Muse Ember vs Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads Muse Ember on coding, 67.3 to 64.9 on the Vibe Coding Index, and Muse Ember costs 12.0x less per output token ($0.50 vs $6.00 per million). Updated November 14, 2026; 15 benchmarks have a result for both.
vs boards won of 15 shared
Muse Ember or Qwen3.8 Max (0902): which to pick
Pick Qwen3.8 Max (0902) for coding: it scores 67.3 on the Vibe Coding Index against 64.9 for Muse Ember.
Pick Muse Ember for output tokens 12.0x cheaper ($0.50 vs $6.00 per million) and a larger context window (1.05M against 1M tokens).
Model AMuse EmberMeta64.9/1003 independent benchmarksNo cost per solved taskModel BQwen3.8 Max (0902)Qwen67.3/1005 independent benchmarks$1.32 per solved task
- Shared results
- 15
- Muse Ember only
- 0
- Qwen3.8 Max (0902) only
- 113
- 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
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) scores 67.3 against 64.9.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Qwen3.8 Max (0902) has a AA Intelligence Index result, 33.7.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.8 Max (0902) has a AA Agentic Index result, 56.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.8 Max (0902) has a GPQA Diamond result, 93.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 Max (0902) has a MMLU Pro result, 88.6%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.8 Max (0902) has a Design Arena: websites result, 1269.
Directional only
General
Vals Index
Muse Ember
Muse Ember leads, 60.5% against 59.1%.
Same board, both measured
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, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 Max (0902) has the number, $1.32.
Directional only
At a glance
- Coding index
- Muse Ember 64.9 from 3 benchmarks, Qwen3.8 Max (0902) 67.3 from 5 benchmarks.
- Widest category
- Agentic work, 5.9 points apart on average over 4 shared benchmarks.
- Widest single gap
- Tax Agent Bench (Vals AI): Muse Ember 38.2% against Qwen3.8 Max (0902) 49.7%, 11.4 points apart on a 0 to 100 scale.
- Output price
- Muse Ember $0.50 against Qwen3.8 Max (0902) $6.00 per million output tokens, 12.0x apart.
- Context window
- Muse Ember takes 1.05M tokens, Qwen3.8 Max (0902) 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 | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 4 | 3 | ||
| Agentic work | 3 | 1 | ||
| Reasoning | 2 | 0 | ||
| Knowledge | 0 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 10 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index43
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.9% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | 1609 | 1676 | Qwen3.8 Max (0902) |
| AA Coding Index | Not measured | 76.2 | Only Qwen3.8 Max (0902) measured |
| LiveCodeBench (Vals AI) | Not measured | 87.8% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Verified (Vals AI) | Not measured | 85.6% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 4 (Vals AI) | 39.4% | 38.9% | Muse Ember |
| Vibe Code Bench (Vals AI) | 83.7% | 77.1% | Muse Ember |
| Code migration (Vals AI) | Not measured | 24.0% | Only Qwen3.8 Max (0902) measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 Max (0902) measured |
| IOI (Vals AI) | Not measured | 68.9% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.4% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 24.8% | Only Qwen3.8 Max (0902) measured |
| SkillsBench (Vals AI) | Not measured | 42.0% | Only Qwen3.8 Max (0902) measured |
| CyberBench (Vals AI) | Not measured | 28.6% | Only Qwen3.8 Max (0902) measured |
| SciCode | Not measured | 53.2% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | 40.9% | 38.9% | Muse Ember |
| FrontierCode 2.0 | 27.2% | 23.4% | Muse Ember |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| MirrorCode | Not measured | 52.2% | Only Qwen3.8 Max (0902) measured |
| ALE-Bench | Not measured | 1679.1 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: coding | Not measured | 1502 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: software and IT | Not measured | 1500 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: React | 1616 | 1698 | Qwen3.8 Max (0902) |
| LMArena WebDev: HTML | 1621 | 1654 | Qwen3.8 Max (0902) |
| LMArena WebDev: from an image | Not measured | 1638 | Only Qwen3.8 Max (0902) measured |
| GameBench 2 | Not measured | 69.6 | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 4.0 | Not measured | 27.0% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 33.7 | Only Qwen3.8 Max (0902) measured |
