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IBM logo
Model A
Granite 4.2 8B

IBM

46.88/100

Estimated · Public rank #162

90% interval 35.4–58.4

Granite 4.2 8B vs Muse Spark 1.2

Updated August 31, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Meta logo
Model B
Muse Spark 1.2

Meta

62.15/100

Estimated · Public rank #54

90% interval 50.6–73.7

Decision reading

Muse Spark 1.2 has the higher public score estimate, 62.15 versus 46.88, 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 1.2

    Muse Spark 1.2 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. Granite 4.2 8B does not fit this workload in one request. Granite 4.2 8B 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
Granite 4.2 8B only
12
Muse Spark 1.2 only
1
Like-for-like categories
0 / 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

Not comparable
Granite 4.2 8B
Not measured
Muse Spark 1.2
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Granite 4.2 8B
36.5
Muse Spark 1.2
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Granite 4.2 8B
Not measured
Muse Spark 1.2
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Granite 4.2 8B
72.2
Muse Spark 1.2
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Math

Not comparable
Granite 4.2 8B
Not measured
Muse Spark 1.2
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Granite 4.2 8B
Not measured
Muse Spark 1.2
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Granite 4.2 8B
Not measured
Muse Spark 1.2
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Granite 4.2 8B
79.3
Muse Spark 1.2
Not measured
Weighted basis
1 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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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

Granite 4.2 8B
Self-hosted; infrastructure cost varies
Fits in one request
Muse Spark 1.2
$0.00338
Fits in one request

Granite 4.2 8B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Granite 4.2 8B
Self-hosted; infrastructure cost varies
Fits in one request
Muse Spark 1.2
$0.07525
Fits in one request

Granite 4.2 8B has no comparable published API token rate.

Cache-heavy agent loop

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

Granite 4.2 8B
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable
Muse Spark 1.2
$0.0975
Fits in one request

Granite 4.2 8B does not fit this workload in one request. Granite 4.2 8B 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.

Documented inputs

Granite 4.2 8B

Not sourced

Muse Spark 1.2

Not sourced

Documented outputs

Granite 4.2 8B

Not sourced

Muse Spark 1.2

Not sourced

Provider availability

Granite 4.2 8B

Not sourced

Muse Spark 1.2

Not sourced

Reasoning profile

Granite 4.2 8B

Reasoning

Muse Spark 1.2

Reasoning

Weight access

Granite 4.2 8B

Open Weight

Muse Spark 1.2

Proprietary

License

Granite 4.2 8B

Open Weight

Muse Spark 1.2

Proprietary

Release date

Granite 4.2 8B

2026-08-25

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, 62.15 versus 46.88, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Muse Spark 1.2 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 evidence15 rows

Agentic

  • Terminal-Bench 2.1

    Granite 4.2 8B20.6%
    Source
    Muse Spark 1.282.9%
    Source

    Muse Spark 1.2 leads this result

  • τ³-bench results

    Granite 4.2 8B58.1%
    Source
    Muse Spark 1.2

    Not directly comparable

  • BFCL v4

    Granite 4.2 8B52.4%
    Source
    Muse Spark 1.2

    Not directly comparable

Coding

  • SWE-bench Verified

    Granite 4.2 8B47.7%
    Source
    Muse Spark 1.2

    Not directly comparable

  • SWE-bench Pro

    Granite 4.2 8B19.1%
    Source
    Muse Spark 1.2

    Not directly comparable

  • SWE Multilingual

    Granite 4.2 8B30.8%
    Source
    Muse Spark 1.2

    Not directly comparable

  • Terminal-Bench 2.1

    Granite 4.2 8B20.6%
    Source
    Muse Spark 1.282.9%
    Source

    Muse Spark 1.2 leads this result

  • LiveCodeBench v6

    Granite 4.2 8B73.2%
    Source
    Muse Spark 1.2

    Not directly comparable

  • SciCode

    Granite 4.2 8B36.1%
    Source
    Muse Spark 1.2

    Not directly comparable

  • deepSwe

    Granite 4.2 8B
    Muse Spark 1.259.3%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Granite 4.2 8B64.1%
    Source
    Muse Spark 1.2

    Not directly comparable

  • MMLU-Pro

    Granite 4.2 8B74.0%
    Source
    Muse Spark 1.2

    Not directly comparable

Math

  • AIME 2025

    Granite 4.2 8B86.7%
    Source
    Muse Spark 1.2

    Not directly comparable

  • HMMT Feb 2025

    Granite 4.2 8B78.3%
    Source
    Muse Spark 1.2

    Not directly comparable

Instruction following

  • IFBench

    Granite 4.2 8B79.3%
    Source
    Muse Spark 1.2

    Not directly comparable

Frequently asked questions

Which is better, Granite 4.2 8B or Muse Spark 1.2?

Muse Spark 1.2 has the higher public score estimate, 62.15 versus 46.88, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Granite 4.2 8B or Muse Spark 1.2?

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, Granite 4.2 8B or Muse Spark 1.2?

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, Granite 4.2 8B or Muse Spark 1.2?

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, Granite 4.2 8B or Muse Spark 1.2?

Muse Spark 1.2 has the larger documented context window: 1M, compared with 128K.

Related comparisons

Last updated August 31, 2026

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