Muse Ember vs Qwen3.5-Flash
Muse Ember leads Qwen3.5-Flash on coding, 64.9 to 41.1 on the Vibe Coding Index, and Qwen3.5-Flash costs 1.9x less per output token ($0.26 vs $0.50 per million). Updated November 14, 2026; 3 benchmarks have a result for both.
Muse Ember or Qwen3.5-Flash: which to pick
Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 41.1 for Qwen3.5-Flash.
Pick Qwen3.5-Flash for output tokens 1.9x cheaper ($0.26 vs $0.50 per million).
- Shared results
- 3
- Muse Ember only
- 12
- Qwen3.5-Flash only
- 52
- Like-for-like categories
- 1 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 41.1.
3 and 2 benchmarks behind the scores
Reasoning
GPQA Diamond
No call
Only Qwen3.5-Flash has a GPQA Diamond result, 82.8%.
Directional only
Math
AIME
No call
Only Qwen3.5-Flash has a AIME result, 92.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5-Flash has a MMLU Pro result, 84.1%.
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
Qwen3.5-Flash
Muse Ember $0.0003, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5-Flash has the number, $0.40.
Directional only
At a glance
- Coding index
- Muse Ember 64.9 from 3 benchmarks, Qwen3.5-Flash 41.1 from 2 benchmarks.
- Widest category
- Coding, 55.3 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Muse Ember 1616 against Qwen3.5-Flash 1228, 62.0 points apart on a 0 to 100 scale.
- Output price
- Muse Ember $0.50 against Qwen3.5-Flash $0.26 per million output tokens, 1.9x apart.
- Context window
- Muse Ember takes 1.05M tokens, Qwen3.5-Flash 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 | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| All shared boards | 3 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | 1609 | 1243 | Muse Ember |
| LiveCodeBench (Vals AI) | Not measured | 83.3% | Only Qwen3.5-Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 64.4% | Only Qwen3.5-Flash measured |
| Terminal-Bench 4 (Vals AI) | 39.4% | Not measured | Only Muse Ember measured |
| Vibe Code Bench (Vals AI) | 83.7% | Not measured | Only Muse Ember measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | 40.9% | Not measured | Only Muse Ember measured |
| FrontierCode 2.0 | 27.2% | Not measured | Only Muse Ember measured |
| ALE-Bench | Not measured | 265.9 | Only Qwen3.5-Flash measured |
| LMArena Text: coding | Not measured | 1412 | Only Qwen3.5-Flash measured |
| LMArena Text: software and IT | Not measured | 1416 | Only Qwen3.5-Flash measured |
| LMArena WebDev: React | 1616 | 1228 | Muse Ember |
| LMArena WebDev: HTML | 1621 | 1291 | Muse Ember |
| Neither model has a result on the other 40 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 143.8 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Tax Agent Bench (Vals AI) | 38.2% | Not measured | Only Muse Ember measured |
| Legal Research Bench (Vals AI) | 49.0% | Not measured | Only Muse Ember measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 25.0% | Not measured | Only Muse Ember measured |
| APEX-Agents | 64.3% | Not measured | Only Muse Ember measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.8% | Only Qwen3.5-Flash measured |
| MMMU Pro (Vals AI) | Not measured | 81.9% | Only Qwen3.5-Flash 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 | 82.3% | Only Qwen3.5-Flash measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.5-Flash measured |
| Mystery game puzzles | Not measured | 20.0% | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts | Not measured | 1404 | Only Qwen3.5-Flash measured |
| LMArena Text: expert | Not measured | 1408 | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1409 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | Not measured | 92.5% | Only Qwen3.5-Flash measured |
| OTIS Mock AIME | Not measured | 84.4% | Only Qwen3.5-Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 18.2% | Only Qwen3.5-Flash measured |
| LMArena Text: math | Not measured | 1407 | Only Qwen3.5-Flash measured |
| LMArena Text: mathematical work | Not measured | 1413 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.1% | Only Qwen3.5-Flash measured |
