Muse Spark Open vs Qwen3.7 Plus

Updated October 15, 2026. Rank says Muse Spark Open is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Muse Spark Open has the higher public point estimate, 62.66 versus 53.79. Their conditional score ranges overlap. These ranges do not establish rank confidence. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Muse Spark Open

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
Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Muse Spark Open is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

56.1Muse Spark Open40.5Qwen3.7 Plus

Directional only · BenchAlign v5.8

Muse Spark Open has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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

Directional only

Muse Spark Open: 60.2; Estimated · #27/127
Qwen3.7 Plus: 35.3; Supported · #80/127
Basis: BenchAlign v5.8 lane · 4 vs 11 public rows
Reading: Directional only

Coding

Directional only

Muse Spark Open: 56.1; Supported · #29/150
Qwen3.7 Plus: 40.5; Estimated · #64/150
Basis: BenchAlign v5.8 lane · 0 vs 7 public rows
Reading: Directional only

Knowledge

Directional only

Muse Spark Open: 64.6; Supported · #38/184
Qwen3.7 Plus: 53.5; Estimated · #65/184
Basis: BenchAlign v5.8 lane · 0 vs 7 public rows
Reading: Directional only

Reasoning

Not comparable

Muse Spark Open: 79.6; Unranked · 2 rankable rows
Qwen3.7 Plus: 80.9; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Muse Spark Open: 83.6; Unranked · 4 rankable rows
Qwen3.7 Plus: 82.0; #16/54
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Muse Spark Open: Not ranked
Qwen3.7 Plus: 95.7; #3/17
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Muse Spark Open: Not ranked
Qwen3.7 Plus: 92.8; #17/146
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Muse Spark Open: Not ranked
Qwen3.7 Plus: 64.3; Unranked · 4 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Muse Spark Open and Qwen3.7 Plus
Category	Muse Spark Open	Qwen3.7 Plus	Basis	Reading
Agentic	60.2Estimated · #27/127	35.3Supported · #80/127	Directional onlyBenchAlign v5.8 lane · 4 vs 11 public rows	Directional only
Coding	56.1Supported · #29/150	40.5Estimated · #64/150	Directional onlyBenchAlign v5.8 lane · 0 vs 7 public rows	Directional only
Knowledge	64.6Supported · #38/184	53.5Estimated · #65/184	Directional onlyBenchAlign v5.8 lane · 0 vs 7 public rows	Directional only
Reasoning	79.6Unranked · 2 rankable rows	80.9Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	83.6Unranked · 4 rankable rows	82.0#16/54	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Multilingual	Not ranked	95.7#3/17	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Instruction following	Not ranked	92.8#17/146	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	64.3Unranked · 4 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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 Open: API rate not published; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Muse Spark Open 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 Open: API rate not published; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

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

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationMuse Spark OpenQwen3.7 Plus

Context window

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

Muse Spark Open

Meta Muse Spark Open model card

Qwen3.7 Plus

API model ID

Muse Spark Open

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 Open

No comparable hosted API rate

Meta AI Research blog

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

Muse Spark Open

text, image, video, audio

Meta Muse Spark Open model card

Qwen3.7 Plus

Not sourced

Documented outputs

Muse Spark Open

text

Meta Muse Spark Open model card

Qwen3.7 Plus

Not sourced

Provider availability

Muse Spark Open

Open Weights · Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, Microsoft Foundry Models, self-hosted inference

Meta AI Research: Muse Spark Open

Qwen3.7 Plus

Not sourced

Reasoning profile

Muse Spark Open

Reasoning

Qwen3.7 Plus

Reasoning

Weight access

Muse Spark Open

Open Weight

Qwen3.7 Plus

Proprietary

License

Muse Spark Open

Open Weight

Qwen3.7 Plus

Proprietary

Release date

Muse Spark Open

2026-10-15

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 Open has the higher public point estimate, 62.66 versus 53.79. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Questions

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

Muse Spark Open has the higher public point estimate, 62.66 versus 53.79. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

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

Muse Spark Open scores higher for coding on the public lane, 56.1 to 40.5. 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 Open or Qwen3.7 Plus?

