Model comparison

Muse Spark vs Qwen3.8 Max

Updated August 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Muse Spark

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.

Long documents
Prompts that approach the documented context limit
Qwen3.8 Max
Qwen3.8 Max has the larger documented context window.
Confidence: documented

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
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.

13 Muse Spark only

11 Shared

41 Qwen3.8 Max only

Shared results: 11
Muse Spark only: 13
Qwen3.8 Max only: 41
Like-for-like categories: 1 / 8

2 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.

Multimodal

Like-for-like

Muse Spark: 82.5
Qwen3.8 Max: 86.3
Weighted basis: 2 vs 2 rows
Reading: Qwen3.8 Max leads

Coding

Directional only

Muse Spark: 67.8
Qwen3.8 Max: 67.7
Weighted basis: 2 vs 1 rows
Reading: Directional only

Knowledge

Directional only

Muse Spark: 50.4
Qwen3.8 Max: 50.2
Weighted basis: 1 vs 2 rows
Reading: Directional only

Agentic

Not comparable

Muse Spark: 59.0
Qwen3.8 Max: 86.1
Weighted basis: 1 vs 1 rows
Reading: Not comparable

Reasoning

Not comparable

Muse Spark: 42.5
Qwen3.8 Max: 78.3
Weighted basis: 1 vs 2 rows
Reading: Not comparable

Math

Not comparable

Muse Spark: 32.9
Qwen3.8 Max: Not measured
Weighted basis: 2 vs 0 rows
Reading: Not comparable

Multilingual

Not comparable

Muse Spark: Not measured
Qwen3.8 Max: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Instruction following

Not comparable

Muse Spark: Not measured
Qwen3.8 Max: 82.8
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Muse Spark and Qwen3.8 Max
Category	Muse Spark	Qwen3.8 Max	Weighted basis	Reading
Multimodal	82.5	86.3	Like-for-like2 vs 2 rows	Qwen3.8 Max leads
Coding	67.8	67.7	Directional only2 vs 1 rows	Directional only
Knowledge	50.4	50.2	Directional only1 vs 2 rows	Directional only
Agentic	59.0	86.1	Not comparable1 vs 1 rows	Not comparable
Reasoning	42.5	78.3	Not comparable1 vs 2 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	82.8	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.

SWE-bench Pro
Coding
Muse Spark: 52.4%Qwen3.8 Max: 67.7%Normalized gap 15.3Muse Spark source Qwen3.8 Max source
CharXiv
Multimodal
Muse Spark: 86.4%Qwen3.8 Max: 93.5%Normalized gap 7.1Muse Spark source Qwen3.8 Max source
HLE
Knowledge
Muse Spark: 50.4%Qwen3.8 Max: 43.6%Normalized gap 6.8Muse Spark source Qwen3.8 Max source
MMMU-Pro
Multimodal
Muse Spark: 80.4%Qwen3.8 Max: 82.3%Normalized gap 1.9Muse Spark source Qwen3.8 Max source

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 Max: API rate not published; Fits in one request

Muse Spark has no comparable published API token rate. Qwen3.8 Max 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 Max: API rate not published; Fits in one request

Muse Spark has no comparable published API token rate. Qwen3.8 Max 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 Max: API rate not published; Fits in one request; Cached-input rate unavailable

Muse Spark has no comparable published API token rate. Qwen3.8 Max 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 Max

Context window

Maximum documented context; output-token limits may be lower.

Muse Spark

262K

Qwen3.8 Max

Alibaba Cloud Model Studio pricing

API model ID

Muse Spark

Not sourced

Qwen3.8 Max

qwen3.8-max

Alibaba Cloud Model Studio pricing

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 Max

No comparable hosted API rate

Alibaba Cloud Model Studio pricing

Documented inputs

Muse Spark

Not sourced

Qwen3.8 Max

Not sourced

Documented outputs

Muse Spark

Not sourced

Qwen3.8 Max

Not sourced

Provider availability

Muse Spark

Not sourced

Qwen3.8 Max

Not sourced

Reasoning profile

Muse Spark

Reasoning

Qwen3.8 Max

Reasoning

Weight access

Muse Spark

Proprietary

Qwen3.8 Max

Proprietary

License

Muse Spark

Proprietary

Qwen3.8 Max

Proprietary

Release date

Muse Spark

2026-04-08

Qwen3.8 Max

2026-08-03

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: Muse Spark has the higher public score estimate, 70.36 versus 65.4, but the 90% score intervals overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Qwen3.8 Max has the larger documented window (1M).