| LegalBench (Vals AI) | Not measured | 84.3% | Only Qwen3.5-Flash measured |
| CaseLaw (Vals AI) | Not measured | 56.0% | Only Qwen3.5-Flash measured |
| CorpFin (Vals AI) | Not measured | 63.6% | Only Qwen3.5-Flash measured |
| TaxEval (Vals AI) | Not measured | 72.2% | Only Qwen3.5-Flash measured |
| MortgageTax (Vals AI) | Not measured | 67.4% | Only Qwen3.5-Flash measured |
| MedCode (Vals AI) | Not measured | 33.0% | Only Qwen3.5-Flash measured |
| AA-Omniscience | 7.7 | Not measured | Only Muse Ember measured |
| SimpleQA Verified | Not measured | 20.3% | Only Qwen3.5-Flash measured |
| LMArena Text: science | Not measured | 1414 | Only Qwen3.5-Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1408 | Only Qwen3.5-Flash measured |
| LMArena Text: legal and government | Not measured | 1398 | Only Qwen3.5-Flash measured |
| LMArena Text: business and finance | Not measured | 1395 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 8 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Vals Index | 60.5% | Not measured | Only Muse Ember measured |
| SAGE (Vals AI) | Not measured | 84.9% | Only Qwen3.5-Flash measured |
| MedScribe (Vals AI) | Not measured | 70.6% | Only Qwen3.5-Flash measured |
| DTBench | Not measured | 82.9% | Only Qwen3.5-Flash measured |
| LMCA | Not measured | 29.1% | Only Qwen3.5-Flash measured |
| LMArena Text | Not measured | 1397 | Only Qwen3.5-Flash measured |
| LMArena Text: instruction following | Not measured | 1375 | Only Qwen3.5-Flash measured |
| LMArena Text: creative writing | Not measured | 1343 | Only Qwen3.5-Flash measured |
| LMArena Text: English | Not measured | 1404 | Only Qwen3.5-Flash measured |
| LMArena Text: non-English | Not measured | 1385 | Only Qwen3.5-Flash measured |
| LMArena Text: Chinese | Not measured | 1447 | Only Qwen3.5-Flash measured |
| LMArena Text: German | Not measured | 1390 | Only Qwen3.5-Flash measured |
| LMArena Text: Japanese | Not measured | 1368 | Only Qwen3.5-Flash measured |
| LMArena Text: Korean | Not measured | 1345 | Only Qwen3.5-Flash measured |
| LMArena Text: French | Not measured | 1413 | Only Qwen3.5-Flash measured |
| LMArena Text: Spanish | Not measured | 1400 | Only Qwen3.5-Flash measured |
| LMArena Text: Russian | Not measured | 1380 | Only Qwen3.5-Flash measured |
| LMArena Text: Polish | Not measured | 1377 | Only Qwen3.5-Flash measured |
| LMArena Text: multi-turn | Not measured | 1393 | Only Qwen3.5-Flash measured |
| LMArena Text: longer queries | Not measured | 1392 | Only Qwen3.5-Flash measured |
| LMArena Text: writing and language | Not measured | 1369 | Only Qwen3.5-Flash measured |
| LMArena Text: entertainment and media | Not measured | 1348 | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Ember | Qwen3.5-Flash | 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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-Flash 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 | Qwen3.5-Flash |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | November 9, 2026 | February 25, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.10 | $0.065 |
| Output $/Mtok | $0.50 | $0.26 |
| Coding index | 64.9 | 41.1 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | Not computable | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Ember better than Qwen3.5-Flash for coding?
Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 41.1 for Qwen3.5-Flash. Pick Qwen3.5-Flash for output tokens 1.9x cheaper ($0.26 vs $0.50 per million).
Which is cheaper, Muse Ember or Qwen3.5-Flash?
Muse Ember costs $0.10 per million input tokens and $0.50 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.
Which has the bigger context window, Muse Ember or Qwen3.5-Flash?
Muse Ember, with 1.05M tokens against 1M.
How many benchmarks is the Muse Ember vs Qwen3.5-Flash comparison based on?
3 benchmarks have a result for both models as of November 14, 2026. Muse Ember's coding index rests on 3 independent benchmarks and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.