GPT-6 Sol vs Muse Wonder
GPT-6 Sol leads Muse Wonder on coding, 76.0 to 71.9 on the Vibe Coding Index, and GPT-6 Sol costs 2.0x less per output token ($10.00 vs $20.00 per million). Updated October 22, 2026; 54 benchmarks have a result for both.
GPT-6 Sol or Muse Wonder: which to pick
Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 71.9 for Muse Wonder.
Pick Muse Wonder for work measured by Terminal-Bench 4 (Vals AI) or Code migration (Vals AI), where it leads.
- Shared results
- 54
- GPT-6 Sol only
- 47
- Muse Wonder only
- 6
- 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
GPT-6 Sol
GPT-6 Sol scores 76.0 against 71.9.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-6 Sol has a AA Intelligence Index result, 47.6.
Directional only
Web design
Design Arena: websites
Muse Wonder
Muse Wonder leads, 1362 against 1292.
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
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Sol
GPT-6 Sol $0.0070, Muse Wonder $0.014 per turn.
List prices
At a glance
- Coding index
- GPT-6 Sol 76.0 from 5 benchmarks, Muse Wonder 71.9 from 3 benchmarks.
- Widest category
- Knowledge, 19.8 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vending-Bench 2: GPT-6 Sol $14,428 against Muse Wonder $9,432, 31.2 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Sol $10.00 against Muse Wonder $20.00 per million output tokens, 2.0x apart.
- Context window
- GPT-6 Sol takes 1.05M 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-6 Sol | Bars | Muse Wonder | Ties |
|---|---|---|---|---|
| Coding | 4 | 7 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 5 | 3 | ||
| Reasoning | 1 | 4 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 3 | 13 | ||
| All shared boards | 14 | 40 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index47
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| LiveBench coding | 93.1% | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev | 1683 | 1652 | GPT-6 Sol |
| Terminal-Bench 4 (Vals AI) | 44.4% | 49.5% | Muse Wonder |
| Vibe Code Bench (Vals AI) | 87.8% | 83.1% | GPT-6 Sol |
| Code migration (Vals AI) | 57.2% | 62.5% | Muse Wonder |
| ProgramBench (Vals AI) | 2.0% | Not measured | Only GPT-6 Sol measured |
| IOI (Vals AI) | 82.6% | 66.9% | GPT-6 Sol |
| Terminal-Bench 2.1 (Vals AI) | 83.2% | Not measured | Only GPT-6 Sol 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) | 78.0% | 80.4% | Muse Wonder |
| SciCode | 57.6% | 60.3% | Muse Wonder |
| FrontierCode | 49.3% | Not measured | Only GPT-6 Sol measured |
| ALE-Bench | 2462.0 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: coding | 1448 | 1522 | Muse Wonder |
| LMArena Text: software and IT | 1433 | 1515 | Muse Wonder |
| LMArena WebDev: React | 1685 | 1641 | GPT-6 Sol |
| LMArena WebDev: HTML | 1685 | 1694 | Muse Wonder |
| LMArena WebDev: from an image | 1660 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| AA Intelligence Index | 47.6 | Not measured | Only GPT-6 Sol measured |
| Epoch Capabilities Index | 163.7 | 161.8 | GPT-6 Sol |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index53
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1231 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | 1238 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | 1217 | Not measured | Only GPT-6 Sol measured |
| Design Arena: spreadsheets | Not measured | 1243 | Only Muse Wonder measured |
| LiveBench research | 69.3% | Not measured | Only GPT-6 Sol measured |
| LiveBench browser | 92.0% | Not measured | Only GPT-6 Sol measured |
| LiveBench long agentic | 66.9% | Not measured | Only GPT-6 Sol measured |
| SREBench (Vals AI) | 30.5% | Not measured | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | 49.0% | 56.6% | Muse Wonder |
| Tax Agent Bench (Vals AI) | 15.0% | 36.3% | Muse Wonder |
| Legal Research Bench (Vals AI) | 28.9% | 50.5% | Muse Wonder |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 23.8% | Only Muse Wonder measured |
| Excel Modeling Benchmark (Vals AI) | 71.5% | 67.1% | GPT-6 Sol |
| BioMysteryBench (Vals AI) | 74.8% | 67.0% | GPT-6 Sol |
| Terminal-Bench-Science (Vals AI) | 30.0% | 22.9% | GPT-6 Sol |
| Vals Science Index | 45.0% | 39.1% | GPT-6 Sol |
| CUA-bench (Vals AI) | Not measured | 7.2% | Only Muse Wonder measured |
| APEX-Agents | 54.3% | Not measured | Only GPT-6 Sol measured |
| SpireClimb | 7.5% | Not measured | Only GPT-6 Sol measured |
| Vending-Bench 2 | $14,428 | $9,432 | GPT-6 Sol |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | 30.2% | 27.5% | GPT-6 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | 50.1% | Muse Wonder |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI | 95.5% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI-2 | 89.6% | Not measured | Only GPT-6 Sol measured |
| Chess puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| EBR-bench | 53.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | 1422 | 1506 | Muse Wonder |