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 evidence65 rows

Agentic

Terminal-Bench 2.0
Muse Spark59%
Source
Qwen3.8 Max—
Not directly comparable
τ²-bench results
Muse Spark91.5%
Source
Qwen3.8 Max—
Not directly comparable
DeepSearchQA
Muse Spark74.8%
Source
Qwen3.8 Max—
Not directly comparable
CyberGym
Muse Spark43.5%
Source
Qwen3.8 Max—
Not directly comparable
Claw-Eval
Muse Spark63.8%
Source
Qwen3.8 Max—
Not directly comparable
Terminal-Bench 2.1
Muse Spark—
Qwen3.8 Max86.6%
Source
Not directly comparable
CoWorkBench
Muse Spark—
Qwen3.8 Max74.8%
Source
Not directly comparable
JobBench
Muse Spark—
Qwen3.8 Max53.4%
Source
Not directly comparable
skillsBench
Muse Spark—
Qwen3.8 Max70.2%
Source
Not directly comparable
Agents' Last Exam
Muse Spark—
Qwen3.8 Max52.4%
Source
Not directly comparable
AutomationBench
Muse Spark—
Qwen3.8 Max27.3%
Source
Not directly comparable
Toolathlon-Verified
Muse Spark—
Qwen3.8 Max72.5%
Source
Not directly comparable
WideResearch
Muse Spark—
Qwen3.8 Max81.9%
Source
Not directly comparable
HLE w/ tools
Muse Spark—
Qwen3.8 Max56.2%
Source
Not directly comparable
OSWorld-Verified
Muse Spark—
Qwen3.8 Max86.1%
Source
Not directly comparable
OSWorld 2.0
Muse Spark—
Qwen3.8 Max19.4%
Source
Not directly comparable
WebArena-Verified
Muse Spark—
Qwen3.8 Max66.8%
Source
Not directly comparable
AndroidWorld
Muse Spark—
Qwen3.8 Max85.3%
Source
Not directly comparable
MobileWorld
Muse Spark—
Qwen3.8 Max77.8%
Source
Not directly comparable

Coding

SWE-bench Verified
Muse Spark77.4%
Source
Qwen3.8 Max—
Not directly comparable
SWE-bench Pro
Muse Spark52.4%
Source
Qwen3.8 Max67.7%
Source
Qwen3.8 Max leads this result
LiveCodeBench Pro
Muse Spark80.0%
Source
Qwen3.8 Max—
Not directly comparable
Vibe Code Bench
Muse Spark19.67%
Source
Qwen3.8 Max—
Not directly comparable
Terminal-Bench 2.1
Muse Spark—
Qwen3.8 Max86.6%
Source
Not directly comparable
deepSwe
Muse Spark—
Qwen3.8 Max56.6%
Source
Not directly comparable
NL2Repo
Muse Spark—
Qwen3.8 Max55.9%
Source
Not directly comparable
FrontierSWE
Muse Spark—
Qwen3.8 Max73.5%
Source
Not directly comparable
MLS-Bench Lite
Muse Spark—
Qwen3.8 Max41.0%
Source
Not directly comparable
PaperBench
Muse Spark—
Qwen3.8 Max93.0%
Source
Not directly comparable

Reasoning

ARC-AGI-2
Muse Spark42.5%
Source
Qwen3.8 Max—
Not directly comparable
MRCRv2
Muse Spark—
Qwen3.8 Max92.9%
Source
Not directly comparable
LongBench v2
Muse Spark—
Qwen3.8 Max66.3%
Source
Not directly comparable

Knowledge

GPQA-D
Muse Spark89.5%
Source
Qwen3.8 Max92.6%
Source
Qwen3.8 Max leads this result
HLE
Muse Spark50.4%
Source
Qwen3.8 Max43.6%
Source
Muse Spark leads this result
HLE w/o tools
Muse Spark42.8%
Source
Qwen3.8 Max43.6%
Source
Qwen3.8 Max leads this result
HealthBench Hard
Muse Spark42.8%
Source
Qwen3.8 Max—
Not directly comparable
MedXpertQA (Text)
Muse Spark52.6%
Source
Qwen3.8 Max—
Not directly comparable
GPQA
Muse Spark—
Qwen3.8 Max92.6%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Muse Spark39.000%
Source
Qwen3.8 Max—
Not directly comparable
FrontierMath v2 (Tier 4)
Muse Spark14.600%
Source
Qwen3.8 Max—
Not directly comparable