| Epoch Capabilities Index | Not measured | 157.6 | Only Qwen3.8 Max (0902) measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 56.0 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building web apps | Not measured | 1278 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building full-stack apps | Not measured | 1279 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building mobile apps | Not measured | 1223 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Android apps | Not measured | 1196 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Godot games | Not measured | 1215 | Only Qwen3.8 Max (0902) measured |
| Design Arena: PowerPoint slides | Not measured | 1252 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 1011 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | Not measured | 72.8% | Only Qwen3.8 Max (0902) measured |
| LiveBench browser | Not measured | 49.4% | Only Qwen3.8 Max (0902) measured |
| LiveBench long agentic | Not measured | 26.6% | Only Qwen3.8 Max (0902) measured |
| Finance Agent (Vals AI) | Not measured | 57.9% | Only Qwen3.8 Max (0902) measured |
| Tax Agent Bench (Vals AI) | 38.2% | 49.7% | Qwen3.8 Max (0902) |
| Legal Research Bench (Vals AI) | 49.0% | 47.6% | Muse Ember |
| Harvey's Legal Agent Benchmark (Vals AI) | 25.0% | 15.4% | Muse Ember |
| Excel Modeling Benchmark (Vals AI) | Not measured | 72.0% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| APEX-Agents | 64.3% | 63.3% | Muse Ember |
| LMArena Search | Not measured | 1260 | Only Qwen3.8 Max (0902) measured |
| τ³-Banking | Not measured | 55.2% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.7% | Only Qwen3.8 Max (0902) measured |
| LiveBench reasoning | Not measured | 88.2% | Only Qwen3.8 Max (0902) measured |
| MysteryMechanism (Vals AI) | Not measured | 23.9% | Only Qwen3.8 Max (0902) measured |
| MMMU Pro (Vals AI) | Not measured | 88.0% | Only Qwen3.8 Max (0902) measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.8% | Only Qwen3.8 Max (0902) measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 43.1% | Only Qwen3.8 Max (0902) measured |
| HLE-Diamond (Artificial Analysis run) | 25.1% | 24.0% | Muse Ember |
| CritPt v2, hard subset (Artificial Analysis run) | 39.0% | 29.5% | Muse Ember |
| GPQA Diamond (Epoch AI run) | Not measured | 92.7% | Only Qwen3.8 Max (0902) measured |
| Chess puzzles | Not measured | 46.0% | Only Qwen3.8 Max (0902) measured |
| Mystery game puzzles | Not measured | 38.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts | Not measured | 1499 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: expert | Not measured | 1510 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts in English | Not measured | 1505 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: diagrams | Not measured | 1321 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: homework | Not measured | 1335 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 100.0% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tiers 1 to 3 | Not measured | 74.7% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Qwen3.8 Max (0902) measured |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: math | Not measured | 1509 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: mathematical work | Not measured | 1497 | Only Qwen3.8 Max (0902) measured |
| MathArena | Not measured | 47.1% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.6% | Only Qwen3.8 Max (0902) measured |
| LegalBench (Vals AI) | Not measured | 83.6% | Only Qwen3.8 Max (0902) measured |
| CorpFin (Vals AI) | Not measured | 65.8% | Only Qwen3.8 Max (0902) measured |
| TaxEval (Vals AI) | Not measured | 75.5% | Only Qwen3.8 Max (0902) measured |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Qwen3.8 Max (0902) measured |
| MedCode (Vals AI) | Not measured | 40.7% | Only Qwen3.8 Max (0902) measured |
| AA-Omniscience | 7.7 | 10.5 | Qwen3.8 Max (0902) |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: science | Not measured | 1514 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: medicine and healthcare | Not measured | 1514 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: legal and government | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: business and finance | Not measured | 1481 | Only Qwen3.8 Max (0902) measured |
| FACTS Benchmark Suite | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1269 | Only Qwen3.8 Max (0902) measured |
| Design Arena: UI components | Not measured | 1335 | Only Qwen3.8 Max (0902) measured |
| Design Arena: game dev | Not measured | 1310 | Only Qwen3.8 Max (0902) measured |
| Design Arena: data viz | Not measured | 1281 | Only Qwen3.8 Max (0902) measured |
