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BenchLM
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Model A
Mercury 2.5

Inception

—

Evidence status unavailable

90% interval unavailable

Mercury 2.5 vs Muse Spark 1.3

Updated September 8, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

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Model B
Muse Spark 1.3

Meta

—

Evidence status unavailable

90% interval unavailable

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

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

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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.

  • Long documents

    Prompts that approach the documented context limit

    Muse Spark 1.3

    Muse Spark 1.3 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Mercury 2.5

    Mercury 2.5 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

    Mercury 2.5

    Mercury 2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    Mercury 2.5

    Mercury 2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Muse Spark 1.3 is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Muse Spark 1.3 is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

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
1
Mercury 2.5 only
4
Muse Spark 1.3 only
9
Like-for-like categories
0 / 8

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

Not comparable
Mercury 2.5
44.5
Estimated · #91/152
Muse Spark 1.3
Not ranked
Basis
BenchAlign lane · 2 vs 5 public rows
Reading
Not comparable

Coding

Not comparable
Mercury 2.5
47.8
Estimated · #73/151
Muse Spark 1.3
Not ranked
Basis
BenchAlign lane · 1 vs 3 public rows
Reading
Not comparable

Reasoning

Not comparable
Mercury 2.5
67.7
Unranked · 1 rankable row
Muse Spark 1.3
78.0
#4/18
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Mercury 2.5
48.3
Estimated · #94/182
Muse Spark 1.3
Not ranked
Basis
BenchAlign lane · 1 vs 0 public rows
Reading
Not comparable

Math

Not comparable
Mercury 2.5
Not ranked
Muse Spark 1.3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Mercury 2.5
Not ranked
Muse Spark 1.3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Mercury 2.5
Not ranked
Muse Spark 1.3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Mercury 2.5
80.1
#53/121
Muse Spark 1.3
Not ranked
Basis
Provisional lane · 1 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.

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

Mercury 2.5
$0.00012
Fits in one request
Muse Spark 1.3
$0.00338
Fits in one request

Mercury 2.5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Mercury 2.5
$0.00245
Fits in one request
Muse Spark 1.3
$0.07525
Fits in one request

Mercury 2.5 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Mercury 2.5
$0.0031
Fits in one request
Muse Spark 1.3
$0.0975
Fits in one request

Mercury 2.5 has the lower modeled cost

Costs use the listed standard API rates.

Specification differences

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

Reasoning profile

Mercury 2.5

Reasoning

Muse Spark 1.3

Reasoning

Weight access

Mercury 2.5

Proprietary

Muse Spark 1.3

Proprietary

License

Mercury 2.5

Proprietary

Muse Spark 1.3

Proprietary

Release date

Mercury 2.5

2026-09-08

Muse Spark 1.3

2026-09-02

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
Repository review: $0.00245 vs $0.07525. Cache-heavy agent loop: $0.0031 vs $0.0975.
Context tradeoff
Muse Spark 1.3 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 evidence14 rows

Agentic

  • τ³-bench results

    Mercury 2.596.0%
    Source
    Muse Spark 1.3—

    Not directly comparable

  • DeepSearchQA

    Mercury 2.534.0%
    Source
    Muse Spark 1.389.4%
    Source

    Muse Spark 1.3 leads this result

  • Terminal-Bench 2.1

    Mercury 2.5—
    Muse Spark 1.388.8%
    Source

    Not directly comparable

  • JobBench

    Mercury 2.5—
    Muse Spark 1.364.9%
    Source

    Not directly comparable

  • OSWorld 2.0

    Mercury 2.5—
    Muse Spark 1.366.9%
    Source

    Not directly comparable

  • AutomationBench

    Mercury 2.5—
    Muse Spark 1.349.4%
    Source

    Not directly comparable

Coding

  • SciCode

    Mercury 2.538%
    Source
    Muse Spark 1.3—

    Not directly comparable

  • Terminal-Bench 2.1

    Mercury 2.5—
    Muse Spark 1.388.8%
    Source

    Not directly comparable

  • deepSwe

    Mercury 2.5—
    Muse Spark 1.375.4%
    Source

    Not directly comparable

  • SWE-Atlas Codebase QnA

    Mercury 2.5—
    Muse Spark 1.359.4%
    Source

    Not directly comparable

Reasoning

  • MRCR v2 256K-512K

    Mercury 2.5—
    Muse Spark 1.398.5%
    Source

    Not directly comparable

  • MRCR v2 512K-1M

    Mercury 2.5—
    Muse Spark 1.398.1%
    Source

    Not directly comparable

Knowledge

  • GPQA-D

    Mercury 2.579.0%
    Source
    Muse Spark 1.3—

    Not directly comparable

Instruction following

  • IFBench

    Mercury 2.577%
    Source
    Muse Spark 1.3—

    Not directly comparable

Frequently asked questions

Which is better, Mercury 2.5 or Muse Spark 1.3?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Mercury 2.5 or Muse Spark 1.3?

Muse Spark 1.3 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Mercury 2.5 or Muse Spark 1.3?

Muse Spark 1.3 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Mercury 2.5 or Muse Spark 1.3?

For the stated presets, chat costs $0.00012 on Mercury 2.5 and $0.00337 on Muse Spark 1.3; repository review costs $0.00245 and $0.07525; the cache-heavy agent loop costs $0.0031 and $0.0975. Costs use the listed standard API rates.

Which has the larger context window, Mercury 2.5 or Muse Spark 1.3?

Muse Spark 1.3 has the larger documented context window: 1M, compared with 260K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 8, 2026

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