Model A

Muse Spark vs Qwen3.7 Plus

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Qwen3.7 Plus

Alibaba

62.29/100

Supported · Public rank #60

90% interval 52.4–72.2

Decision reading

Muse Spark has the higher public score estimate, 68.39 versus 62.29, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

12 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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.

Agentic work
Tool use, computer use, and multi-step task completion
Muse Spark
Muse Spark leads on the public agentic lane, 58.8 to 37.7, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Qwen3.7 Plus
Qwen3.7 Plus 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
Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
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.

12 Muse Spark only

12 Shared

40 Qwen3.7 Plus only

Shared results: 12
Muse Spark only: 12
Qwen3.7 Plus only: 40
Like-for-like categories: 2 / 8

3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like

Muse Spark: 58.8; Supported · #31/151
Qwen3.7 Plus: 37.7; Supported · #126/151
Basis: BenchAlign lane · 5 vs 11 public rows
Reading: Muse Spark leads

Multimodal

Like-for-like

Muse Spark: 77.5; #14/48
Qwen3.7 Plus: 72.5; #18/48
Basis: Provisional lane · 2 vs 2 weighted rows
Reading: Muse Spark leads

Coding

Directional only

Muse Spark: 59.2; Supported · #28/183
Qwen3.7 Plus: 53.1; Estimated · #51/183
Basis: BenchAlign lane · 4 vs 7 public rows
Reading: Directional only

Knowledge

Directional only

Muse Spark: 65.7; Supported · #23/181
Qwen3.7 Plus: 56.8; Estimated · #50/181
Basis: BenchAlign lane · 5 vs 7 public rows
Reading: Directional only

Instruction following

Directional only

Muse Spark: 92.9; #8/120
Qwen3.7 Plus: 91.1; #17/120
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Reasoning

Not comparable

Muse Spark: 45.9; Unranked · 3 rankable rows
Qwen3.7 Plus: 73.7; Unranked · 3 rankable rows
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Muse Spark: 55.3; Unranked · 2 rankable rows
Qwen3.7 Plus: 78.3; Unranked · 3 rankable rows
Basis: Provisional lane · 2 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Muse Spark: Not ranked
Qwen3.7 Plus: 78.9; #3/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Muse Spark and Qwen3.7 Plus
Category	Muse Spark	Qwen3.7 Plus	Basis	Reading
Agentic	58.8Supported · #31/151	37.7Supported · #126/151	Like-for-likeBenchAlign lane · 5 vs 11 public rows	Muse Spark leads
Multimodal	77.5#14/48	72.5#18/48	Like-for-likeProvisional lane · 2 vs 2 weighted rows	Muse Spark leads
Coding	59.2Supported · #28/183	53.1Estimated · #51/183	Directional onlyBenchAlign lane · 4 vs 7 public rows	Directional only
Knowledge	65.7Supported · #23/181	56.8Estimated · #50/181	Directional onlyBenchAlign lane · 5 vs 7 public rows	Directional only
Instruction following	92.9#8/120	91.1#17/120	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Reasoning	45.9Unranked · 3 rankable rows	73.7Unranked · 3 rankable rows	Not comparableProvisional lane · 1 vs 1 weighted rows	Not comparable
Math	55.3Unranked · 2 rankable rows	78.3Unranked · 3 rankable rows	Not comparableProvisional lane · 2 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	78.9#3/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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
Muse Spark: 50.4%Qwen3.7 Plus: 34.7%Normalized gap 15.7Muse Spark source Qwen3.7 Plus source
Terminal-Bench 2.0
Agentic
Muse Spark: 59%Qwen3.7 Plus: 70.3%Normalized gap 11.3Muse Spark source Qwen3.7 Plus source
SWE-bench Pro
Coding
Muse Spark: 52.4%Qwen3.7 Plus: 57.6%Normalized gap 5.2Muse Spark source Qwen3.7 Plus source
MMMU-Pro
Multimodal
Muse Spark: 80.4%Qwen3.7 Plus: 79%Normalized gap 1.4Muse Spark source Qwen3.7 Plus source
CharXiv
Multimodal
Muse Spark: 86.4%Qwen3.7 Plus: 85.9%Normalized gap 0.5Muse Spark source Qwen3.7 Plus 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
Qwen3.7 Plus: API rate not published; Fits in one request

Muse Spark has no comparable published API token rate. Qwen3.7 Plus 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
Qwen3.7 Plus: API rate not published; Fits in one request

Muse Spark has no comparable published API token rate. Qwen3.7 Plus 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
Qwen3.7 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Muse Spark has no comparable published API token rate. Qwen3.7 Plus 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 SparkQwen3.7 Plus

Context window

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

Muse Spark

262K

Qwen3.7 Plus

API model ID

Muse Spark

Not sourced

Qwen3.7 Plus

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

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

Muse Spark

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

Muse Spark

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

Muse Spark

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

Muse Spark

Reasoning

Qwen3.7 Plus

Reasoning

Weight access

Muse Spark

Proprietary

Qwen3.7 Plus

Proprietary

License

Muse Spark

Proprietary

Qwen3.7 Plus

Proprietary

Release date

Muse Spark

2026-04-08

Qwen3.7 Plus

2026-06-03

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, 68.39 versus 62.29, but the 90% score intervals overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Qwen3.7 Plus 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 evidence64 rows

