Muse Spark Open vs Qwen3.8 27B
Updated October 21, 2026. 22 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 62.1 for Muse Spark Open.
Pick Muse Spark Open when the context window is larger, 1.05M against 1M tokens, or when what matters is Vibe Code Bench (Vals AI) or Code migration (Vals AI), where it leads.
- Shared results
- 22
- Muse Spark Open only
- 4
- Qwen3.8 27B only
- 63
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Qwen3.8 27B
Qwen3.8 27B scores 73.6 against 62.1.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only Qwen3.8 27B has a AA Intelligence Index result, 33.7.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.8 27B has a AA Agentic Index result, 45.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.8 27B has a GPQA Diamond result, 88.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 27B has a MMLU Pro result, 84.3%.
Directional only
Web design
Design Arena: websites
No call
Only Muse Spark Open has a Design Arena: websites result, 1311.
Directional only
Long documents
Listed context window
Muse Spark Open
Muse Spark Open takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 27B
Muse Spark Open $0.0034, Qwen3.8 27B $0.0007 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 27B has the number, $1.26.
Directional only
At a glance
- Coding index
- Muse Spark Open 62.1 from 2 benchmarks, Qwen3.8 27B 73.6 from 2 benchmarks.
- Widest category
- Web design, 15.6 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveBench research: Muse Spark Open 80.3% against Qwen3.8 27B 59.4%, 20.9 points apart on a 0 to 100 scale.
- Output price
- Muse Spark Open $4.25 against Qwen3.8 27B $1.35 per million output tokens, 3.1x apart.
- Context window
- Muse Spark Open takes 1.05M tokens, Qwen3.8 27B 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 Spark Open | Bars | Qwen3.8 27B | Ties |
|---|---|---|---|---|
| Coding | 3 | 4 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 4 | ||
| Reasoning | 1 | 2 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 9 | 13 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index34
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | 86.8% | Qwen3.8 27B |
| LMArena WebDev | 1528 | 1593 | Qwen3.8 27B |
| AA Coding Index | Not measured | 68.1 | Only Qwen3.8 27B measured |
| LiveCodeBench (Vals AI) | Not measured | 84.0% | Only Qwen3.8 27B measured |
| SWE-bench Verified (Vals AI) | Not measured | 86.0% | Only Qwen3.8 27B measured |
| Terminal-Bench 4 (Vals AI) | 6.6% | Not measured | Only Muse Spark Open measured |
| Vibe Code Bench (Vals AI) | 76.2% | 64.8% | Muse Spark Open |
| Code migration (Vals AI) | 21.2% | 14.2% | Muse Spark Open |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 27B measured |
| IOI (Vals AI) | Not measured | 39.1% | Only Qwen3.8 27B measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 58.4% | Only Qwen3.8 27B measured |
| SkillsBench (Vals AI) | Not measured | 38.1% | Only Qwen3.8 27B measured |
| CyberBench (Vals AI) | Not measured | 67.8% | Only Qwen3.8 27B measured |
| SciCode | 58.4% | 46.6% | Muse Spark Open |
| ALE-Bench | 1590.1 | Not measured | Only Muse Spark Open measured |
| LMArena Text: coding | Not measured | 1483 | Only Qwen3.8 27B measured |
| LMArena Text: software and IT | Not measured | 1478 | Only Qwen3.8 27B measured |
| LMArena WebDev: React | 1529 | 1602 | Qwen3.8 27B |
| LMArena WebDev: HTML | 1495 | 1570 | Qwen3.8 27B |
| LMArena WebDev: from an image | Not measured | 1577 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 33.7 | Only Qwen3.8 27B measured |
| Epoch Capabilities Index | 155.1 | 151.7 | Muse Spark Open |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 45.8 | Only Qwen3.8 27B measured |
| LiveBench research | 80.3% | 59.4% | Muse Spark Open |
| LiveBench browser | 36.0% | 32.0% | Muse Spark Open |
| LiveBench long agentic | 18.9% | 27.9% | Qwen3.8 27B |
| Finance Agent (Vals AI) | 61.3% | 48.5% | Muse Spark Open |
| Tax Agent Bench (Vals AI) | 26.3% | 30.9% | Qwen3.8 27B |
| Legal Research Bench (Vals AI) | 38.5% | 36.1% | Muse Spark Open |
| Excel Modeling Benchmark (Vals AI) | 53.7% | 59.7% | Qwen3.8 27B |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only Qwen3.8 27B measured |
| APEX-Agents | 33.4% | 47.5% | Qwen3.8 27B |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 88.9% | Only Qwen3.8 27B measured |
| LiveBench reasoning | 73.7% | 80.0% | Qwen3.8 27B |
| MMMU Pro (Vals AI) | Not measured | 83.9% | Only Qwen3.8 27B measured |
| GPQA Diamond (Artificial Analysis run) | 89.0% | 90.5% | Qwen3.8 27B |
| Humanity's Last Exam (Artificial Analysis run) | 43.9% | 33.9% | Muse Spark Open |
| ARC-AGI | Not measured | 87.5% | Only Qwen3.8 27B measured |
| ARC-AGI-2 | Not measured | 42.4% | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts | Not measured | 1459 | Only Qwen3.8 27B measured |
| LMArena Text: expert | Not measured | 1479 | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts in English | Not measured | 1461 | Only Qwen3.8 27B measured |
| LMArena Vision: diagrams | Not measured | 1285 | Only Qwen3.8 27B measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| ProofBench | Not measured | 16.0% | Only Qwen3.8 27B measured |