| Design Arena: 3D | Not measured | 1318 | Only Qwen3.8 Max (0902) measured |
| Design Arena: all code categories | Not measured | 1287 | Only Qwen3.8 Max (0902) measured |
| Design Arena: ASCII art | Not measured | 1189 | Only Qwen3.8 Max (0902) measured |
| LiveBench design | Not measured | 76.6% | Only Qwen3.8 Max (0902) 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 | Muse Ember | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Vals Index | 60.5% | 59.1% | Muse Ember |
| LiveBench data analysis | Not measured | 78.4% | Only Qwen3.8 Max (0902) measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | Not measured | 81.8% | Only Qwen3.8 Max (0902) measured |
| MedScribe (Vals AI) | Not measured | 85.0% | Only Qwen3.8 Max (0902) measured |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 Max (0902) measured |
| GDPval-AA | Not measured | 1674 | Only Qwen3.8 Max (0902) measured |
| DTBench | Not measured | 92.0% | Only Qwen3.8 Max (0902) measured |
| LMCA | Not measured | 46.2% | Only Qwen3.8 Max (0902) measured |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | Not measured | 1485 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: instruction following | Not measured | 1483 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: creative writing | Not measured | 1482 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision | Not measured | 1312 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | Not measured | 1494 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: non-English | Not measured | 1475 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Chinese | Not measured | 1543 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: German | Not measured | 1475 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Japanese | Not measured | 1463 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Korean | Not measured | 1455 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: French | Not measured | 1504 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Spanish | Not measured | 1494 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Russian | Not measured | 1488 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Polish | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: multi-turn | Not measured | 1492 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: longer queries | Not measured | 1493 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: writing and language | Not measured | 1480 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: entertainment and media | Not measured | 1470 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: English | Not measured | 1310 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: Chinese | Not measured | 1353 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: humor | Not measured | 1309 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: creative writing | Not measured | 1310 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Ember | Qwen3.8 Max (0902) | 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$0.0003Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request
Muse Ember costs less
Repository review
50K input + 3K output tokens
Muse Ember$0.0065Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request
Muse Ember costs less
Agent loop
200K input + 10K output tokens
Muse Ember$0.025Fits in one request
Qwen3.8 Max (0902)$0.460Fits 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 | Meta Muse Ember | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | November 9, 2026 | September 3, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.10 | $2.00 |
| Output $/Mtok | $0.50 | $6.00 |
| Coding index | 64.9 | 67.3 |
| Independent measurements behind it | 3 | 5 |
| Cost per solved task | Not computable | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Ember better than Qwen3.8 Max (0902) for coding?
Pick Qwen3.8 Max (0902) for coding: it scores 67.3 on the Vibe Coding Index against 64.9 for Muse Ember. Pick Muse Ember for output tokens 12.0x cheaper ($0.50 vs $6.00 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, Muse Ember or Qwen3.8 Max (0902)?
Muse Ember costs $0.10 per million input tokens and $0.50 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.
Which has the bigger context window, Muse Ember or Qwen3.8 Max (0902)?
Muse Ember, with 1.05M tokens against 1M.
How many benchmarks is the Muse Ember vs Qwen3.8 Max (0902) comparison based on?
15 benchmarks have a result for both models as of November 14, 2026. Muse Ember's coding index rests on 3 independent benchmarks and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.