Muse Spark 1.2 vs Qwen3.7 Plus

Decision reading

Muse Spark 1.2 has the higher public score estimate, 70.28 versus 61.6, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 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 1.2

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 1.2
Muse Spark 1.2 leads on the public agentic lane, 61 to 36.7, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger

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
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.

60.0Muse Spark 1.252.6Qwen3.7 Plus

Directional only · BenchAlign

Muse Spark 1.2 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.

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

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

7 Muse Spark 1.2 only

1 Shared

51 Qwen3.7 Plus only

Shared results: 1
Muse Spark 1.2 only: 7
Qwen3.7 Plus only: 51
Like-for-like categories: 1 / 8

2 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 1.2: 61.0; Supported · #16/154
Qwen3.7 Plus: 36.7; Supported · #133/154
Basis: BenchAlign lane · 2 vs 11 public rows
Reading: Muse Spark 1.2 leads

Coding

Directional only

Muse Spark 1.2: 60.0; Supported · #21/154
Qwen3.7 Plus: 52.6; Estimated · #48/154
Basis: BenchAlign lane · 5 vs 7 public rows
Reading: Directional only

Knowledge

Directional only

Muse Spark 1.2: 70.7; Estimated · #10/184
Qwen3.7 Plus: 56.2; Estimated · #49/184
Basis: BenchAlign lane · 1 vs 7 public rows
Reading: Directional only

Reasoning

Not comparable

Muse Spark 1.2: 75.3; Unranked · 2 rankable rows
Qwen3.7 Plus: 74.0; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Muse Spark 1.2: Not ranked
Qwen3.7 Plus: 78.2; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Muse Spark 1.2: Not ranked
Qwen3.7 Plus: 78.9; #3/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Muse Spark 1.2: Not ranked
Qwen3.7 Plus: 72.4; #18/48
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Muse Spark 1.2: Not ranked
Qwen3.7 Plus: 89.2; #18/124
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Muse Spark 1.2 and Qwen3.7 Plus
Category	Muse Spark 1.2	Qwen3.7 Plus	Basis	Reading
Agentic	61.0Supported · #16/154	36.7Supported · #133/154	Like-for-likeBenchAlign lane · 2 vs 11 public rows	Muse Spark 1.2 leads
Coding	60.0Supported · #21/154	52.6Estimated · #48/154	Directional onlyBenchAlign lane · 5 vs 7 public rows	Directional only
Knowledge	70.7Estimated · #10/184	56.2Estimated · #49/184	Directional onlyBenchAlign lane · 1 vs 7 public rows	Directional only
Reasoning	75.3Unranked · 2 rankable rows	74.0Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	78.2Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	78.9#3/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	Not ranked	72.4#18/48	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Instruction following	Not ranked	89.2#18/124	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.

A shared-evidence shape is not available.

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

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 1.2: $0.00338; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Qwen3.7 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Muse Spark 1.2: $0.07525; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Qwen3.7 Plus has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Muse Spark 1.2: $0.0975; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

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 Spark 1.2Qwen3.7 Plus

Context window

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

Muse Spark 1.2

Meta: Muse Spark 1.2 model page

Qwen3.7 Plus

API model ID

Muse Spark 1.2

muse-spark-1.2

Meta: Muse Spark 1.2 model page

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 1.2

$0.15 per 1M cached input tokens

Meta: Muse Spark 1.2 model page

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

Muse Spark 1.2

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

Muse Spark 1.2

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

Muse Spark 1.2

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

Muse Spark 1.2

Reasoning

Qwen3.7 Plus

Reasoning

Weight access

Muse Spark 1.2

Proprietary

Qwen3.7 Plus

Proprietary

License

Muse Spark 1.2

Proprietary

Qwen3.7 Plus

Proprietary

Release date

Muse Spark 1.2

2026-08-05

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 1.2 has the higher public score estimate, 70.28 versus 61.6, but the 90% score intervals overlap.
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.

Benchmark evidence

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

Browse raw public benchmark evidence59 rows

Agentic

Terminal-Bench 2.1
Muse Spark 1.282.9%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Muse Spark 1.269.7%
Source
Qwen3.7 Plus52.8%
Source
Muse Spark 1.2 leads this result
Terminal-Bench 2.0
Muse Spark 1.2—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
Muse Spark 1.2—
Qwen3.7 Plus61.8%
Source
Not directly comparable
Claw-Eval
Muse Spark 1.2—
Qwen3.7 Plus62.7%
Source
Not directly comparable
BFCL v4
Muse Spark 1.2—
Qwen3.7 Plus72.9%
Source
Not directly comparable
MCP Atlas
Muse Spark 1.2—
Qwen3.7 Plus73.2%
Source
Not directly comparable
VITA-Bench
Muse Spark 1.2—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
Muse Spark 1.2—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
Muse Spark 1.2—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
Muse Spark 1.2—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
Muse Spark 1.2—
Qwen3.7 Plus2.8%
Source
Not directly comparable