| LMArena Text: math | Not measured | 1455 | Only Qwen3.8 27B measured |
| LMArena Text: mathematical work | Not measured | 1458 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.3% | Only Qwen3.8 27B measured |
| LegalBench (Vals AI) | Not measured | 82.4% | Only Qwen3.8 27B measured |
| TaxEval (Vals AI) | Not measured | 70.8% | Only Qwen3.8 27B measured |
| MortgageTax (Vals AI) | Not measured | 64.9% | Only Qwen3.8 27B measured |
| MedCode (Vals AI) | Not measured | 28.7% | Only Qwen3.8 27B measured |
| LMArena Text: science | Not measured | 1467 | Only Qwen3.8 27B measured |
| LMArena Text: medicine and healthcare | Not measured | 1437 | Only Qwen3.8 27B measured |
| LMArena Text: legal and government | Not measured | 1447 | Only Qwen3.8 27B measured |
| LMArena Text: business and finance | Not measured | 1438 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1311 | Not measured | Only Muse Spark Open measured |
| Design Arena: game dev | 1290 | Not measured | Only Muse Spark Open measured |
| LiveBench design | 60.3% | 75.9% | Qwen3.8 27B |
| Neither model has a result on the other 6 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Muse Spark Open | Qwen3.8 27B | Leader |
|---|---|---|---|
| LiveBench data analysis | 60.2% | 76.6% | Qwen3.8 27B |
| SAGE (Vals AI) | Not measured | 52.4% | Only Qwen3.8 27B measured |
| MedScribe (Vals AI) | Not measured | 83.8% | Only Qwen3.8 27B measured |
| Long context reasoning (AA-LCR) | 78.3% | 82.0% | Qwen3.8 27B |
| DTBench | Not measured | 88.0% | Only Qwen3.8 27B measured |
| LMCA | Not measured | 41.4% | Only Qwen3.8 27B measured |
| Surface Evolver Bench | Not measured | 45.0% | Only Qwen3.8 27B measured |
| LMArena Text | Not measured | 1440 | Only Qwen3.8 27B measured |
| LMArena Text: instruction following | Not measured | 1436 | Only Qwen3.8 27B measured |
| LMArena Text: creative writing | Not measured | 1383 | Only Qwen3.8 27B measured |
| LMArena Vision | Not measured | 1269 | Only Qwen3.8 27B measured |
| LMArena Text: English | Not measured | 1448 | Only Qwen3.8 27B measured |
| LMArena Text: non-English | Not measured | 1428 | Only Qwen3.8 27B measured |
| LMArena Text: Chinese | Not measured | 1501 | Only Qwen3.8 27B measured |
| LMArena Text: German | Not measured | 1443 | Only Qwen3.8 27B measured |
| LMArena Text: Japanese | Not measured | 1387 | Only Qwen3.8 27B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.8 27B measured |
| LMArena Text: French | Not measured | 1465 | Only Qwen3.8 27B measured |
| LMArena Text: Spanish | Not measured | 1449 | Only Qwen3.8 27B measured |
| LMArena Text: Russian | Not measured | 1415 | Only Qwen3.8 27B measured |
| LMArena Text: Polish | Not measured | 1439 | Only Qwen3.8 27B measured |
| LMArena Text: multi-turn | Not measured | 1440 | Only Qwen3.8 27B measured |
| LMArena Text: longer queries | Not measured | 1448 | Only Qwen3.8 27B measured |
| LMArena Text: writing and language | Not measured | 1405 | Only Qwen3.8 27B measured |
| LMArena Text: entertainment and media | Not measured | 1393 | Only Qwen3.8 27B measured |
| LMArena Vision: English | Not measured | 1267 | Only Qwen3.8 27B measured |
| LMArena Vision: Chinese | Not measured | 1326 | Only Qwen3.8 27B measured |
| LMArena Vision: reading text | Not measured | 1281 | Only Qwen3.8 27B measured |
| LMArena Vision: humor | Not measured | 1235 | Only Qwen3.8 27B measured |
| LMArena Vision: creative writing | Not measured | 1237 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Spark Open | Qwen3.8 27B | 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
Qwen3.8 27B costs less
Repository review
50K input + 3K output tokens
Qwen3.8 27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 27B 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 Spark Open | Qwen3.8 27B |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | Open weights | Open weights |
| Released | October 15, 2026 | August 14, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.25 | $0.04 |
| Output $/Mtok | $4.25 | $1.35 |
| Coding index | 62.1 | 73.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $1.26 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Spark Open better than Qwen3.8 27B for coding?
Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 62.1 for Muse Spark Open. Pick Muse Spark Open when the context window is larger, 1.05M against 1M tokens, or when what matters is Vibe Code Bench (Vals AI) or Code migration (Vals AI), where it leads.
Which is cheaper, Muse Spark Open or Qwen3.8 27B?
Muse Spark Open costs $1.25 per million input tokens and $4.25 per million output tokens; Qwen3.8 27B costs $0.04 and $1.35. Cost per solved task is known for Qwen3.8 27B only.
Which has the bigger context window, Muse Spark Open or Qwen3.8 27B?
Muse Spark Open, with 1.05M tokens against 1M.
How many benchmarks is the Muse Spark Open vs Qwen3.8 27B comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. Muse Spark Open's coding index rests on 2 independent benchmarks and Qwen3.8 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.