Coding
Directional only- Muse Spark
- 67.8
- Qwen3.8-27B
- 61.7
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Muse Spark vs Qwen3.8-27B
Updated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
6 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
18 Muse Spark only
6 Shared
21 Qwen3.8-27B only
- Shared results
- 6
- Muse Spark only
- 18
- Qwen3.8-27B only
- 21
- Like-for-like categories
- 0 / 8
3 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Knowledge
Directional only- Muse Spark
- 50.4
- Qwen3.8-27B
- 38.7
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Multimodal
Directional only- Muse Spark
- 82.5
- Qwen3.8-27B
- 90.2
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Agentic
Not comparable- Muse Spark
- 59.0
- Qwen3.8-27B
- 84.3
- Weighted basis
- 1 vs 1 rows
- Reading
- Not comparable
Reasoning
Not comparable- Muse Spark
- 42.5
- Qwen3.8-27B
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Muse Spark
- 32.9
- Qwen3.8-27B
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Muse Spark
- Not measured
- Qwen3.8-27B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Muse Spark
- Not measured
- Qwen3.8-27B
- 79.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | Muse Spark | Qwen3.8-27B | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 67.8 | 61.7 | Directional only2 vs 1 rows | Directional only |
| Knowledge | 50.4 | 38.7 | Directional only1 vs 2 rows | Directional only |
| Multimodal | 82.5 | 90.2 | Directional only2 vs 1 rows | Directional only |
| Agentic | 59.0 | 84.3 | Not comparable1 vs 1 rows | Not comparable |
| Reasoning | 42.5 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 32.9 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | 79.5 | Not comparable0 vs 1 rows | Not comparable |
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
HLE
Knowledge
SWE-bench Pro
Coding
CharXiv
Multimodal
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Muse Spark
- API rate not published
- Fits in one request
- Qwen3.8-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
Muse Spark has no comparable published API token rate. Qwen3.8-27B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Muse Spark
- API rate not published
- Fits in one request
- Qwen3.8-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
Muse Spark has no comparable published API token rate. Qwen3.8-27B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Muse Spark
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Qwen3.8-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Muse Spark has no comparable published API token rate. Qwen3.8-27B has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationMuse SparkQwen3.8-27B
Context window
Maximum documented context; output-token limits may be lower.
Muse Spark
262K
Qwen3.8-27B
API model ID
Muse Spark
Not sourced
Qwen3.8-27B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Muse Spark
No comparable hosted API rate
Qwen3.8-27B
No comparable hosted API rate
Qwen3.8-27B model cardDocumented inputs
Muse Spark
Not sourced
Qwen3.8-27B
Not sourced
Documented outputs
Muse Spark
Not sourced
Qwen3.8-27B
Not sourced
Provider availability
Muse Spark
Not sourced
Qwen3.8-27B
Not sourced
Reasoning profile
Muse Spark
Reasoning
Qwen3.8-27B
Reasoning
Weight access
Muse Spark
Proprietary
Qwen3.8-27B
Open Weight
License
Muse Spark
Proprietary
Qwen3.8-27B
Open Weight
Release date
Muse Spark
2026-04-08
Qwen3.8-27B
2026-08-05
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 262K.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence45 rows
Agentic
Terminal-Bench 2.0
Muse Spark59%SourceQwen3.8-27B—Not directly comparable