| LMArena Text: expert | 1437 | 1513 | Muse Wonder |
| LMArena Text: hard prompts in English | 1420 | 1506 | Muse Wonder |
| LMArena Vision: diagrams | 1270 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: homework | 1286 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tiers 1 to 3 | 89.8% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | 90.0% | Not measured | Only GPT-6 Sol measured |
| ProofBench | 83.0% | 84.0% | Muse Wonder |
| LMArena Text: math | 1407 | 1486 | Muse Wonder |
| LMArena Text: mathematical work | 1424 | 1514 | Muse Wonder |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 47.1% | Not measured | Only GPT-6 Sol measured |
| SimpleQA Verified | 60.7% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: science | 1389 | 1506 | Muse Wonder |
| LMArena Text: medicine and healthcare | 1366 | 1512 | Muse Wonder |
| LMArena Text: legal and government | 1396 | 1505 | Muse Wonder |
| LMArena Text: business and finance | 1380 | 1483 | Muse Wonder |
| FACTS Benchmark Suite | 72.5% | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| Design Arena: websites | 1292 | 1362 | Muse Wonder |
| Design Arena: UI components | 1290 | 1379 | Muse Wonder |
| Design Arena: game dev | 1311 | 1376 | Muse Wonder |
| Design Arena: data viz | 1269 | 1317 | Muse Wonder |
| Design Arena: 3D | 1314 | 1427 | Muse Wonder |
| Design Arena: all code categories | 1300 | 1371 | Muse Wonder |
| Design Arena: SVG | 1315 | Not measured | Only GPT-6 Sol measured |
| Design Arena: ASCII art | 1222 | Not measured | Only GPT-6 Sol measured |
| LiveBench design | 82.2% | Not measured | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index313
| Benchmark | GPT-6 Sol | Muse Wonder | Leader |
|---|---|---|---|
| Vals Index | Not measured | 64.9% | Only Muse Wonder measured |
| LiveBench data analysis | 81.2% | Not measured | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | 56.6% | 70.2% | Muse Wonder |
| SAGE (Vals AI) | 44.8% | Not measured | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | 82.0% | Not measured | Only GPT-6 Sol measured |
| Long context reasoning (AA-LCR) | 83.7% | 80.7% | GPT-6 Sol |
| DTBench | 97.3% | 95.2% | GPT-6 Sol |
| LMCA | 59.1% | 56.8% | GPT-6 Sol |
| Furniture assembly | 58.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text | 1398 | 1502 | Muse Wonder |
| LMArena Text: instruction following | 1413 | 1491 | Muse Wonder |
| LMArena Text: creative writing | 1378 | 1491 | Muse Wonder |
| LMArena Vision | 1240 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: English | 1396 | 1507 | Muse Wonder |
| LMArena Text: non-English | 1388 | 1492 | Muse Wonder |
| LMArena Text: Chinese | 1412 | 1537 | Muse Wonder |
| LMArena Text: German | 1379 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Japanese | 1377 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Korean | 1336 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: French | 1399 | 1523 | Muse Wonder |
| LMArena Text: Spanish | 1387 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Russian | 1402 | 1522 | Muse Wonder |
| LMArena Text: Polish | 1372 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: multi-turn | 1414 | 1510 | Muse Wonder |
| LMArena Text: longer queries | 1416 | 1493 | Muse Wonder |
| LMArena Text: writing and language | 1389 | 1496 | Muse Wonder |
| LMArena Text: entertainment and media | 1373 | 1482 | Muse Wonder |
| LMArena Vision: English | 1229 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: reading text | 1258 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | 1219 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Sol | 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-6 Sol costs less
Repository review
50K input + 3K output tokens
GPT-6 Sol costs less
Agent loop
200K input + 10K output tokens
GPT-6 Sol 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-6 Sol | Meta Muse Wonder |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | October 12, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $4.00 |
| Output $/Mtok | $10.00 | $20.00 |
| Coding index | 76.0 | 71.9 |
| Independent measurements behind it | 5 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Sol better than Muse Wonder for coding?
Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 71.9 for Muse Wonder. Pick Muse Wonder for work measured by Terminal-Bench 4 (Vals AI) or Code migration (Vals AI), where it leads.
Which is cheaper, GPT-6 Sol or Muse Wonder?
GPT-6 Sol costs $2.00 per million input tokens and $10.00 per million output tokens; Muse Wonder costs $4.00 and $20.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Sol or Muse Wonder?
GPT-6 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-6 Sol vs Muse Wonder comparison based on?
54 benchmarks have a result for both models as of October 22, 2026. GPT-6 Sol's coding index rests on 5 independent benchmarks and Muse Wonder's on 3. Where only one model has a result, the page says so instead of naming a winner.