GPT-6.1 Sol vs Muse Ember
GPT-6.1 Sol leads Muse Ember on coding, 79.8 to 64.9 on the Vibe Coding Index, and Muse Ember costs 20.0x less per output token ($0.50 vs $10.00 per million). Updated November 14, 2026; 15 benchmarks have a result for both.
vs boards won of 15 shared
GPT-6.1 Sol or Muse Ember: which to pick
Pick GPT-6.1 Sol for coding: it scores 79.8 on the Vibe Coding Index against 64.9 for Muse Ember.
Pick Muse Ember for output tokens 20.0x cheaper ($0.50 vs $10.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Model AGPT-6.1 SolOpenAI79.8/1005 independent benchmarksNo cost per solved taskModel BMuse EmberMeta64.9/1003 independent benchmarksNo cost per solved task
- Shared results
- 15
- GPT-6.1 Sol only
- 114
- Muse Ember only
- 0
- 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
GPT-6.1 Sol
GPT-6.1 Sol scores 79.8 against 64.9.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Sol has a AA Intelligence Index result, 54.6.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6.1 Sol has a Design Arena: websites result, 1316.
Directional only
General
Vals Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 63.9% against 60.5%.
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 Ember
GPT-6.1 Sol $0.0070, Muse Ember $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-6.1 Sol 79.8 from 5 benchmarks, Muse Ember 64.9 from 3 benchmarks.
- Widest category
- Reasoning, 32.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- HLE-Diamond (Artificial Analysis run): GPT-6.1 Sol 58.8% against Muse Ember 25.1%, 33.7 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Sol $10.00 against Muse Ember $0.50 per million output tokens, 20.0x apart.
- Context window
- GPT-6.1 Sol takes 1.05M tokens, Muse Ember 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 Ember | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Agentic work | 0 | 4 | ||
| Reasoning | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 11 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| LiveBench coding | 82.1% | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev | 1743 | 1609 | GPT-6.1 Sol |
| Terminal-Bench 4 (Vals AI) | 55.0% | 39.4% | GPT-6.1 Sol |
| Vibe Code Bench (Vals AI) | 88.9% | 83.7% | GPT-6.1 Sol |
| Code migration (Vals AI) | 65.1% | Not measured | Only GPT-6.1 Sol measured |
| 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% | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | 56.1% | 40.9% | GPT-6.1 Sol |
| FrontierCode 2.0 | 40.6% | 27.2% | GPT-6.1 Sol |
| FrontierCode | 50.2% | Not measured | Only GPT-6.1 Sol measured |
| MirrorCode | 61.1% | Not measured | Only GPT-6.1 Sol measured |
| ALE-Bench | 2743.8 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: coding | 1486 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: software and IT | 1478 | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev: React | 1747 | 1616 | GPT-6.1 Sol |
| LMArena WebDev: HTML | 1794 | 1621 | GPT-6.1 Sol |
| LMArena WebDev: from an image | 1696 | Not measured | Only GPT-6.1 Sol measured |
| SciCode | 9.2% | Not measured | Only GPT-6.1 Sol measured |
| SWE-Bench Pro V2 | 96.1% | Not measured | Only GPT-6.1 Sol measured |
| GameBench 2 | 92.0 | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench 4.0 | 58.2% | Not measured | Only GPT-6.1 Sol measured |
| 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 | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| AA Intelligence Index | 54.6 | Not measured | Only GPT-6.1 Sol measured |
| Epoch Capabilities Index | 168.5 | Not measured | Only GPT-6.1 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1277 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: agents building mobile apps | 1229 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: agents building Android apps | 1190 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: agents building games | 1195 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: HTML slides | 1485 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: PowerPoint slides | 1304 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: spreadsheets | 1378 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench research | 90.0% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench browser | 93.3% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench long agentic | 65.6% | Not measured | Only GPT-6.1 Sol measured |
| SREBench (Vals AI) | 50.8% | Not measured | Only GPT-6.1 Sol measured |
| Finance Agent (Vals AI) | 52.0% | Not measured | Only GPT-6.1 Sol measured |
| Tax Agent Bench (Vals AI) | 21.8% | 38.2% | Muse Ember |
| Legal Research Bench (Vals AI) | 38.5% | 49.0% | Muse Ember |
| Harvey's Legal Agent Benchmark (Vals AI) | 6.3% | 25.0% | Muse Ember |
| Excel Modeling Benchmark (Vals AI) | 70.8% | Not measured | Only GPT-6.1 Sol measured |
| 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% | 64.3% | Muse Ember |
| PostTrainBench | 38.8% | Not measured | Only GPT-6.1 Sol measured |
| SpireClimb | 23.8% | Not measured | Only GPT-6.1 Sol measured |
| Vending-Bench 2 | $12,861 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Search | 1230 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.6% | Not measured | Only GPT-6.1 Sol measured |
| MysteryMechanism (Vals AI) | 46.4% | Not measured | Only GPT-6.1 Sol measured |
| Humanity's Last Exam (Artificial Analysis run) | 52.9% | Not measured | Only GPT-6.1 Sol measured |
| HLE-Diamond (Artificial Analysis run) | 58.8% | 25.1% | GPT-6.1 Sol |
| CritPt v2, hard subset (Artificial Analysis run) | 69.5% | 39.0% | 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 |
| SimpleBench | 82.9% | 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 | 1466 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: expert | 1498 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts in English | 1472 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: diagrams | 1312 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: homework | 1353 | Not measured | Only GPT-6.1 Sol measured |
