GPT-6.1 Sol vs Muse Spark Open
GPT-6.1 Sol leads Muse Spark Open on coding, 82.4 to 47.4 on the Vibe Coding Index, and Muse Spark Open costs 2.4x less per output token ($4.25 vs $10.00 per million). Updated October 22, 2026; 27 benchmarks have a result for both.
GPT-6.1 Sol or Muse Spark Open: which to pick
Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 47.4 for Muse Spark Open.
Pick Muse Spark Open for output tokens 2.4x cheaper ($4.25 vs $10.00 per million) and work measured by SciCode or Finance Agent (Vals AI), where it leads.
- Shared results
- 27
- GPT-6.1 Sol only
- 71
- Muse Spark Open only
- 1
- 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
GPT-6.1 Sol
GPT-6.1 Sol scores 82.4 against 47.4.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Sol has a AA Intelligence Index result, 51.8.
Directional only
Web design
Design Arena: websites
GPT-6.1 Sol
GPT-6.1 Sol leads, 1321 against 1310.
Same board, both measured
General
Vals Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 63.9% against 48.6%.
Same board, both measured
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Spark Open
GPT-6.1 Sol $0.0070, Muse Spark Open $0.0034 per turn.
List prices
At a glance
- Coding index
- GPT-6.1 Sol 82.4 from 5 benchmarks, Muse Spark Open 47.4 from 4 benchmarks.
- Widest category
- Coding, 27.4 points apart on average over 9 shared benchmarks.
- Widest single gap
- Terminal-Bench 4 (Vals AI): GPT-6.1 Sol 55.0% against Muse Spark Open 6.6%, 64.6 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Sol $10.00 against Muse Spark Open $4.25 per million output tokens, 2.4x apart.
- Context window
- GPT-6.1 Sol takes 1.05M tokens, Muse Spark Open 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-6.1 Sol | Bars | Muse Spark Open | Ties |
|---|---|---|---|---|
| Coding | 8 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 5 | 3 | 1 tie | |
| Reasoning | 2 | 0 | ||
| Web design | 3 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 22 | 4 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index81
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench coding | 96.0% | 73.6% | GPT-6.1 Sol |
| LMArena WebDev | 1753 | 1528 | GPT-6.1 Sol |
| Terminal-Bench 4 (Vals AI) | 55.0% | 6.6% | GPT-6.1 Sol |
| Vibe Code Bench (Vals AI) | 88.9% | 76.2% | GPT-6.1 Sol |
| Code migration (Vals AI) | 65.1% | 21.2% | GPT-6.1 Sol |
| ProgramBench (Vals AI) | 3.0% | Not measured | Only GPT-6.1 Sol measured |
| IOI (Vals AI) | 96.9% | Not measured | Only GPT-6.1 Sol measured |
| SWE-bench Multimodal (Vals AI) | 43.5% | Not measured | Only GPT-6.1 Sol measured |
| CyberBench (Vals AI) | 39.3% | Not measured | Only GPT-6.1 Sol measured |
| SciCode | 55.8% | 58.4% | Muse Spark Open |
| FrontierCode | 50.2% | Not measured | Only GPT-6.1 Sol measured |
| ALE-Bench | 2743.8 | 1590.1 | GPT-6.1 Sol |
| LMArena Text: coding | 1478 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: software and IT | 1476 | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev: React | 1754 | 1529 | GPT-6.1 Sol |
| LMArena WebDev: HTML | 1800 | 1495 | GPT-6.1 Sol |
| LMArena WebDev: from an image | 1702 | Not measured | Only GPT-6.1 Sol measured |
| SciCode | 9.2% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.8 | Not measured | Only GPT-6.1 Sol measured |
| Epoch Capabilities Index | 168.4 | 155.1 | GPT-6.1 Sol |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index53
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1306 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: agents building mobile apps | 1213 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: spreadsheets | 1259 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench research | 83.5% | 80.3% | GPT-6.1 Sol |
| LiveBench browser | 88.0% | 36.0% | GPT-6.1 Sol |
| LiveBench long agentic | 73.0% | 18.9% | GPT-6.1 Sol |
| SREBench (Vals AI) | 50.8% | Not measured | Only GPT-6.1 Sol measured |
| Finance Agent (Vals AI) | 52.0% | 61.3% | Muse Spark Open |
| Tax Agent Bench (Vals AI) | 21.8% | 26.3% | Muse Spark Open |
| Legal Research Bench (Vals AI) | 38.5% | 38.5% | Tie |
| Harvey's Legal Agent Benchmark (Vals AI) | 6.3% | 25.0% | Muse Spark Open |
| Excel Modeling Benchmark (Vals AI) | 70.8% | 53.7% | GPT-6.1 Sol |
| BioMysteryBench (Vals AI) | 79.6% | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench-Science (Vals AI) | 52.9% | Not measured | Only GPT-6.1 Sol measured |
| Vals Science Index | 59.6% | Not measured | Only GPT-6.1 Sol measured |
| Robo-bench (Vals AI) | 28.3% | Not measured | Only GPT-6.1 Sol measured |
| APEX-Agents | 60.0% | 33.4% | GPT-6.1 Sol |
| SpireClimb | 24.7% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.6% | 73.7% | GPT-6.1 Sol |
| MysteryMechanism (Vals AI) | 46.4% | Not measured | Only GPT-6.1 Sol measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.0% | Only Muse Spark Open measured |
| Humanity's Last Exam (Artificial Analysis run) | 52.9% | 43.9% | GPT-6.1 Sol |
| GPQA Diamond (Epoch AI run) | 95.4% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI | 98.5% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI-2 | 94.2% | Not measured | Only GPT-6.1 Sol measured |
| Chess puzzles | 68.0% | Not measured | Only GPT-6.1 Sol measured |