Agentic

Terminal-Bench 2.0
Muse Spark59%
Source
Qwen3.7 Plus70.3%
Source
Qwen3.7 Plus leads this result
τ²-bench results
Muse Spark91.5%
Source
Qwen3.7 Plus—
Not directly comparable
DeepSearchQA
Muse Spark74.8%
Source
Qwen3.7 Plus—
Not directly comparable
CyberGym
Muse Spark43.5%
Source
Qwen3.7 Plus—
Not directly comparable
Claw-Eval
Muse Spark63.8%
Source
Qwen3.7 Plus62.7%
Source
Muse Spark leads this result
QwenClawBench
Muse Spark—
Qwen3.7 Plus61.8%
Source
Not directly comparable
BFCL v4
Muse Spark—
Qwen3.7 Plus72.9%
Source
Not directly comparable
MCP Atlas
Muse Spark—
Qwen3.7 Plus73.2%
Source
Not directly comparable
VITA-Bench
Muse Spark—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
Muse Spark—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
Muse Spark—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
Muse Spark—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
Muse Spark—
Qwen3.7 Plus2.8%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Muse Spark—
Qwen3.7 Plus52.8%
Source
Not directly comparable

Coding

SWE-bench Verified
Muse Spark77.4%
Source
Qwen3.7 Plus77.7%
Source
Qwen3.7 Plus leads this result
SWE-bench Pro
Muse Spark52.4%
Source
Qwen3.7 Plus57.6%
Source
Qwen3.7 Plus leads this result
LiveCodeBench Pro
Muse Spark80.0%
Source
Qwen3.7 Plus—
Not directly comparable
Vibe Code Bench
Muse Spark19.67%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
Muse Spark—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE Multilingual
Muse Spark—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
Muse Spark—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
Muse Spark—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench
Muse Spark—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

ARC-AGI-2
Muse Spark42.5%
Source
Qwen3.7 Plus—
Not directly comparable
CritPt
Muse Spark—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
Muse Spark—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Knowledge

GPQA-D
Muse Spark89.5%
Source
Qwen3.7 Plus90.3%
Source
Qwen3.7 Plus leads this result
HLE
Muse Spark50.4%
Source
Qwen3.7 Plus34.7%
Source
Muse Spark leads this result
HLE w/o tools
Muse Spark42.8%
Source
Qwen3.7 Plus—
Not directly comparable
HealthBench Hard
Muse Spark42.8%
Source
Qwen3.7 Plus—
Not directly comparable
MedXpertQA (Text)
Muse Spark52.6%
Source
Qwen3.7 Plus—
Not directly comparable
GPQA
Muse Spark—
Qwen3.7 Plus90.3%
Source
Not directly comparable
MMLU-Pro
Muse Spark—
Qwen3.7 Plus88.5%
Source
Not directly comparable
MMLU-Redux
Muse Spark—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
Muse Spark—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
Muse Spark—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Muse Spark39.000%
Source
Qwen3.7 Plus—
Not directly comparable
FrontierMath v2 (Tier 4)
Muse Spark14.600%
Source
Qwen3.7 Plus—
Not directly comparable
HMMT Feb 2026
Muse Spark—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
Muse Spark—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
Muse Spark—
Qwen3.7 Plus22.7%
Source
Not directly comparable

Multilingual

MMLU-ProX
Muse Spark—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
Muse Spark—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
Muse Spark—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
Muse Spark—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
Muse Spark—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Multimodal

CharXiv
Muse Spark86.4%
Source
Qwen3.7 Plus85.9%
Source
Muse Spark leads this result
MMMU-Pro
Muse Spark80.4%
Source
Qwen3.7 Plus79%
Source
Muse Spark leads this result
ERQA
Muse Spark64.7%
Source
Qwen3.7 Plus69.8%
Source
Qwen3.7 Plus leads this result
SimpleVQA
Muse Spark71.3%
Source
Qwen3.7 Plus81.7%
Source
Qwen3.7 Plus leads this result
ScreenSpot Pro
Muse Spark84.1%
Source
Qwen3.7 Plus79.0%
Source
Muse Spark leads this result
ZeroBench
Muse Spark33.0%
Source
Qwen3.7 Plus—
Not directly comparable
MedXpertQA (MM)
Muse Spark78.4%
Source
Qwen3.7 Plus71.0%
Source
Muse Spark leads this result
MathVision
Muse Spark—
Qwen3.7 Plus90.3%
Source
Not directly comparable
MMSearch-Plus
Muse Spark—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
Muse Spark—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
Muse Spark—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
Muse Spark—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
Muse Spark—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
Muse Spark—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
Muse Spark—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
Muse Spark—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Instruction following

IFEval
Muse Spark—
Qwen3.7 Plus94.6%
Source
Not directly comparable
IFBench
Muse Spark—
Qwen3.7 Plus79.1%
Source
Not directly comparable

Frequently asked questions

Which is better, Muse Spark or Qwen3.7 Plus?

Muse Spark has the higher public score estimate, 68.39 versus 62.29, 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 Qwen3.7 Plus?

Muse Spark scores higher for coding on the public lane, 59.2 to 53.1. Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Muse Spark or Qwen3.7 Plus?

Muse Spark leads the public agentic tasks lane, 58.8 to 37.7, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Muse Spark or Qwen3.7 Plus?

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 Qwen3.7 Plus?

Qwen3.7 Plus has the larger documented context window: 1M, compared with 262K.

Related comparisons

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Last updated September 4, 2026

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Muse Spark vs Qwen3.7 Plus

Which one for your work

Agentic work

Long documents

Coding work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Multimodal

Coding

Knowledge

Instruction following

Reasoning

Math

Multilingual

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

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Muse Spark or Qwen3.7 Plus?

Which is better for coding, Muse Spark or Qwen3.7 Plus?

Which is better for agentic tasks, Muse Spark or Qwen3.7 Plus?

Which costs less, Muse Spark or Qwen3.7 Plus?

Which has the larger context window, Muse Spark or Qwen3.7 Plus?

Related comparisons

Watch Muse Spark vs Qwen3.7 Plus