Muse Spark Open vs Qwen3.8 Max (0902)
Updated October 21, 2026. 25 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Muse Spark Open and Qwen3.8 Max (0902) are level for coding, 62.1 against 63.5 on the Vibe Coding Index, so price and context decide.
Pick Muse Spark Open when output tokens cost 1.4x less, or when the context window is larger, 1.05M against 1M tokens. Pick Qwen3.8 Max (0902) when what matters is LMArena WebDev or Terminal-Bench 4 (Vals AI), where it leads.
- Shared results
- 25
- Muse Spark Open only
- 1
- Qwen3.8 Max (0902) only
- 88
- 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
No call
Level: 62.1 against 63.5, inside 2 points.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only Qwen3.8 Max (0902) has a AA Intelligence Index result, 45.4.
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
Muse Spark Open
Muse Spark Open leads, 1311 against 1275.
Same board, both measured
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
Muse Spark Open
Muse Spark Open $0.0034, 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 Spark Open 62.1 from 2 benchmarks, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
- Widest category
- Coding, 13.8 points apart on average over 8 shared benchmarks.
- Widest single gap
- APEX-Agents: Muse Spark Open 33.4% against Qwen3.8 Max (0902) 63.3%, 29.9 points apart on a 0 to 100 scale.
- Output price
- Muse Spark Open $4.25 against Qwen3.8 Max (0902) $6.00 per million output tokens, 1.4x apart.
- Context window
- Muse Spark Open 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 Spark Open | Bars | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 3 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 3 | 5 | ||
| Reasoning | 1 | 2 | ||
| Web design | 1 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 8 | 17 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index35
| Benchmark | Muse Spark Open | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | 60.3% | Muse Spark Open |
| LMArena WebDev | 1528 | 1674 | 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) | 6.6% | 34.3% | Qwen3.8 Max (0902) |
| Vibe Code Bench (Vals AI) | 76.2% | 64.7% | Muse Spark Open |
| Code migration (Vals AI) | 21.2% | 24.0% | Qwen3.8 Max (0902) |
| 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 | 12.8% | 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 | 58.4% | 53.2% | Muse Spark Open |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| ALE-Bench | 1590.1 | Not measured | Only Muse Spark Open measured |
| LMArena Text: coding | Not measured | 1502 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: software and IT | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: React | 1529 | 1692 | Qwen3.8 Max (0902) |
| LMArena WebDev: HTML | 1495 | 1649 | Qwen3.8 Max (0902) |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Muse Spark Open | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 45.4 | Only Qwen3.8 Max (0902) measured |
| Epoch Capabilities Index | 155.1 | 157.4 | Qwen3.8 Max (0902) |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index35
| Benchmark | Muse Spark Open | 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 | 1301 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building full-stack apps | Not measured | 1305 | 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 | 1207 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Godot games | Not measured | 1234 | Only Qwen3.8 Max (0902) measured |
| Design Arena: PowerPoint slides | Not measured | 1257 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 868 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | 80.3% | 69.9% | Muse Spark Open |
| LiveBench browser | 36.0% | 32.0% | Muse Spark Open |
| LiveBench long agentic | 18.9% | 42.3% | Qwen3.8 Max (0902) |
| Finance Agent (Vals AI) | 61.3% | 50.6% | Muse Spark Open |
| Tax Agent Bench (Vals AI) | 26.3% | 32.1% | Qwen3.8 Max (0902) |
| Legal Research Bench (Vals AI) | 38.5% | 47.6% | Qwen3.8 Max (0902) |
| Excel Modeling Benchmark (Vals AI) | 53.7% | 60.1% | Qwen3.8 Max (0902) |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| APEX-Agents | 33.4% | 63.3% | Qwen3.8 Max (0902) |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Muse Spark Open | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.7% | Only Qwen3.8 Max (0902) measured |
| LiveBench reasoning | 73.7% | 88.2% | Qwen3.8 Max (0902) |
| 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) | 89.0% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | 43.9% | 43.1% | Muse Spark Open |
| 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 | 1496 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: expert | Not measured | 1507 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts in English | Not measured | 1503 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: diagrams | Not measured | 1323 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: homework | Not measured | 1336 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Muse Spark Open | 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 | 1501 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: mathematical work | Not measured | 1491 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Muse Spark Open | 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 |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: science | Not measured | 1512 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: medicine and healthcare | Not measured | 1503 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: legal and government | Not measured | 1492 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: business and finance | Not measured | 1480 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Muse Spark Open | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 1311 | 1275 | Muse Spark Open |
| Design Arena: UI components | Not measured | 1340 | Only Qwen3.8 Max (0902) measured |
| Design Arena: game dev | 1290 | 1313 | Qwen3.8 Max (0902) |
| Design Arena: data viz | Not measured | 1281 | Only Qwen3.8 Max (0902) measured |
| Design Arena: 3D | Not measured | 1337 | Only Qwen3.8 Max (0902) measured |
| Design Arena: all code categories | Not measured | 1293 | Only Qwen3.8 Max (0902) measured |
| Design Arena: ASCII art | Not measured | 1201 | Only Qwen3.8 Max (0902) measured |
| LiveBench design | 60.3% | 78.6% | Qwen3.8 Max (0902) |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Muse Spark Open | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench data analysis | 60.2% | 78.4% | Qwen3.8 Max (0902) |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | Not measured | 51.2% | 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) | 78.3% | 80.3% | Qwen3.8 Max (0902) |
| 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 | 1483 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: instruction following | Not measured | 1481 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: creative writing | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | Not measured | 1491 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: non-English | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Chinese | Not measured | 1539 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: German | Not measured | 1478 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Japanese | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Korean | Not measured | 1460 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: French | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Spanish | Not measured | 1489 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Russian | Not measured | 1482 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Polish | Not measured | 1471 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: multi-turn | Not measured | 1489 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: longer queries | Not measured | 1488 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: writing and language | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: entertainment and media | Not measured | 1464 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: English | Not measured | 1311 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: Chinese | Not measured | 1358 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: humor | Not measured | 1304 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Qwen3.8 Max (0902) 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 | Muse Spark Open | 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 Spark Open costs less
Repository review
50K input + 3K output tokens
Muse Spark Open costs less
Agent loop
200K input + 10K output tokens
Muse Spark Open 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 Max (0902) |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | Open weights | No public weights listed |
| Released | October 15, 2026 | September 3, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.25 | $2.00 |
| Output $/Mtok | $4.25 | $6.00 |
| Coding index | 62.1 | 63.5 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Spark Open better than Qwen3.8 Max (0902) for coding?
Muse Spark Open and Qwen3.8 Max (0902) are level for coding, 62.1 against 63.5 on the Vibe Coding Index, so price and context decide. Pick Muse Spark Open when output tokens cost 1.4x less, or when the context window is larger, 1.05M against 1M tokens. Pick Qwen3.8 Max (0902) when what matters is LMArena WebDev or Terminal-Bench 4 (Vals AI), where it leads.
Which is cheaper, Muse Spark Open or Qwen3.8 Max (0902)?
Muse Spark Open costs $1.25 per million input tokens and $4.25 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 Spark Open or Qwen3.8 Max (0902)?
Muse Spark Open, with 1.05M tokens against 1M.
How many benchmarks is the Muse Spark Open vs Qwen3.8 Max (0902) comparison based on?
25 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 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.