI) | Not measured | 70.2% | Only Muse Wonder measured |
| IFBench | 69.0% | Not measured | Only gpt-oss-120b measured |
| Long context reasoning (AA-LCR) | 52.0% | 80.7% | Muse Wonder |
| DTBench | 76.3% | 95.2% | Muse Wonder |
| LMCA | 22.1% | 56.8% | Muse Wonder |
| Fiction.LiveBench | 44.4% | Not measured | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | 77.1% | Not measured | Only gpt-oss-120b measured |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text | 1366 | 1502 | Muse Wonder |
| LMArena Text: instruction following | 1318 | 1491 | Muse Wonder |
| LMArena Text: creative writing | 1274 | 1491 | Muse Wonder |
| LMArena Text: English | 1375 | 1507 | Muse Wonder |
| LMArena Text: non-English | 1351 | 1492 | Muse Wonder |
| LMArena Text: Chinese | 1385 | 1537 | Muse Wonder |
| LMArena Text: German | 1353 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Japanese | 1331 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Korean | 1282 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: French | 1370 | 1523 | Muse Wonder |
| LMArena Text: Spanish | 1389 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Russian | 1343 | 1522 | Muse Wonder |
| LMArena Text: Polish | 1353 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | 1340 | 1510 | Muse Wonder |
| LMArena Text: longer queries | 1319 | 1493 | Muse Wonder |
| LMArena Text: writing and language | 1306 | 1496 | Muse Wonder |
| LMArena Text: entertainment and media | 1292 | 1482 | Muse Wonder |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | Muse Wonder | 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
gpt-oss-120b costs less
Repository review
50K input + 3K output tokens
gpt-oss-120b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-120b 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 | OpenAI gpt-oss-120b | Meta Muse Wonder |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | October 12, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.10 | $4.00 |
| Output $/Mtok | $0.50 | $20.00 |
| Coding index | Not benchmarked | 71.9 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | $0.51 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than Muse Wonder for coding?
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; gpt-oss-120b has none, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 40.0x cheaper ($0.50 vs $20.00 per million).
Which is cheaper, gpt-oss-120b or Muse Wonder?
gpt-oss-120b costs $0.10 per million input tokens and $0.50 per million output tokens; Muse Wonder costs $4.00 and $20.00. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, gpt-oss-120b or Muse Wonder?
Muse Wonder, with 1.05M tokens against 131K.
How many benchmarks is the gpt-oss-120b vs Muse Wonder comparison based on?
36 benchmarks have a result for both models as of October 22, 2026. gpt-oss-120b's coding index rests on 1 independent benchmark and Muse Wonder's on 3. Where only one model has a result, the page says so instead of naming a winner.