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Radar

Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

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Model A
Muse Spark

Meta

70.6/100

Supported · Public rank #17

90% interval 61.0–80.2

Muse Spark vs o4-mini (high)

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

Model B
o4-mini (high)

OpenAI

50.4/100

Estimated · Public rank #130

90% interval 38.9–61.9

Decision reading

Muse Spark has the higher public score estimate, 70.6 versus 50.37, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 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

    Muse Spark

    Muse Spark 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

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. o4-mini (high) does not fit this workload in one request. Muse Spark has no comparable published API token rate. o4-mini (high) has no comparable published API token rate.

    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
2
Muse Spark only
22
o4-mini (high) only
0
Like-for-like categories
1 / 8

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.

Math

Like-for-like
Muse Spark
32.9
o4-mini (high)
20.2
Weighted basis
2 vs 2 rows
Reading
Muse Spark leads

Agentic

Not comparable
Muse Spark
59.0
o4-mini (high)
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Muse Spark
67.8
o4-mini (high)
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Muse Spark
42.5
o4-mini (high)
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Muse Spark
50.4
o4-mini (high)
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Muse Spark
Not measured
o4-mini (high)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Muse Spark
82.5
o4-mini (high)
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Muse Spark
Not measured
o4-mini (high)
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.

  • FrontierMath v2 (Tiers 1-3)

    Math

    Muse Spark: 39.000%o4-mini (high): 24.828%Normalized gap 14.2Shared source
  • FrontierMath v2 (Tier 4)

    Math

    Muse Spark: 14.600%o4-mini (high): 6.250%Normalized gap 8.3Shared 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
o4-mini (high)
API rate not published
Fits in one request

Muse Spark has no comparable published API token rate. o4-mini (high) 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
o4-mini (high)
API rate not published
Fits in one request

Muse Spark has no comparable published API token rate. o4-mini (high) 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
o4-mini (high)
API rate not published
Does not fit in one request
Cached-input rate unavailable

o4-mini (high) does not fit this workload in one request. Muse Spark has no comparable published API token rate. o4-mini (high) 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

262K

o4-mini (high)

200K

API model ID

Muse Spark

Not sourced

o4-mini (high)

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

o4-mini (high)

No comparable hosted API rate

Documented inputs

Muse Spark

Not sourced

o4-mini (high)

Not sourced

Documented outputs

Muse Spark

Not sourced

o4-mini (high)

Not sourced

Provider availability

Muse Spark

Not sourced

o4-mini (high)

Not sourced

Reasoning profile

Muse Spark

Reasoning

o4-mini (high)

Reasoning

Weight access

Muse Spark

Proprietary

o4-mini (high)

Proprietary

License

Muse Spark

Proprietary

o4-mini (high)

Proprietary

Release date

Muse Spark

2026-04-08

o4-mini (high)

2025-04-16

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, 70.6 versus 50.37, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Muse Spark has the larger documented window (262K).

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 evidence24 rows

Agentic

  • Terminal-Bench 2.0

    Muse Spark59%
    Source
    o4-mini (high)

    Not directly comparable

  • τ²-bench results

    Muse Spark91.5%
    Source
    o4-mini (high)

    Not directly comparable

  • DeepSearchQA

    Muse Spark74.8%
    Source
    o4-mini (high)

    Not directly comparable

  • CyberGym

    Muse Spark43.5%
    Source
    o4-mini (high)

    Not directly comparable

  • Claw-Eval

    Muse Spark63.8%
    Source
    o4-mini (high)

    Not directly comparable

Coding

  • SWE-bench Verified

    Muse Spark77.4%
    Source
    o4-mini (high)

    Not directly comparable

  • SWE-bench Pro

    Muse Spark52.4%
    Source
    o4-mini (high)

    Not directly comparable

  • LiveCodeBench Pro

    Muse Spark80.0%
    Source
    o4-mini (high)

    Not directly comparable

  • Vibe Code Bench

    Muse Spark19.67%
    Source
    o4-mini (high)

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Muse Spark42.5%
    Source
    o4-mini (high)

    Not directly comparable

Knowledge

  • GPQA-D

    Muse Spark89.5%
    Source
    o4-mini (high)

    Not directly comparable

  • HLE

    Muse Spark50.4%
    Source
    o4-mini (high)

    Not directly comparable

  • HLE w/o tools

    Muse Spark42.8%
    Source
    o4-mini (high)

    Not directly comparable

  • HealthBench Hard

    Muse Spark42.8%
    Source
    o4-mini (high)

    Not directly comparable

  • MedXpertQA (Text)

    Muse Spark52.6%
    Source
    o4-mini (high)

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Muse Spark39.000%
    o4-mini (high)24.828%

    Muse Spark leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    Muse Spark14.600%
    o4-mini (high)6.250%

    Muse Spark leads this result

Multimodal

  • CharXiv

    Muse Spark86.4%
    Source
    o4-mini (high)

    Not directly comparable

  • MMMU-Pro

    Muse Spark80.4%
    Source
    o4-mini (high)

    Not directly comparable

  • ERQA

    Muse Spark64.7%
    Source
    o4-mini (high)

    Not directly comparable

  • SimpleVQA

    Muse Spark71.3%
    Source
    o4-mini (high)

    Not directly comparable

  • ScreenSpot Pro

    Muse Spark84.1%
    Source
    o4-mini (high)

    Not directly comparable

  • ZeroBench

    Muse Spark33.0%
    Source
    o4-mini (high)

    Not directly comparable

  • MedXpertQA (MM)

    Muse Spark78.4%
    Source
    o4-mini (high)

    Not directly comparable

Frequently asked questions

Which is better, Muse Spark or o4-mini (high)?

Muse Spark has the higher public score estimate, 70.6 versus 50.37, 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 o4-mini (high)?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Muse Spark or o4-mini (high)?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Muse Spark or o4-mini (high)?

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 o4-mini (high)?

Muse Spark has the larger documented context window: 262K, compared with 200K.

Related comparisons

Last updated August 21, 2026

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