Multimodal

CharXiv
Muse Spark86.4%
Source
Qwen3.8 Max93.5%
Source
Qwen3.8 Max leads this result
MMMU-Pro
Muse Spark80.4%
Source
Qwen3.8 Max82.3%
Source
Qwen3.8 Max leads this result
ERQA
Muse Spark64.7%
Source
Qwen3.8 Max77.8%
Source
Qwen3.8 Max leads this result
SimpleVQA
Muse Spark71.3%
Source
Qwen3.8 Max75.0%
Source
Qwen3.8 Max leads this result
ScreenSpot Pro
Muse Spark84.1%
Source
Qwen3.8 Max84.5%
Source
Qwen3.8 Max leads this result
ZeroBench
Muse Spark33.0%
Source
Qwen3.8 Max24.0%
Source
Muse Spark leads this result
MedXpertQA (MM)
Muse Spark78.4%
Source
Qwen3.8 Max80.4%
Source
Qwen3.8 Max leads this result
MathVision
Muse Spark—
Qwen3.8 Max95.2%
Source
Not directly comparable
MathVision w/ Python
Muse Spark—
Qwen3.8 Max97.7%
Source
Not directly comparable
BabyVision
Muse Spark—
Qwen3.8 Max82.0%
Source
Not directly comparable
BabyVision w/ Python
Muse Spark—
Qwen3.8 Max91.3%
Source
Not directly comparable
ZeroBench w/ Python
Muse Spark—
Qwen3.8 Max49.0%
Source
Not directly comparable
Vision2Web
Muse Spark—
Qwen3.8 Max69.0%
Source
Not directly comparable
CharXiv w/o tools
Muse Spark—
Qwen3.8 Max88.4%
Source
Not directly comparable
OmniDocBench 1.5
Muse Spark—
Qwen3.8 Max92.1%
Source
Not directly comparable
OCRBench V2
Muse Spark—
Qwen3.8 Max74.2%
Source
Not directly comparable
CC-OCR
Muse Spark—
Qwen3.8 Max79.6%
Source
Not directly comparable
RealWorldQA
Muse Spark—
Qwen3.8 Max88.0%
Source
Not directly comparable
PerceptionBench
Muse Spark—
Qwen3.8 Max63.5%
Source
Not directly comparable
Video-MME (with subtitle)
Muse Spark—
Qwen3.8 Max90.4%
Source
Not directly comparable
VideoMMMU
Muse Spark—
Qwen3.8 Max88.7%
Source
Not directly comparable
MMVU
Muse Spark—
Qwen3.8 Max82.4%
Source
Not directly comparable
MLVU (M-Avg)
Muse Spark—
Qwen3.8 Max90.8%
Source
Not directly comparable
LVBench
Muse Spark—
Qwen3.8 Max81.8%
Source
Not directly comparable

Instruction following

IFBench
Muse Spark—
Qwen3.8 Max82.8%
Source
Not directly comparable

Frequently asked questions

Which is better, Muse Spark or Qwen3.8 Max?

Muse Spark has the higher public score estimate, 70.36 versus 65.4, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Muse Spark or Qwen3.8 Max?

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 Max?

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 Max?

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 Max?

Qwen3.8 Max has the larger documented context window: 1M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 3, 2026

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Muse Spark vs Qwen3.8 Max

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Multimodal

Coding

Knowledge

Agentic

Reasoning

Math

Multilingual

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multimodal

Instruction following

Frequently asked questions

Which is better, Muse Spark or Qwen3.8 Max?

Which is better for coding, Muse Spark or Qwen3.8 Max?

Which is better for agentic tasks, Muse Spark or Qwen3.8 Max?

Which costs less, Muse Spark or Qwen3.8 Max?

Which has the larger context window, Muse Spark or Qwen3.8 Max?

Related comparisons

Watch Muse Spark vs Qwen3.8 Max