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BenchLM
Model A
Muse Spark 1.1

Meta

76.7/100

Supported · Public rank #7

90% interval 72.6–80.9

Muse Spark 1.1 vs Step 3.7 Flash

Updated August 22, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Step 3.7 Flash

StepFun

50.8/100

Estimated · Public rank #122

90% interval 39.2–62.3

Decision reading

Muse Spark 1.1 has the higher public score, 76.74 versus 50.76, and the 90% score intervals do not overlap.

5 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Muse Spark 1.1

    Muse Spark 1.1 leads on the same 1 weighted benchmark row.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Muse Spark 1.1

    Muse Spark 1.1 has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are 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: rate-fallback

  • 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.

Shared results
5
Muse Spark 1.1 only
16
Step 3.7 Flash only
6
Like-for-like categories
1 / 8

1 category uses 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.

Coding

Like-for-like
Muse Spark 1.1
61.5
Step 3.7 Flash
56.3
Weighted basis
1 vs 1 rows
Reading
Muse Spark 1.1 leads

Agentic

Directional only
Muse Spark 1.1
80.4
Step 3.7 Flash
66.4
Weighted basis
2 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Muse Spark 1.1
Not measured
Step 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Muse Spark 1.1
62.1
Step 3.7 Flash
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Muse Spark 1.1
Not measured
Step 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Muse Spark 1.1
Not measured
Step 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Muse Spark 1.1
88.4
Step 3.7 Flash
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Muse Spark 1.1
Not measured
Step 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
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.

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 1.1
API rate not published
Fits in one request
Step 3.7 Flash
$0.00077
Fits in one request

Muse Spark 1.1 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Muse Spark 1.1
API rate not published
Fits in one request
Step 3.7 Flash
$0.01345
Fits in one request

Muse Spark 1.1 has no comparable published API token rate.

Cache-heavy agent loop

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

Muse Spark 1.1
API rate not published
Fits in one request
Cached-input rate unavailable
Step 3.7 Flash
$0.0555
Fits in one request
Cached input priced at the published list-input rate

Step 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate. Muse Spark 1.1 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.

Context window

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

Muse Spark 1.1

1M

Step 3.7 Flash

256K

API model ID

Muse Spark 1.1

Not sourced

Step 3.7 Flash

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 1.1

No comparable hosted API rate

Step 3.7 Flash

Not published

Documented inputs

Muse Spark 1.1

Not sourced

Step 3.7 Flash

Not sourced

Documented outputs

Muse Spark 1.1

Not sourced

Step 3.7 Flash

Not sourced

Provider availability

Muse Spark 1.1

Not sourced

Step 3.7 Flash

Not sourced

Reasoning profile

Muse Spark 1.1

Reasoning

Step 3.7 Flash

Reasoning

Weight access

Muse Spark 1.1

Proprietary

Step 3.7 Flash

Open Weight

License

Muse Spark 1.1

Proprietary

Step 3.7 Flash

Open Weight

Release date

Muse Spark 1.1

2026-07-09

Step 3.7 Flash

2026-05-29

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 1.1 has the higher public score, 76.74 versus 50.76, and the 90% score intervals do not overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Muse Spark 1.1 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 evidence27 rows

Agentic

  • Terminal-Bench 2.0

    Muse Spark 1.180%
    Source
    Step 3.7 Flash59.5%
    Source

    Muse Spark 1.1 leads this result

  • MCP Atlas

    Muse Spark 1.188.1%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • Toolathlon

    Muse Spark 1.175.6%
    Source
    Step 3.7 Flash49.5%
    Source

    Muse Spark 1.1 leads this result

  • OSWorld-Verified

    Muse Spark 1.180.8%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • WebArena-Verified

    Muse Spark 1.169%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • DeepSearchQA

    Muse Spark 1.184.9%
    Source
    Step 3.7 Flash92.8%
    Source

    Step 3.7 Flash leads this result

  • CyberGym

    Muse Spark 1.159.0%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • Finance Agent v2

    Muse Spark 1.157.2%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • deepSwe

    Muse Spark 1.153.3%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • OSWorld 2.0

    Muse Spark 1.114.2%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • JobBench

    Muse Spark 1.154.7%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • Cybench

    Muse Spark 1.192.9%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • ExploitGym

    Muse Spark 1.10.8%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • BrowseComp

    Muse Spark 1.1—
    Step 3.7 Flash75.8%
    Source

    Not directly comparable

  • Claw-Eval

    Muse Spark 1.1—
    Step 3.7 Flash67.1%
    Source

    Not directly comparable

  • HLE w/ tools

    Muse Spark 1.1—
    Step 3.7 Flash47.2%
    Source

    Not directly comparable

  • Gert Labs

    Muse Spark 1.1—
    Step 3.7 Flash51.57%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Muse Spark 1.180.0%
    Source
    Step 3.7 Flash59.5%
    Source

    Muse Spark 1.1 leads this result

  • SWE-bench Pro

    Muse Spark 1.161.5%
    Source
    Step 3.7 Flash56.3%
    Source

    Muse Spark 1.1 leads this result

Reasoning

  • MRCR 1M

    Muse Spark 1.154.1%
    Source
    Step 3.7 Flash—

    Not directly comparable

Knowledge

  • HLE

    Muse Spark 1.162.1%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • HLE w/o tools

    Muse Spark 1.152.2%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • HealthBench Professional

    Muse Spark 1.159.3%
    Source
    Step 3.7 Flash—

    Not directly comparable

Multimodal

  • CharXiv

    Muse Spark 1.188.4%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • BabyVision

    Muse Spark 1.176.3%
    Source
    Step 3.7 Flash—

    Not directly comparable

  • SimpleVQA

    Muse Spark 1.1—
    Step 3.7 Flash79.2%
    Source

    Not directly comparable

  • V*

    Muse Spark 1.1—
    Step 3.7 Flash95.3%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Muse Spark 1.1 or Step 3.7 Flash?

Muse Spark 1.1 has the higher public score, 76.74 versus 50.76, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Muse Spark 1.1 or Step 3.7 Flash?

Muse Spark 1.1 leads the like-for-like coding comparison across 1 shared weighted benchmark row.

Which is better for agentic tasks, Muse Spark 1.1 or Step 3.7 Flash?

The current agentic tasks 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 costs less, Muse Spark 1.1 or Step 3.7 Flash?

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 1.1 or Step 3.7 Flash?

Muse Spark 1.1 has the larger documented context window: 1M, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 22, 2026

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