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BenchLM
Model A
GPT-5.4

OpenAI

73.1/100

Supported · Public rank #12

90% interval 69.9–76.3

GPT-5.4 vs Muse Spark

Updated August 21, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Muse Spark

Meta

70.6/100

Supported · Public rank #17

90% interval 61.0–80.2

Decision reading

GPT-5.4 has the higher public score estimate, 73.09 versus 70.6, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

23 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.

  • Long documents

    Prompts that approach the documented context limit

    GPT-5.4

    GPT-5.4 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

    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: 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.

Shared results
23
GPT-5.4 only
14
Muse Spark only
1
Like-for-like categories
2 / 8

4 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.

Reasoning

Like-for-like
GPT-5.4
74.0
Muse Spark
42.5
Weighted basis
1 vs 1 rows
Reading
GPT-5.4 leads

Math

Like-for-like
GPT-5.4
42.5
Muse Spark
32.9
Weighted basis
2 vs 2 rows
Reading
GPT-5.4 leads

Agentic

Directional only
GPT-5.4
77.2
Muse Spark
59.0
Weighted basis
3 vs 1 rows
Reading
Directional only

Coding

Directional only
GPT-5.4
57.7
Muse Spark
67.8
Weighted basis
1 vs 2 rows
Reading
Directional only

Knowledge

Directional only
GPT-5.4
57.6
Muse Spark
50.4
Weighted basis
2 vs 1 rows
Reading
Directional only

Multimodal

Directional only
GPT-5.4
73.2
Muse Spark
82.5
Weighted basis
3 vs 2 rows
Reading
Directional only

Multilingual

Not comparable
GPT-5.4
Not measured
Muse Spark
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
GPT-5.4
Not measured
Muse Spark
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

GPT-5.4
$0.01
Fits in one request
Muse Spark
API rate not published
Fits in one request

Muse Spark has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-5.4
$0.17
Fits in one request
Muse Spark
API rate not published
Fits in one request

Muse Spark has no comparable published API token rate.

Cache-heavy agent loop

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

GPT-5.4
$0.25
Fits in one request
Muse Spark
API rate not published
Fits in one request
Cached-input rate unavailable

Muse Spark 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.

GPT-5.4

1.05M

OpenAI pricing

Muse Spark

262K

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

GPT-5.4

$0.25 per 1M cached input tokens

OpenAI pricing

Muse Spark

No comparable hosted API rate

Documented inputs

GPT-5.4

Not sourced

Muse Spark

Not sourced

Documented outputs

GPT-5.4

Not sourced

Muse Spark

Not sourced

Provider availability

GPT-5.4

Not sourced

Muse Spark

Not sourced

Reasoning profile

GPT-5.4

Reasoning

Muse Spark

Reasoning

Weight access

GPT-5.4

Proprietary

Muse Spark

Proprietary

License

GPT-5.4

Proprietary

Muse Spark

Proprietary

Release date

GPT-5.4

2026-03-05

Muse Spark

2026-04-08

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
GPT-5.4 has the higher public score estimate, 73.09 versus 70.6, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
GPT-5.4 has the larger documented window (1.05M).