| Mystery game puzzles | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| EBR-bench | 54.3% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts | 1463 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: expert | 1489 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts in English | 1465 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: diagrams | 1306 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: homework | 1356 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tiers 1 to 3 | 93.7% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tier 4 | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| ProofBench | 99.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: math | 1489 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: mathematical work | 1513 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 48.8% | Not measured | Only GPT-6.1 Sol measured |
| SimpleQA Verified | 73.9% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: science | 1444 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: legal and government | 1471 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: business and finance | 1445 | Not measured | Only GPT-6.1 Sol measured |
| FACTS Benchmark Suite | 75.3% | Not measured | Only GPT-6.1 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 index30
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| Design Arena: websites | 1321 | 1310 | GPT-6.1 Sol |
| Design Arena: UI components | 1317 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: game dev | 1389 | 1282 | GPT-6.1 Sol |
| Design Arena: data viz | 1281 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: 3D | 1460 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: all code categories | 1345 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench design | 82.1% | 60.3% | GPT-6.1 Sol |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-6.1 Sol | Muse Spark Open | Leader |
|---|---|---|---|
| Vals Index | 63.9% | 48.6% | GPT-6.1 Sol |
| LiveBench data analysis | 82.7% | 60.2% | GPT-6.1 Sol |
| Public Benefits Bench (Vals AI) | 59.3% | Not measured | Only GPT-6.1 Sol measured |
| SAGE (Vals AI) | 46.5% | Not measured | Only GPT-6.1 Sol measured |
| MedScribe (Vals AI) | 86.5% | Not measured | Only GPT-6.1 Sol measured |
| Long context reasoning (AA-LCR) | 84.0% | 78.3% | GPT-6.1 Sol |
| DTBench | 96.5% | Not measured | Only GPT-6.1 Sol measured |
| LMCA | 62.8% | Not measured | Only GPT-6.1 Sol measured |
| Furniture assembly | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text | 1443 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: instruction following | 1466 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: creative writing | 1425 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision | 1288 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: English | 1450 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: non-English | 1433 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Chinese | 1487 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: French | 1460 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Spanish | 1439 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Russian | 1457 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: multi-turn | 1442 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: longer queries | 1458 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: writing and language | 1444 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: entertainment and media | 1426 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: English | 1274 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: reading text | 1289 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-6.1 Sol measured |
| 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-6.1 Sol | Muse Spark Open | 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
Muse Spark Open costs less
Repository review
50K input + 3K output tokens
Muse Spark Open costs less
Agent loop
200K input + 10K output tokens
Muse Spark Open 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-6.1 Sol | Meta Muse Spark Open |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | No public weights listed | Open weights |
| Released | September 29, 2026 | October 15, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $1.25 |
| Output $/Mtok | $10.00 | $4.25 |
| Coding index | 82.4 | 47.4 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Sol better than Muse Spark Open for coding?
Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 47.4 for Muse Spark Open. Pick Muse Spark Open for output tokens 2.4x cheaper ($4.25 vs $10.00 per million) and work measured by SciCode or Finance Agent (Vals AI), where it leads.
Which is cheaper, GPT-6.1 Sol or Muse Spark Open?
GPT-6.1 Sol costs $2.00 per million input tokens and $10.00 per million output tokens; Muse Spark Open costs $1.25 and $4.25. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6.1 Sol or Muse Spark Open?
GPT-6.1 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-6.1 Sol vs Muse Spark Open comparison based on?
27 benchmarks have a result for both models as of October 22, 2026. GPT-6.1 Sol's coding index rests on 5 independent benchmarks and Muse Spark Open's on 4. Where only one model has a result, the page says so instead of naming a winner.