Muse Spark Open scores higher for agentic tasks on the public lane, 60.2 to 35.3. Muse Spark Open is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

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

Both models list the same context window, 1M.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence58 rows

Agentic

JobBench
Muse Spark Open61.8%
Source
Qwen3.7 Plus—
Not directly comparable
MCP Atlas
Muse Spark Open89.2%
Source
Qwen3.7 Plus73.2%
Source
Muse Spark Open leads this result
HLE w/ tools
Muse Spark Open61.0%
Source
Qwen3.7 Plus—
Not directly comparable
Toolathlon-Verified
Muse Spark Open72.8%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
Muse Spark Open—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
Muse Spark Open—
Qwen3.7 Plus61.8%
Source
Not directly comparable
Claw-Eval
Muse Spark Open—
Qwen3.7 Plus62.7%
Source
Not directly comparable
BFCL v4
Muse Spark Open—
Qwen3.7 Plus72.9%
Source
Not directly comparable
VITA-Bench
Muse Spark Open—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
Muse Spark Open—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
Muse Spark Open—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
Muse Spark Open—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
Muse Spark Open—
Qwen3.7 Plus2.8%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Muse Spark Open—
Qwen3.7 Plus52.8%
Source
Not directly comparable

Coding

Terminal-Bench 2.0
Muse Spark Open—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE-bench Verified
Muse Spark Open—
Qwen3.7 Plus77.7%
Source
Not directly comparable
SWE-bench Pro
Muse Spark Open—
Qwen3.7 Plus57.6%
Source
Not directly comparable
SWE Multilingual
Muse Spark Open—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
Muse Spark Open—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
Muse Spark Open—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench v6
Muse Spark Open—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

CritPt
Muse Spark Open—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
Muse Spark Open—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Multimodal

ZeroBench
Muse Spark Open50.0%
Source
Qwen3.7 Plus—
Not directly comparable
BabyVision
Muse Spark Open80.2%
Source
Qwen3.7 Plus—
Not directly comparable
SimpleVQA
Muse Spark Open73.6%
Source
Qwen3.7 Plus81.7%
Source
Qwen3.7 Plus leads this result
MMMU-Pro
Muse Spark Open—
Qwen3.7 Plus79%
Source
Not directly comparable
MathVision
Muse Spark Open—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
Muse Spark Open—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
Muse Spark Open—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
Muse Spark Open—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
Muse Spark Open—
Qwen3.7 Plus79.0%
Source
Not directly comparable
MMSearch-Plus
Muse Spark Open—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
Muse Spark Open—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
Muse Spark Open—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
Muse Spark Open—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
Muse Spark Open—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
Muse Spark Open—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
Muse Spark Open—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
Muse Spark Open—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Knowledge

GPQA
Muse Spark Open—
Qwen3.7 Plus90.3%
Source
Not directly comparable
GPQA-D
Muse Spark Open—
Qwen3.7 Plus90.3%
Source
Not directly comparable
HLE
Muse Spark Open—
Qwen3.7 Plus34.7%
Source
Not directly comparable
MMLU-Pro
Muse Spark Open—
Qwen3.7 Plus88.5%
Source
Not directly comparable
MMLU-Redux
Muse Spark Open—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
Muse Spark Open—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
Muse Spark Open—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Multilingual

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

Instruction following

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

Math

HMMT Feb 2026
Muse Spark Open—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
Muse Spark Open—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
Muse Spark Open—
Qwen3.7 Plus22.7%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Muse Spark Open—
Qwen3.7 Plus34.386%
Source
Not directly comparable

58 public results · 2 shared

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Last updated October 15, 2026

Muse Spark Open vs Qwen3.7 Plus

Decision reading

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Knowledge

Reasoning

Multimodal

Multilingual

Instruction following

Math

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

If you already use one of these models

Questions

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

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

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

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

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

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch Muse Spark Open vs Qwen3.7 Plus