Coding

Terminal-Bench 2.1
Muse Spark 1.282.9%
Source
Qwen3.7 Plus—
Not directly comparable
DeepSWE
Muse Spark 1.259.3%
Source
Qwen3.7 Plus—
Not directly comparable
VulcanBench v3
Muse Spark 1.287.0%
Source
Qwen3.7 Plus—
Not directly comparable
FrontierSWE v2
Muse Spark 1.212.0%
Source
Qwen3.7 Plus—
Not directly comparable
SWE-bench (Vals)
Muse Spark 1.286.6%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
Muse Spark 1.2—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE-bench Verified
Muse Spark 1.2—
Qwen3.7 Plus77.7%
Source
Not directly comparable
SWE-bench Pro
Muse Spark 1.2—
Qwen3.7 Plus57.6%
Source
Not directly comparable
SWE Multilingual
Muse Spark 1.2—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
Muse Spark 1.2—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
Muse Spark 1.2—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench
Muse Spark 1.2—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

CritPt
Muse Spark 1.2—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
Muse Spark 1.2—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Knowledge

MMLU-Pro (Vals)
Muse Spark 1.288.3%
Source
Qwen3.7 Plus—
Not directly comparable
GPQA
Muse Spark 1.2—
Qwen3.7 Plus90.3%
Source
Not directly comparable
GPQA-D
Muse Spark 1.2—
Qwen3.7 Plus90.3%
Source
Not directly comparable
HLE
Muse Spark 1.2—
Qwen3.7 Plus34.7%
Source
Not directly comparable
MMLU-Pro
Muse Spark 1.2—
Qwen3.7 Plus88.5%
Source
Not directly comparable
MMLU-Redux
Muse Spark 1.2—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
Muse Spark 1.2—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
Muse Spark 1.2—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Math

HMMT Feb 2026
Muse Spark 1.2—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
Muse Spark 1.2—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
Muse Spark 1.2—
Qwen3.7 Plus22.7%
Source
Not directly comparable

Multilingual

MMLU-ProX
Muse Spark 1.2—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
Muse Spark 1.2—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
Muse Spark 1.2—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
Muse Spark 1.2—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
Muse Spark 1.2—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Multimodal

MMMU-Pro
Muse Spark 1.2—
Qwen3.7 Plus79%
Source
Not directly comparable
MathVision
Muse Spark 1.2—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
Muse Spark 1.2—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
Muse Spark 1.2—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
Muse Spark 1.2—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
Muse Spark 1.2—
Qwen3.7 Plus79.0%
Source
Not directly comparable
SimpleVQA
Muse Spark 1.2—
Qwen3.7 Plus81.7%
Source
Not directly comparable
MMSearch-Plus
Muse Spark 1.2—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
Muse Spark 1.2—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
Muse Spark 1.2—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
Muse Spark 1.2—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
Muse Spark 1.2—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
Muse Spark 1.2—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
Muse Spark 1.2—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
Muse Spark 1.2—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Instruction following

IFEval
Muse Spark 1.2—
Qwen3.7 Plus94.6%
Source
Not directly comparable
IFBench
Muse Spark 1.2—
Qwen3.7 Plus79.1%
Source
Not directly comparable

Questions

Which is better, Muse Spark 1.2 or Qwen3.7 Plus?

Muse Spark 1.2 has the higher public score estimate, 70.28 versus 61.6, 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 1.2 or Qwen3.7 Plus?

Muse Spark 1.2 scores higher for coding on the public lane, 60 to 52.6. 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 1.2 or Qwen3.7 Plus?

Muse Spark 1.2 leads the public agentic tasks lane, 61 to 36.7, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Muse Spark 1.2 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 1.2 or Qwen3.7 Plus?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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Muse Spark 1.2 vs Qwen3.7 Plus

Which one for your work

Agentic work

Coding work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Knowledge

Reasoning

Math

Multilingual

Multimodal

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

Multilingual

Multimodal

Instruction following

Questions

Which is better, Muse Spark 1.2 or Qwen3.7 Plus?

Which is better for coding, Muse Spark 1.2 or Qwen3.7 Plus?

Which is better for agentic tasks, Muse Spark 1.2 or Qwen3.7 Plus?

Which costs less, Muse Spark 1.2 or Qwen3.7 Plus?

Which has the larger context window, Muse Spark 1.2 or Qwen3.7 Plus?

Related comparisons

Watch Muse Spark 1.2 vs Qwen3.7 Plus