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 evidence38 rows

Agentic

  • Terminal-Bench 2.0

    GPT-5.475.1%
    Source
    Muse Spark59%
    Source

    GPT-5.4 leads this result

  • CyberGym

    GPT-5.479.0%
    Source
    Muse Spark43.5%
    Source

    GPT-5.4 leads this result

  • BrowseComp

    GPT-5.482.7%
    Source
    Muse Spark—

    Not directly comparable

  • OSWorld-Verified

    GPT-5.475%
    Source
    Muse Spark—

    Not directly comparable

  • MCP Atlas

    GPT-5.470.6%
    Source
    Muse Spark—

    Not directly comparable

  • Toolathlon

    GPT-5.454.6%
    Source
    Muse Spark—

    Not directly comparable

  • τ²-bench results

    GPT-5.498.9%
    Source
    Muse Spark91.5%
    Source

    GPT-5.4 leads this result

  • Claw-Eval

    Shared source
    GPT-5.460.3%
    Muse Spark63.8%

    Muse Spark leads this result

  • DeepSearchQA

    Shared source
    GPT-5.473.6%
    Muse Spark74.8%

    Muse Spark leads this result

  • Gert Labs

    GPT-5.464.89%
    Source
    Muse Spark—

    Not directly comparable

  • ResearchClawBench

    GPT-5.415.3%
    Source
    Muse Spark—

    Not directly comparable

  • JobBench

    GPT-5.438.9%
    Source
    Muse Spark—

    Not directly comparable

  • ExploitGym

    GPT-5.46.0%
    Source
    Muse Spark—

    Not directly comparable

Coding

  • LiveCodeBench Pro

    Shared source
    GPT-5.487.5%
    Muse Spark80.0%

    GPT-5.4 leads this result

  • SWE-bench Pro

    GPT-5.457.7%
    Source
    Muse Spark52.4%
    Source

    GPT-5.4 leads this result

  • React Native Evals

    GPT-5.485.3%
    Source
    Muse Spark—

    Not directly comparable

  • Vibe Code Bench

    Shared source
    GPT-5.467.42%
    Muse Spark19.67%

    GPT-5.4 leads this result

  • SWE-bench Verified

    GPT-5.4—
    Muse Spark77.4%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    GPT-5.474.0%
    Source
    Muse Spark42.5%
    Source

    GPT-5.4 leads this result

  • ARC-AGI-3

    GPT-5.40.2%
    Source
    Muse Spark—

    Not directly comparable

Knowledge

  • GPQA

    GPT-5.492.8%
    Source
    Muse Spark—

    Not directly comparable

  • HLE

    GPT-5.452.1%
    Source
    Muse Spark50.4%
    Source

    GPT-5.4 leads this result

  • HLE w/o tools

    GPT-5.439.8%
    Source
    Muse Spark42.8%
    Source

    Muse Spark leads this result

  • GPQA-D

    Shared source
    GPT-5.492.8%
    Muse Spark89.5%

    GPT-5.4 leads this result

  • HealthBench Hard

    Shared source
    GPT-5.440.1%
    Muse Spark42.8%

    Muse Spark leads this result

  • MedXpertQA (Text)

    Shared source
    GPT-5.459.6%
    Muse Spark52.6%

    GPT-5.4 leads this result

  • HealthBench Professional

    GPT-5.448.1%
    Source
    Muse Spark—

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    GPT-5.447.600%
    Muse Spark39.000%

    GPT-5.4 leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    GPT-5.427.100%
    Muse Spark14.600%

    GPT-5.4 leads this result

Multimodal

  • MMMU-Pro

    GPT-5.481.2%
    Source
    Muse Spark80.4%
    Source

    GPT-5.4 leads this result

  • OfficeQA Pro

    GPT-5.453.2%
    Source
    Muse Spark—

    Not directly comparable

  • MMMU-Pro w/ Python

    GPT-5.482.1%
    Source
    Muse Spark—

    Not directly comparable

  • CharXiv

    Shared source
    GPT-5.482.8%
    Muse Spark86.4%

    Muse Spark leads this result

  • ERQA

    Shared source
    GPT-5.465.4%
    Muse Spark64.7%

    GPT-5.4 leads this result

  • SimpleVQA

    Shared source
    GPT-5.461.1%
    Muse Spark71.3%

    Muse Spark leads this result

  • ScreenSpot Pro

    Shared source
    GPT-5.485.4%
    Muse Spark84.1%

    GPT-5.4 leads this result

  • ZeroBench

    Shared source
    GPT-5.441.0%
    Muse Spark33.0%

    GPT-5.4 leads this result

  • MedXpertQA (MM)

    Shared source
    GPT-5.477.1%
    Muse Spark78.4%

    Muse Spark leads this result

Frequently asked questions

Which is better, GPT-5.4 or Muse Spark?

GPT-5.4 has the higher public score estimate, 73.09 versus 70.6, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, GPT-5.4 or Muse Spark?

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, GPT-5.4 or Muse Spark?

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, GPT-5.4 or Muse Spark?

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, GPT-5.4 or Muse Spark?

GPT-5.4 has the larger documented context window: 1.05M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 21, 2026

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