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BenchLM

Claude Fable 5 vs Muse Spark 1.2

Decision reading

Claude Fable 5 has the higher public score, 81.41 versus 70.28, and the 90% score intervals do not overlap.

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

Anthropic logo
Model A
Claude Fable 5

Anthropic

81.41/100

Supported · Public rank #5

90% interval 77.9–84.9

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 Claude Fable 5 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

    Claude Fable 5

    Claude Fable 5 leads on the public coding lane, 76.9 to 60, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger

  • Agentic work

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

    Claude Fable 5

    Claude Fable 5 leads on the public agentic lane, 75.3 to 61, with Supported evidence for both models, although the 90% intervals overlap.

    Confidence: limited

  • 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

Show secondary and unsupported calls

  • 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. Costs use the listed standard API rates.

    Confidence: listed-rates

  • 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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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.

76.9Claude Fable 560.0Muse Spark 1.2

Like-for-like · BenchAlign

Claude Fable 5 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
5
Claude Fable 5 only
14
Muse Spark 1.2 only
3
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
Claude Fable 5
75.3
Supported · #3/154
Muse Spark 1.2
61.0
Supported · #16/154
Basis
BenchAlign lane · 5 vs 2 public rows
Reading
Claude Fable 5 leads · intervals overlap

Coding

Like-for-like
Claude Fable 5
76.9
Supported · #2/154
Muse Spark 1.2
60.0
Supported · #21/154
Basis
BenchAlign lane · 10 vs 5 public rows
Reading
Claude Fable 5 leads

Knowledge

Directional only
Claude Fable 5
83.3
Supported · #2/184
Muse Spark 1.2
70.7
Estimated · #10/184
Basis
BenchAlign lane · 2 vs 1 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Fable 5
77.6
#6/20
Muse Spark 1.2
75.3
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5
Not ranked
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5
62.6
Unranked · 2 rankable rows
Muse Spark 1.2
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Fable 5
77.0
#57/124
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

Claude Fable 5
$0.035
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

Claude Fable 5
$0.65
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

Claude Fable 5
$0.9
Fits in one request
Muse Spark 1.2
$0.0975
Fits in one request

Muse Spark 1.2 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.

Cached-input rate

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

Claude Fable 5

$1 per 1M cached input tokens

Claude API pricing

Muse Spark 1.2

$0.15 per 1M cached input tokens

Meta: Muse Spark 1.2 model page

Reasoning profile

Claude Fable 5

Reasoning

Muse Spark 1.2

Reasoning

Weight access

Claude Fable 5

Proprietary

Muse Spark 1.2

Proprietary

License

Claude Fable 5

Proprietary

Muse Spark 1.2

Proprietary

Release date

Claude Fable 5

2026-06-09

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
Claude Fable 5 has the higher public score, 81.41 versus 70.28, and the 90% score intervals do not overlap.
Workload cost
Repository review: $0.65 vs $0.07525. Cache-heavy agent loop: $0.9 vs $0.0975.
Context tradeoff
Both models list 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 evidence22 rows

Agentic

  • Terminal-Bench 3.0

    Claude Fable 534.0%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • OSWorld-Verified

    Claude Fable 585%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 580.5%
    Source
    Muse Spark 1.269.7%
    Source

    Claude Fable 5 leads this result

  • ApprenticeBench

    Claude Fable 534%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Fable 5—
    Muse Spark 1.282.9%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Fable 595%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE-bench Pro

    Claude Fable 580%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • FrontierSWE v2

    Shared source
    Claude Fable 547.0%
    Muse Spark 1.212.0%

    Claude Fable 5 leads this result

  • FrontierCode 1.1 Main

    Claude Fable 553.5%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • cursorBench31

    Claude Fable 570.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • cursorBench32

    Claude Fable 570.5%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • VulcanBench v3

    Claude Fable 589.5%
    Source
    Muse Spark 1.287.0%
    Source

    Claude Fable 5 leads this result

  • LiveCodeBench (Vals)

    Claude Fable 589.8%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Fable 595.0%
    Source
    Muse Spark 1.286.6%
    Source

    Claude Fable 5 leads this result

  • Terminal-Bench 2.1

    Claude Fable 5—
    Muse Spark 1.282.9%
    Source

    Not directly comparable

  • DeepSWE

    Claude Fable 5—
    Muse Spark 1.259.3%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Fable 593.2%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 591.5%
    Source
    Muse Spark 1.288.3%
    Source

    Claude Fable 5 leads this result

Multimodal

  • Blueprint-Bench 2

    Claude Fable 538.6%
    Source
    Muse Spark 1.2—

    Not directly comparable

  • OfficeQA Pro

    Claude Fable 557.9%
    Source
    Muse Spark 1.2—

    Not directly comparable

Questions

Which is better, Claude Fable 5 or Muse Spark 1.2?

Claude Fable 5 has the higher public score, 81.41 versus 70.28, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Claude Fable 5 or Muse Spark 1.2?

Claude Fable 5 leads the public coding lane, 76.9 to 60, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Claude Fable 5 or Muse Spark 1.2?

Claude Fable 5 leads the public agentic tasks lane, 75.3 to 61, with Supported evidence for both models, although the 90% intervals overlap.

Which costs less, Claude Fable 5 or Muse Spark 1.2?

For the stated presets, chat costs $0.035 on Claude Fable 5 and $0.00337 on Muse Spark 1.2; repository review costs $0.65 and $0.07525; the cache-heavy agent loop costs $0.9 and $0.0975. Costs use the listed standard API rates.

Which has the larger context window, Claude Fable 5 or Muse Spark 1.2?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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