Model comparison
Muse Spark vs Qwen3.6-27B
Head-to-head evidence from 25 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Muse Spark #13 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Muse Spark and Qwen3.6-27B share 25 comparable benchmark results. 5 of 8 categories are comparable. 14 results are unique to Muse Spark; 29 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 25
- Muse Spark only
- 14
- Qwen3.6-27B only
- 29
- Comparable categories
- 5 / 8
Pick Muse Spark if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority.
Confidence note. This is a partial-evidence comparison with 25 shared benchmark results across 6 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Muse Spark is clearly ahead on the BenchAlign aggregate, 71.04 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Muse Spark's sharpest advantage is in multimodal & grounded, where it averages 82.5 against 76.7. The single biggest benchmark swing on the page is HLE, 50.4% to 24%. Qwen3.6-27B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Muse Spark | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | Muse Spark32.9 | Margin→ 56.3 | Qwen3.6-27B89.2 |
| Coding | Muse Spark67.8 | Margin→ 9.7 | Qwen3.6-27B77.5 |
| Multimodal | Muse Spark82.5 | Margin← 5.8 | Qwen3.6-27B76.7 |
| Knowledge | Muse Spark50.4 | Margin→ 2.9 | Qwen3.6-27B53.3 |
| Agentic | Muse Spark59.0 | Margin→ 0.3 | Qwen3.6-27B59.3 |
| Reasoning | Muse Spark42.5 | MarginNo overlap | Qwen3.6-27BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 50.4%B 24%Winner: Muse SparkΔ 26.4HLE: Muse Spark scored 50.4%; Qwen3.6-27B scored 24%. Muse Spark wins this benchmark. - Source ↗
CharXiv
MultimodalA 86.4%B 78.4%Winner: Muse SparkΔ 8CharXiv: Muse Spark scored 86.4%; Qwen3.6-27B scored 78.4%. Muse Spark wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 80.4%B 75.8%Winner: Muse SparkΔ 4.6MMMU-Pro: Muse Spark scored 80.4%; Qwen3.6-27B scored 75.8%. Muse Spark wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.4%B 53.5%Winner: Qwen3.6-27BΔ 1.1SWE-bench Pro: Muse Spark scored 52.4%; Qwen3.6-27B scored 53.5%. Qwen3.6-27B wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 59%B 59.3%Winner: Qwen3.6-27BΔ 0.3Terminal-Bench 2.0: Muse Spark scored 59%; Qwen3.6-27B scored 59.3%. Qwen3.6-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Muse Spark | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Muse SparkNot available | Qwen3.6-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Muse SparkNot available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Muse SparkNot available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Muse Spark262K | Qwen3.6-27B262K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticQwen3.6-27B wins12 benchmarks
| Benchmark | Muse Spark | Qwen3.6-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59% | 59.3% | Qwen3.6-27B leads |
| τ²-bench resultsSource | 91.5% | 94.2% | Qwen3.6-27B leads |
| DeepSearchQASource | 74.8% | — | Not comparable |
| CyberGymSource | 43.5% | — | Not comparable |
| Claw-EvalSource | 63.8% | 72.4% | Qwen3.6-27B leads |
| AA Agentic IndexSource | 28.7% | 27.0% | Muse Spark leads |
| GDPval-AASource | 32.2% | 32.0% | Muse Spark leads |
| GDPval-AASource | 1144 | 1140 | Muse Spark leads |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
CodingQwen3.6-27B wins10 benchmarks
| Benchmark | Muse Spark | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.4% | 77.2% | Muse Spark leads |
| SWE-bench ProSource | 52.4% | 53.5% | Qwen3.6-27B leads |
| LiveCodeBench ProSource | 80.0% | — | Not comparable |
| Vibe Code BenchSource | 19.67% | — | Not comparable |
| AA Coding IndexSource | 58.6% | 53.7% | Muse Spark leads |
| AA-SciCodeSource | 51.5% | 39.8% | Muse Spark leads |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning3 benchmarks
KnowledgeQwen3.6-27B wins16 benchmarks
| Benchmark | Muse Spark | Qwen3.6-27B | Result |
|---|---|---|---|
| GPQA-DSource | 89.5% | — | Not comparable |
| HLESource | 50.4% | 24% | Muse Spark leads |
| HLE w/o toolsSource | 42.8% | — | Not comparable |
| HealthBench HardSource | 42.8% | — | Not comparable |
| MedXpertQA (Text)Source | 52.6% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 43.1% | 37.0% | Muse Spark leads |
| AA-GPQA DiamondSource | 88.4% | 84.2% | Muse Spark leads |
| AA-HLESource | 39.9% | 21.6% | Muse Spark leads |
| AA-Omniscience IndexSource | 4.1% | -19.8% | Muse Spark leads |
| AA-Omniscience AccuracySource | 44.6% | 19.2% | Muse Spark leads |
| AA-Omniscience Hallucination RateSource | 73.2% | 48.3% | Qwen3.6-27B leads |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
MathQwen3.6-27B wins7 benchmarks
| Benchmark | Muse Spark | Qwen3.6-27B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 39.000% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 14.600% | — | Not comparable |
| HMMT Feb 2025Source | — | 93.8% | Not comparable |
| HMMT Nov 2025Source | — | 90.7% | Not comparable |
| HMMT Feb 2026Source | — | 84.3% | Not comparable |
| MMAnswerBenchSource | — | 80.8% | Not comparable |
| AIME26Source | — | 94.1% | Not comparable |
MultimodalMuse Spark wins19 benchmarks
| Benchmark | Muse Spark | Qwen3.6-27B | Result |
|---|---|---|---|
| CharXivSource | 86.4% | 78.4% | Muse Spark leads |
| MMMU-ProSource | 80.4% | 75.8% | Muse Spark leads |
| ERQASource | 64.7% | 62.5% | Muse Spark leads |
| SimpleVQASource | 71.3% | 56.1% | Muse Spark leads |
| ScreenSpot ProSource | 84.1% | — | Not comparable |
| ZeroBenchSource | 33.0% | — | Not comparable |
| MedXpertQA (MM)Source | 78.4% | — | Not comparable |
| AA-MMMU-ProSource | 80.5% | 74.6% | Muse Spark leads |
| MMMUSource | — | 82.9% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Muse Spark | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | 67.6% | Muse Spark leads |
Frequently Asked Questions (6)
Which is better, Muse Spark or Qwen3.6-27B?
Muse Spark is ahead on BenchLM's BenchAlign leaderboard, 71.04 to 53.82. The biggest single separator in this matchup is HLE, where the scores are 50.4% and 24%.
Which is better for knowledge tasks, Muse Spark or Qwen3.6-27B?
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 53.3 versus 50.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, Muse Spark or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 67.8. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, Muse Spark or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 32.9. Muse Spark stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Muse Spark or Qwen3.6-27B?
Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 59. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Muse Spark or Qwen3.6-27B?
Muse Spark has the edge for multimodal and grounded tasks in this comparison, averaging 82.5 versus 76.7. Inside this category, SimpleVQA is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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