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BenchLM

Grok 4.20 vs Muse Spark 1.2

Decision reading

Muse Spark 1.2 has the higher public score estimate, 70.28 versus 67.27, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

xAI logo
Model A
Grok 4.20

xAI

67.27/100

Supported · Public rank #29

90% interval 58.7–75.8

Meta logo
Model B
Muse Spark 1.2

Meta

70.28/100

Estimated · Public rank #16

90% interval 58.9–76.0

Updated September 18, 2026. Rank says Muse Spark 1.2 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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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 1.2

    Muse Spark 1.2 leads on the public coding lane, 60 to 28.3, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger

  • 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 26.5, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger

  • 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

    Muse Spark 1.2

    Muse Spark 1.2 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Muse Spark 1.2

    Muse Spark 1.2 has the lower estimated token cost for this stated workload. Grok 4.20 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

  • Repository review cost

    50K fresh input + 3K output tokens

    Muse Spark 1.2

    Muse Spark 1.2 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    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.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

28.3Grok 4.2060.0Muse Spark 1.2

Like-for-like · BenchAlign

Muse Spark 1.2 leads the like-for-like coding row.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist 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.

Shared results
3
Grok 4.20 only
20
Muse Spark 1.2 only
5
Like-for-like categories
2 / 8

1 category rests 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
Grok 4.20
26.5
Supported · #149/154
Muse Spark 1.2
61.0
Supported · #16/154
Basis
BenchAlign lane · 4 vs 2 public rows
Reading
Muse Spark 1.2 leads

Coding

Like-for-like
Grok 4.20
28.3
Supported · #145/154
Muse Spark 1.2
60.0
Supported · #21/154
Basis
BenchAlign lane · 6 vs 5 public rows
Reading
Muse Spark 1.2 leads

Knowledge

Directional only
Grok 4.20
49.2
Supported · #87/184
Muse Spark 1.2
70.7
Estimated · #10/184
Basis
BenchAlign lane · 6 vs 1 public rows
Reading
Directional only

Reasoning

Not comparable
Grok 4.20
34.3
Unranked · 2 rankable rows
Muse Spark 1.2
75.3
Unranked · 2 rankable rows
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Grok 4.20
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Grok 4.20
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Grok 4.20
34.6
#43/48
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Grok 4.20
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
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.

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

Grok 4.20
$0.005
Fits in one request
Muse Spark 1.2
$0.00338
Fits in one request

Muse Spark 1.2 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Grok 4.20
$0.118
Fits in one request
Muse Spark 1.2
$0.07525
Fits in one request

Muse Spark 1.2 has the lower modeled cost

Costs use the listed standard API rates.

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 1.2
$0.0975
Fits in one request

Muse Spark 1.2 has the lower modeled cost

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

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

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 1.2

$0.15 per 1M cached input tokens

Meta: Muse Spark 1.2 model page

Documented inputs

Grok 4.20

Not sourced

Muse Spark 1.2

Not sourced

Documented outputs

Grok 4.20

Not sourced

Muse Spark 1.2

Not sourced

Provider availability

Grok 4.20

Not sourced

Muse Spark 1.2

Not sourced

Reasoning profile

Grok 4.20

Reasoning

Muse Spark 1.2

Reasoning

Weight access

Grok 4.20

Proprietary

Muse Spark 1.2

Proprietary

License

Grok 4.20

Proprietary

Muse Spark 1.2

Proprietary

Release date

Grok 4.20

2026-03-10

Muse Spark 1.2

2026-08-05

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 67.27, but the 90% score intervals overlap.
Workload cost
Repository review: $0.118 vs $0.07525. Cache-heavy agent loop: $0.5 vs $0.0975.
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 evidence28 rows

Agentic

  • Terminal-Bench 2.0

    Grok 4.2047.1%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • DeepSearchQA

    Grok 4.2062.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Gert Labs

    Grok 4.2038.36%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Grok 4.2044.2%
    Source
    Muse Spark 1.269.7%
    Source

    Muse Spark 1.2 leads this result

  • Terminal-Bench 2.1

    Grok 4.20—
    Muse Spark 1.282.9%
    Source

    Not directly comparable

Coding

  • LiveCodeBench Pro

    Grok 4.2074.2%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE-bench Verified

    Grok 4.2076.7%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE-bench Pro

    Grok 4.2051.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Vibe Code Bench

    Grok 4.204.06%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • LiveCodeBench (Vals)

    Grok 4.2084.3%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE-bench (Vals)

    Grok 4.2072.2%
    Source
    Muse Spark 1.286.6%
    Source

    Muse Spark 1.2 leads this result

  • Terminal-Bench 2.1

    Grok 4.20—
    Muse Spark 1.282.9%
    Source

    Not directly comparable

  • DeepSWE

    Grok 4.20—
    Muse Spark 1.259.3%
    Source

    Not directly comparable

  • VulcanBench v3

    Grok 4.20—
    Muse Spark 1.287.0%
    Source

    Not directly comparable

  • FrontierSWE v2

    Grok 4.20—
    Muse Spark 1.212.0%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Grok 4.2053.3%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • ARC-AGI-3

    Grok 4.200.1%
    Source
    Muse Spark 1.2—

    Not directly comparable

Knowledge

  • GPQA-D

    Grok 4.2088.5%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • HLE w/o tools

    Grok 4.2031.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • HealthBench Hard

    Grok 4.2020.3%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MedXpertQA (Text)

    Grok 4.2050.2%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • GPQA Diamond (Vals)

    Grok 4.2088.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MMLU-Pro (Vals)

    Grok 4.2086.3%
    Source
    Muse Spark 1.288.3%
    Source

    Muse Spark 1.2 leads this result

Multimodal

  • MMMU-Pro

    Grok 4.2075.2%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • CharXiv

    Grok 4.2060.9%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • ERQA

    Grok 4.2054.1%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SimpleVQA

    Grok 4.2057.4%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MedXpertQA (MM)

    Grok 4.2065.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

Questions

Which is better, Grok 4.20 or Muse Spark 1.2?

Muse Spark 1.2 has the higher public score estimate, 70.28 versus 67.27, 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 1.2?

Muse Spark 1.2 leads the public coding lane, 60 to 28.3, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Grok 4.20 or Muse Spark 1.2?

Muse Spark 1.2 leads the public agentic tasks lane, 61 to 26.5, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Grok 4.20 or Muse Spark 1.2?

For the stated presets, chat costs $0.005 on Grok 4.20 and $0.00337 on Muse Spark 1.2; repository review costs $0.118 and $0.07525; the cache-heavy agent loop costs $0.5 and $0.0975. Grok 4.20 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Grok 4.20 or Muse Spark 1.2?

Grok 4.20 has the larger documented context window: 2M, compared with 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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