| GoBench | 2378 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-6.1 Sol | Muse Ember | 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 | 1475 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: mathematical work | 1498 | Not measured | Only GPT-6.1 Sol measured |
| MathArena | 80.6% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 48.8% | Not measured | Only GPT-6.1 Sol measured |
| AA-Omniscience | 42.4 | 7.7 | GPT-6.1 Sol |
| SimpleQA Verified | 73.9% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: science | 1457 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: medicine and healthcare | 1429 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: legal and government | 1472 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: business and finance | 1441 | Not measured | Only GPT-6.1 Sol measured |
| FACTS Benchmark Suite | 76.8% | Not measured | Only GPT-6.1 Sol measured |
| PRBench Finance | 46.2% | Not measured | Only GPT-6.1 Sol measured |
| PRBench Legal | 47.9% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| Design Arena: websites | 1316 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: UI components | 1353 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: game dev | 1407 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: data viz | 1276 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: 3D | 1426 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: all code categories | 1361 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: SVG | 1343 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench design | 79.6% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Sol | Muse Ember | Leader |
|---|---|---|---|
| Vals Index | 63.9% | 60.5% | GPT-6.1 Sol |
| LiveBench data analysis | 82.7% | Not measured | Only GPT-6.1 Sol measured |
| Public Benefits Bench (Vals AI) | 59.3% | Not measured | Only GPT-6.1 Sol measured |
| SAGE (Vals AI) | 90.5% | 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% | Not measured | Only GPT-6.1 Sol measured |
| GDPval-AA | 1607 | Not measured | Only GPT-6.1 Sol measured |
| 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 | 1445 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: instruction following | 1463 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: creative writing | 1420 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision | 1286 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: English | 1451 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: non-English | 1435 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Chinese | 1501 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: German | 1449 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Japanese | 1427 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Korean | 1442 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: French | 1449 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Spanish | 1439 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Russian | 1452 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Polish | 1446 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: multi-turn | 1449 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: longer queries | 1459 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: writing and language | 1440 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: entertainment and media | 1421 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: English | 1280 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: Chinese | 1340 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: reading text | 1291 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: humor | 1272 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: creative writing | 1292 | Not measured | Only GPT-6.1 Sol measured |
| MultiChallenge | 82.0% | Not measured | Only GPT-6.1 Sol measured |
| EQ-Bench 4 | 1272 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Sol | Muse Ember | 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-6.1 Sol$0.0070Fits in one request
Muse Ember$0.0003Fits in one request
Muse Ember costs less
Repository review
50K input + 3K output tokens
GPT-6.1 Sol$0.130Fits in one request
Muse Ember$0.0065Fits in one request
Muse Ember costs less
Agent loop
200K input + 10K output tokens
GPT-6.1 Sol$0.500Fits in one request
Muse Ember$0.025Fits in one request
Muse Ember 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 Ember |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | No public weights listed | No public weights listed |
| Released | September 29, 2026 | November 9, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $0.10 |
| Output $/Mtok | $10.00 | $0.50 |
| Coding index | 79.8 | 64.9 |
| Independent measurements behind it | 5 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Sol better than Muse Ember for coding?
Pick GPT-6.1 Sol for coding: it scores 79.8 on the Vibe Coding Index against 64.9 for Muse Ember. Pick Muse Ember for output tokens 20.0x cheaper ($0.50 vs $10.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Which is cheaper, GPT-6.1 Sol or Muse Ember?
GPT-6.1 Sol costs $2.00 per million input tokens and $10.00 per million output tokens; Muse Ember costs $0.10 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6.1 Sol or Muse Ember?
GPT-6.1 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-6.1 Sol vs Muse Ember comparison based on?
15 benchmarks have a result for both models as of November 14, 2026. GPT-6.1 Sol's coding index rests on 5 independent benchmarks and Muse Ember's on 3. Where only one model has a result, the page says so instead of naming a winner.