GPT-5 Mini vs Muse Wonder
Muse Wonder leads GPT-5 Mini on coding, 71.9 to 34.2 on the Vibe Coding Index, and GPT-5 Mini costs 10.0x less per output token ($2.00 vs $20.00 per million). Updated October 22, 2026; 38 benchmarks have a result for both.
GPT-5 Mini or Muse Wonder: which to pick
Pick Muse Wonder for coding: it scores 71.9 on the Vibe Coding Index against 34.2 for GPT-5 Mini.
Pick GPT-5 Mini for output tokens 10.0x cheaper ($2.00 vs $20.00 per million).
- Shared results
- 38
- GPT-5 Mini only
- 63
- Muse Wonder only
- 22
- 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
Muse Wonder
Muse Wonder scores 71.9 against 34.2.
2 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5 Mini has a AA Intelligence Index result, 20.6.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5 Mini has a GPQA Diamond result, 80.3%.
Directional only
Math
AIME
No call
Only GPT-5 Mini has a AIME result, 91.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Mini has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
Muse Wonder
Muse Wonder leads, 1362 against 1125.
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 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Mini
GPT-5 Mini $0.0013, Muse Wonder $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Mini has the number, $0.08.
Directional only
At a glance
- Coding index
- GPT-5 Mini 34.2 from 2 benchmarks, Muse Wonder 71.9 from 3 benchmarks.
- Widest category
- Agentic work, 59.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ProofBench: GPT-5 Mini 9.0% against Muse Wonder 84.0%, 75.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Mini $2.00 against Muse Wonder $20.00 per million output tokens, 10.0x apart.
- Context window
- GPT-5 Mini takes 400K 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-5 Mini | Bars | Muse Wonder | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 0 | 15 | ||
| All shared boards | 0 | 38 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| SWE-bench Verified | 59.8% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Multilingual | 39.7% | Not measured | Only GPT-5 Mini measured |
| LMArena WebDev | Not measured | 1652 | Only Muse Wonder measured |
| LiveCodeBench (Vals AI) | 86.6% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Verified (Vals AI) | 60.8% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 49.5% | Only Muse Wonder measured |
| Vibe Code Bench (Vals AI) | 14.2% | 83.1% | Muse Wonder |
| 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) | 83.8% | Not measured | Only GPT-5 Mini measured |
| SciCode | 39.0% | 60.3% | Muse Wonder |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench | 34.8% | Not measured | Only GPT-5 Mini measured |
| WeirdML | 52.7% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: coding | 1406 | 1522 | Muse Wonder |
| LMArena Text: software and IT | 1394 | 1515 | Muse Wonder |
| LMArena WebDev: React | Not measured | 1641 | Only Muse Wonder measured |
| LMArena WebDev: HTML | Not measured | 1694 | Only Muse Wonder measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.6 | Not measured | Only GPT-5 Mini measured |
| Epoch Capabilities Index | 145.3 | 161.8 | Muse Wonder |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| 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 | 71.1% | Not measured | Only GPT-5 Mini measured |
| Vending-Bench 2 | -$31 | $9,432 | Muse Wonder |
| Berkeley Function Calling Leaderboard (BFCL) | 55.5% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | Not measured | Only GPT-5 Mini measured |
| MysteryMechanism (Vals AI) | Not measured | 27.5% | Only Muse Wonder measured |
| MMMU Pro (Vals AI) | 78.9% | Not measured | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 82.8% | Not measured | Only GPT-5 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 21.5% | 50.1% | Muse Wonder |
| GPQA Diamond (Epoch AI run) | 75.0% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI | 54.3% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI-2 | 4.4% | Not measured | Only GPT-5 Mini measured |
| Chess puzzles | 24.0% | Not measured | Only GPT-5 Mini measured |
| Mystery game puzzles | 10.0% | Not measured | Only GPT-5 Mini measured |
| VPCT | 40.2% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1380 | 1506 | Muse Wonder |
| LMArena Text: expert | 1379 | 1513 | Muse Wonder |
| LMArena Text: hard prompts in English | 1383 | 1506 | Muse Wonder |
| LMArena Vision: diagrams | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: homework | 1210 | Not measured | Only GPT-5 Mini measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| AIME | 91.5% | Not measured | Only GPT-5 Mini measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only GPT-5 Mini measured |
| MGSM (Vals AI) | 92.6% | Not measured | Only GPT-5 Mini measured |
| AA Math Index | 90.7 | Not measured | Only GPT-5 Mini measured |
| AIME 2025 (Artificial Analysis run) | 90.7% | Not measured | Only GPT-5 Mini measured |
| OTIS Mock AIME | 86.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | 46.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5 Mini measured |
| ProofBench | 9.0% | 84.0% | Muse Wonder |
| MATH level 5 | 97.8% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: math | 1378 | 1486 | Muse Wonder |
