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BenchLM
Model A
Grok 4.20

xAI

55.2/100

Estimated · Public rank #97

90% interval 38.3–72.0

Grok 4.20 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

Muse Spark has the higher public score estimate, 70.6 versus 55.16, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

16 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

    Muse Spark leads on the same 2 weighted benchmark rows.

    Confidence: limited

  • Agentic work

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

    Muse Spark

    Muse Spark leads on the same 1 weighted benchmark row.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Grok 4.20

    Grok 4.20 has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • 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
16
Grok 4.20 only
2
Muse Spark only
8
Like-for-like categories
4 / 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.

Agentic

Like-for-like
Grok 4.20
47.1
Muse Spark
59.0
Weighted basis
1 vs 1 rows
Reading
Muse Spark leads

Coding

Like-for-like
Grok 4.20
67.1
Muse Spark
67.8
Weighted basis
2 vs 2 rows
Reading
Muse Spark leads

Reasoning

Like-for-like
Grok 4.20
53.3
Muse Spark
42.5
Weighted basis
1 vs 1 rows
Reading
Grok 4.20 leads

Multimodal

Like-for-like
Grok 4.20
70.1
Muse Spark
82.5
Weighted basis
2 vs 2 rows
Reading
Muse Spark leads

Knowledge

Not comparable
Grok 4.20
Not measured
Muse Spark
50.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

Math

Not comparable
Grok 4.20
Not measured
Muse Spark
32.9
Weighted basis
0 vs 2 rows
Reading
Not comparable

Multilingual

Not comparable
Grok 4.20
Not measured
Muse Spark
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Grok 4.20
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.

  • CharXiv

    Multimodal

    Grok 4.20: 60.9%Muse Spark: 86.4%Normalized gap 25.5Shared source

  • Terminal-Bench 2.0

    Agentic

    Grok 4.20: 47.1%Muse Spark: 59%Normalized gap 11.9Shared source

  • ARC-AGI-2

    Reasoning

    Grok 4.20: 53.3%Muse Spark: 42.5%Normalized gap 10.8Shared source

  • MMMU-Pro

    Multimodal

    Grok 4.20: 75.2%Muse Spark: 80.4%Normalized gap 5.2Shared source

  • SWE-bench Verified

    Coding

    Grok 4.20: 76.7%Muse Spark: 77.4%Normalized gap 0.7Shared 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

Grok 4.20
$0.005
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

Grok 4.20
$0.118
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

Grok 4.20
$0.5
Fits in one request
Cached input priced at the published list-input rate
Muse Spark
API rate not published
Fits in one request
Cached-input rate unavailable

Grok 4.20 has no published cached-input rate, so cached tokens use its listed input rate. 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.

Grok 4.20

2M

Muse Spark

262K

API model ID

Grok 4.20

Not sourced

Muse Spark

Not sourced

Cached-input rate

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

Grok 4.20

Not published

Muse Spark

No comparable hosted API rate

Documented inputs

Grok 4.20

Not sourced

Muse Spark

Not sourced

Documented outputs

Grok 4.20

Not sourced

Muse Spark

Not sourced

Provider availability

Grok 4.20

Not sourced

Muse Spark

Not sourced

Reasoning profile

Grok 4.20

Reasoning

Muse Spark

Reasoning

Weight access

Grok 4.20

Proprietary

Muse Spark

Proprietary

License

Grok 4.20

Proprietary

Muse Spark

Proprietary

Release date

Grok 4.20

2026-03-10

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
Muse Spark has the higher public score estimate, 70.6 versus 55.16, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Grok 4.20 has the larger documented window (2M).

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 evidence26 rows

Agentic

  • Terminal-Bench 2.0

    Shared source
    Grok 4.2047.1%
    Muse Spark59%

    Muse Spark leads this result

  • DeepSearchQA

    Shared source
    Grok 4.2062.8%
    Muse Spark74.8%

    Muse Spark leads this result

  • Gert Labs

    Grok 4.2038.36%
    Source
    Muse Spark—

    Not directly comparable

  • τ²-bench results

    Grok 4.20—
    Muse Spark91.5%
    Source

    Not directly comparable

  • CyberGym

    Grok 4.20—
    Muse Spark43.5%
    Source

    Not directly comparable

  • Claw-Eval

    Grok 4.20—
    Muse Spark63.8%
    Source

    Not directly comparable

Coding

  • LiveCodeBench Pro

    Shared source
    Grok 4.2074.2%
    Muse Spark80.0%

    Muse Spark leads this result

  • SWE-bench Verified

    Shared source
    Grok 4.2076.7%
    Muse Spark77.4%

    Muse Spark leads this result

  • SWE-bench Pro

    Shared source
    Grok 4.2051.8%
    Muse Spark52.4%

    Muse Spark leads this result

  • Vibe Code Bench

    Shared source
    Grok 4.204.06%
    Muse Spark19.67%

    Muse Spark leads this result

Reasoning

  • ARC-AGI-2

    Shared source
    Grok 4.2053.3%
    Muse Spark42.5%

    Grok 4.20 leads this result

  • ARC-AGI-3

    Grok 4.200.1%
    Source
    Muse Spark—

    Not directly comparable

Knowledge

  • GPQA-D

    Shared source
    Grok 4.2088.5%
    Muse Spark89.5%

    Muse Spark leads this result

  • HLE w/o tools

    Shared source
    Grok 4.2031.6%
    Muse Spark42.8%

    Muse Spark leads this result

  • HealthBench Hard

    Shared source
    Grok 4.2020.3%
    Muse Spark42.8%

    Muse Spark leads this result

  • MedXpertQA (Text)

    Shared source
    Grok 4.2050.2%
    Muse Spark52.6%

    Muse Spark leads this result

  • HLE

    Grok 4.20—
    Muse Spark50.4%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Grok 4.20—
    Muse Spark39.000%
    Source

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Grok 4.20—
    Muse Spark14.600%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Shared source
    Grok 4.2075.2%
    Muse Spark80.4%

    Muse Spark leads this result

  • CharXiv

    Shared source
    Grok 4.2060.9%
    Muse Spark86.4%

    Muse Spark leads this result

  • ERQA

    Shared source
    Grok 4.2054.1%
    Muse Spark64.7%

    Muse Spark leads this result

  • SimpleVQA

    Shared source
    Grok 4.2057.4%
    Muse Spark71.3%

    Muse Spark leads this result

  • MedXpertQA (MM)

    Shared source
    Grok 4.2065.8%
    Muse Spark78.4%

    Muse Spark leads this result

  • ScreenSpot Pro

    Grok 4.20—
    Muse Spark84.1%
    Source

    Not directly comparable

  • ZeroBench

    Grok 4.20—
    Muse Spark33.0%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Grok 4.20 or Muse Spark?

Muse Spark has the higher public score estimate, 70.6 versus 55.16, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Grok 4.20 or Muse Spark?

Muse Spark leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, Grok 4.20 or Muse Spark?

Muse Spark leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.

Which costs less, Grok 4.20 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, Grok 4.20 or Muse Spark?

Grok 4.20 has the larger documented context window: 2M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 21, 2026

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