τ²-bench results
Muse Spark91.5%SourceQwen3.8-27B—Not directly comparable
DeepSearchQA
Muse Spark74.8%SourceQwen3.8-27B—Not directly comparable
CyberGym
Muse Spark43.5%SourceQwen3.8-27B—Not directly comparable
Claw-Eval
Muse Spark63.8%SourceQwen3.8-27B—Not directly comparable
Terminal-Bench 2.1
Muse Spark—Qwen3.8-27B73.0%SourceNot directly comparable
CoWorkBench
Muse Spark—Qwen3.8-27B70.7%SourceNot directly comparable
JobBench
Muse Spark—Qwen3.8-27B33.4%SourceNot directly comparable
Agents' Last Exam
Muse Spark—Qwen3.8-27B42.9%SourceNot directly comparable
OSWorld-Verified
Muse Spark—Qwen3.8-27B84.3%SourceNot directly comparable
WebArena-Verified
Muse Spark—Qwen3.8-27B64.8%SourceNot directly comparable
AndroidWorld
Muse Spark—Qwen3.8-27B81.9%SourceNot directly comparable
Coding
SWE-bench Verified
Muse Spark77.4%SourceQwen3.8-27B—Not directly comparable
SWE-bench Pro
Muse Spark52.4%SourceQwen3.8-27B61.7%SourceQwen3.8-27B leads this result
LiveCodeBench Pro
Muse Spark80.0%SourceQwen3.8-27B—Not directly comparable
Vibe Code Bench
Muse Spark19.67%SourceQwen3.8-27B—Not directly comparable
Terminal-Bench 2.1
Muse Spark—Qwen3.8-27B73.0%SourceNot directly comparable
NL2Repo
Muse Spark—Qwen3.8-27B42.3%SourceNot directly comparable
deepSwe
Muse Spark—Qwen3.8-27B42.2%SourceNot directly comparable
LiveCodeBench v6
Muse Spark—Qwen3.8-27B90.3%SourceNot directly comparable
Reasoning
ARC-AGI-2
Muse Spark42.5%SourceQwen3.8-27B—Not directly comparable
Knowledge
GPQA-D
Muse Spark89.5%SourceQwen3.8-27B89.2%SourceMuse Spark leads this result
HLE
Muse Spark50.4%SourceQwen3.8-27B30.8%SourceMuse Spark leads this result
HLE w/o tools
Muse Spark42.8%SourceQwen3.8-27B30.8%SourceMuse Spark leads this result
HealthBench Hard
Muse Spark42.8%SourceQwen3.8-27B—Not directly comparable
MedXpertQA (Text)
Muse Spark52.6%SourceQwen3.8-27B—Not directly comparable
GPQA
Muse Spark—Qwen3.8-27B89.2%SourceNot directly comparable
Math
Multimodal
CharXiv
Muse Spark86.4%SourceQwen3.8-27B90.2%SourceQwen3.8-27B leads this result
MMMU-Pro
Muse Spark80.4%SourceQwen3.8-27B—Not directly comparable
ERQA
Muse Spark64.7%SourceQwen3.8-27B65.5%SourceQwen3.8-27B leads this result
SimpleVQA
Muse Spark71.3%SourceQwen3.8-27B—Not directly comparable
ScreenSpot Pro
Muse Spark84.1%SourceQwen3.8-27B—Not directly comparable
ZeroBench
Muse Spark33.0%SourceQwen3.8-27B—Not directly comparable
MedXpertQA (MM)
Muse Spark78.4%SourceQwen3.8-27B—Not directly comparable
MathVision
Muse Spark—Qwen3.8-27B90.0%SourceNot directly comparable
MathVision w/ Python
Muse Spark—Qwen3.8-27B94.6%SourceNot directly comparable
BabyVision
Muse Spark—Qwen3.8-27B65.7%SourceNot directly comparable
BabyVision w/ Python
Muse Spark—Qwen3.8-27B85.6%SourceNot directly comparable
Vision2Web
Muse Spark—Qwen3.8-27B62.9%SourceNot directly comparable
CharXiv w/o tools
Muse Spark—Qwen3.8-27B83.7%SourceNot directly comparable
OmniDocBench 1.5
Muse Spark—Qwen3.8-27B91.1%SourceNot directly comparable
RealWorldQA
Muse Spark—Qwen3.8-27B85.9%SourceNot directly comparable
Instruction following
IFBench
Muse Spark—Qwen3.8-27B79.5%SourceNot directly comparable
Frequently asked questions
Which is better, Muse Spark or Qwen3.8-27B?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Muse Spark or Qwen3.8-27B?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Muse Spark or Qwen3.8-27B?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Muse Spark or Qwen3.8-27B?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Muse Spark or Qwen3.8-27B?
Both models list the same context window, 262K.
Related comparisons
Last updated August 14, 2026
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