| LMArena Text: mathematical work | 1380 | 1514 | Muse Wonder |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| MMLU Pro | 82.2% | Not measured | Only GPT-5 Mini measured |
| LegalBench (Vals AI) | 81.8% | Not measured | Only GPT-5 Mini measured |
| CaseLaw (Vals AI) | 68.5% | Not measured | Only GPT-5 Mini measured |
| CorpFin (Vals AI) | 60.2% | Not measured | Only GPT-5 Mini measured |
| TaxEval (Vals AI) | 75.2% | Not measured | Only GPT-5 Mini measured |
| MortgageTax (Vals AI) | 66.9% | Not measured | Only GPT-5 Mini measured |
| MedQA (Vals AI) | 96.1% | Not measured | Only GPT-5 Mini measured |
| MedCode (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | 83.7% | Not measured | Only GPT-5 Mini measured |
| SimpleQA Verified | 21.6% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: science | 1371 | 1506 | Muse Wonder |
| LMArena Text: medicine and healthcare | 1380 | 1512 | Muse Wonder |
| LMArena Text: legal and government | 1375 | 1505 | Muse Wonder |
| LMArena Text: business and finance | 1358 | 1483 | Muse Wonder |
| FACTS Benchmark Suite | 38.6% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-5 Mini | Muse Wonder | Leader |
|---|---|---|---|
| Design Arena: websites | 1125 | 1362 | Muse Wonder |
| Design Arena: UI components | 1103 | 1379 | Muse Wonder |
| Design Arena: game dev | 1129 | 1376 | Muse Wonder |
| Design Arena: data viz | 1131 | 1317 | Muse Wonder |
| Design Arena: 3D | 1036 | 1427 | Muse Wonder |
| Design Arena: all code categories | 1114 | 1371 | Muse Wonder |
| Design Arena: SVG | 1091 | Not measured | Only GPT-5 Mini measured |
| Design Arena: ASCII art | 1125 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
| Benchmark | GPT-5 Mini | 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 |
| SAGE (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | 80.6% | Not measured | Only GPT-5 Mini measured |
| IFBench | 75.4% | Not measured | Only GPT-5 Mini measured |
| Long context reasoning (AA-LCR) | 72.3% | 80.7% | Muse Wonder |
| DTBench | 80.5% | 95.2% | Muse Wonder |
| LMCA | 34.2% | 56.8% | Muse Wonder |
| Fiction.LiveBench | 69.4% | Not measured | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | 83.1% | Not measured | Only GPT-5 Mini measured |
| LMArena Text | 1373 | 1502 | Muse Wonder |
| LMArena Text: instruction following | 1357 | 1491 | Muse Wonder |
| LMArena Text: creative writing | 1325 | 1491 | Muse Wonder |
| LMArena Vision | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: English | 1379 | 1507 | Muse Wonder |
| LMArena Text: non-English | 1363 | 1492 | Muse Wonder |
| LMArena Text: Chinese | 1386 | 1537 | Muse Wonder |
| LMArena Text: German | 1366 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Japanese | 1341 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1308 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: French | 1386 | 1523 | Muse Wonder |
| LMArena Text: Spanish | 1354 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Russian | 1362 | 1522 | Muse Wonder |
| LMArena Text: Polish | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | 1363 | 1510 | Muse Wonder |
| LMArena Text: longer queries | 1355 | 1493 | Muse Wonder |
| LMArena Text: writing and language | 1344 | 1496 | Muse Wonder |
| LMArena Text: entertainment and media | 1340 | 1482 | Muse Wonder |
| LMArena Vision: English | 1216 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | 1214 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: reading text | 1199 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: humor | 1205 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: captioning | 1217 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | 1181 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Mini | 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-5 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5 Mini 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-5 Mini | Meta Muse Wonder |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | No public weights listed | No public weights listed |
| Released | August 7, 2025 | October 12, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $0.25 | $4.00 |
| Output $/Mtok | $2.00 | $20.00 |
| Coding index | 34.2 | 71.9 |
| Independent measurements behind it | 2 | 3 |
| Cost per solved task | $0.08 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Mini better than Muse Wonder for coding?
Pick Muse Wonder for coding: it scores 71.9 on the Vibe Coding Index against 34.2 for GPT-5 Mini. Pick GPT-5 Mini for output tokens 10.0x cheaper ($2.00 vs $20.00 per million).
Which is cheaper, GPT-5 Mini or Muse Wonder?
GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Muse Wonder costs $4.00 and $20.00. Cost per solved task is known for GPT-5 Mini only.
Which has the bigger context window, GPT-5 Mini or Muse Wonder?
Muse Wonder, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5 Mini vs Muse Wonder comparison based on?
38 benchmarks have a result for both models as of October 22, 2026. GPT-5 Mini's coding index rests on 2 independent benchmarks and Muse Wonder's on 3. Where only one model has a result, the page says so instead of naming a winner.