Muse Ember vs Qwen3.7 Max
Muse Ember leads Qwen3.7 Max on coding, 64.9 to 54.1 on the Vibe Coding Index, and Muse Ember costs 8.8x less per output token ($0.50 vs $4.425 per million). Updated November 14, 2026; 7 benchmarks have a result for both.
Muse Ember or Qwen3.7 Max: which to pick
Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 54.1 for Qwen3.7 Max.
Qwen3.7 Max is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 7
- Muse Ember only
- 8
- Qwen3.7 Max only
- 56
- Like-for-like categories
- 2 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 Ember
Muse Ember scores 64.9 against 54.1.
3 benchmarks behind each score
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Max has a Design Arena: websites result, 1267.
Directional only
General
Vals Index
No call
Only Muse Ember has a Vals Index result, 60.5%.
Directional only
Long documents
Listed context window
Muse Ember
Muse Ember takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Ember
Muse Ember $0.0003, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- Muse Ember 64.9 from 3 benchmarks, Qwen3.7 Max 54.1 from 3 benchmarks.
- Widest category
- Coding, 23.6 points apart on average over 5 shared benchmarks.
- Widest single gap
- Terminal-Bench 4.0 (Artificial Analysis run): Muse Ember 40.9% against Qwen3.7 Max 1.5%, 39.4 points apart on a 0 to 100 scale.
- Output price
- Muse Ember $0.50 against Qwen3.7 Max $4.425 per million output tokens, 8.8x apart.
- Context window
- Muse Ember takes 1.05M tokens, Qwen3.7 Max 1M.
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 | Muse Ember | Bars | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Agentic work | 2 | 0 | ||
| All shared boards | 7 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| LMArena WebDev | 1609 | 1515 | Muse Ember |
| AA Coding Index | Not measured | 66.0 | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | Not measured | 87.1% | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | Not measured | 68.8% | Only Qwen3.7 Max measured |
| Terminal-Bench 4 (Vals AI) | 39.4% | Not measured | Only Muse Ember measured |
| Vibe Code Bench (Vals AI) | 83.7% | 47.7% | Muse Ember |
| Code migration (Vals AI) | Not measured | 13.1% | Only Qwen3.7 Max measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 61.0% | Only Qwen3.7 Max measured |
| SciCode | Not measured | 49.5% | Only Qwen3.7 Max measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | 40.9% | 1.5% | Muse Ember |
| FrontierCode 2.0 | 27.2% | Not measured | Only Muse Ember measured |
| ALE-Bench | Not measured | 1189.4 | Only Qwen3.7 Max measured |
| LMArena WebDev: React | 1616 | 1512 | Muse Ember |
| LMArena WebDev: HTML | 1621 | 1514 | Muse Ember |
| GameBench 2 | Not measured | 39.3 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 154.5 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | Not measured | 1184 | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | Not measured | 1166 | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | Not measured | 1149 | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | Not measured | 1148 | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | Not measured | 1166 | Only Qwen3.7 Max measured |
| Design Arena: agents building games | Not measured | 1101 | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | Not measured | 1053 | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | Not measured | 1153 | Only Qwen3.7 Max measured |
| Design Arena: spreadsheets | Not measured | 999 | Only Qwen3.7 Max measured |
| Finance Agent (Vals AI) | Not measured | 47.8% | Only Qwen3.7 Max measured |
| Tax Agent Bench (Vals AI) | 38.2% | 15.8% | Muse Ember |
| Legal Research Bench (Vals AI) | 49.0% | 25.5% | Muse Ember |
| Harvey's Legal Agent Benchmark (Vals AI) | 25.0% | Not measured | Only Muse Ember measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.0% | Only Qwen3.7 Max measured |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| APEX-Agents | 64.3% | Not measured | Only Muse Ember measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.2% | Only Qwen3.7 Max measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 40.5% | Only Qwen3.7 Max measured |
| HLE-Diamond (Artificial Analysis run) | 25.1% | Not measured | Only Muse Ember measured |
| CritPt v2, hard subset (Artificial Analysis run) | 39.0% | Not measured | Only Muse Ember measured |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only Qwen3.7 Max measured |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | Not measured | 27.0% | Only Qwen3.7 Max measured |
| Mystery game puzzles | Not measured | 32.0% | Only Qwen3.7 Max measured |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Qwen3.7 Max measured |
| FrontierMath, tiers 1 to 3 | Not measured | 64.6% | Only Qwen3.7 Max measured |
| FrontierMath, tier 4 | Not measured | 34.1% | Only Qwen3.7 Max measured |
| ProofBench | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.3% | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | Not measured | 84.9% | Only Qwen3.7 Max measured |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | Not measured | 38.8% | Only Qwen3.7 Max measured |
| AA-Omniscience | 7.7 | Not measured | Only Muse Ember measured |
| SimpleQA Verified | Not measured | 55.8% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1267 | Only Qwen3.7 Max measured |
| Design Arena: UI components | Not measured | 1263 | Only Qwen3.7 Max measured |
| Design Arena: game dev | Not measured | 1254 | Only Qwen3.7 Max measured |
| Design Arena: data viz | Not measured | 1273 | Only Qwen3.7 Max measured |
| Design Arena: 3D | Not measured | 1245 | Only Qwen3.7 Max measured |
| Design Arena: all code categories | Not measured | 1265 | Only Qwen3.7 Max measured |
| Design Arena: SVG | Not measured | 1206 | Only Qwen3.7 Max measured |
| Design Arena: ASCII art | Not measured | 1204 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | Leader |
|---|---|---|---|
| Vals Index | 60.5% | Not measured | Only Muse Ember measured |
| MedScribe (Vals AI) | Not measured | 79.4% | Only Qwen3.7 Max measured |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Qwen3.7 Max measured |
| GDPval-AA | Not measured | 1134 | Only Qwen3.7 Max measured |
| DTBench | Not measured | 92.3% | Only Qwen3.7 Max measured |
| LMCA | Not measured | 44.0% | Only Qwen3.7 Max measured |
| EQ-Bench 4 | Not measured | 1100 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Ember | Qwen3.7 Max | 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 Ember costs less
Repository review
50K input + 3K output tokens
Muse Ember costs less
Agent loop
200K input + 10K output tokens
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 | Meta Muse Ember | Qwen3.7 Max |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | November 9, 2026 | May 21, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.10 | $1.475 |
| Output $/Mtok | $0.50 | $4.425 |
| Coding index | 64.9 | 54.1 |
| Independent measurements behind it | 3 | 3 |
| Cost per solved task | Not computable | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Ember better than Qwen3.7 Max for coding?
Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 54.1 for Qwen3.7 Max. Qwen3.7 Max is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, Muse Ember or Qwen3.7 Max?
Muse Ember costs $0.10 per million input tokens and $0.50 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, Muse Ember or Qwen3.7 Max?
Muse Ember, with 1.05M tokens against 1M.
How many benchmarks is the Muse Ember vs Qwen3.7 Max comparison based on?
7 benchmarks have a result for both models as of November 14, 2026. Muse Ember's coding index rests on 3 independent benchmarks and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.