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Radar

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BenchLM
Anthropic logo
Model A
Claude Fable 5

Anthropic

82.49/100

Supported · Public rank #3

90% interval 80.3–84.7

Claude Fable 5 vs Claude Fable 5.1

Updated September 1, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload. This is a same-family comparison, so migration details appear when the source data supports them.

Anthropic logo
Model B
Claude Fable 5.1

Anthropic

82.74/100

Estimated · Public rank #1

90% interval 71.2–94.3

Decision reading

Claude Fable 5.1 has the higher public score estimate, 82.74 versus 82.49, 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.

  • Cache-heavy agent loop cost

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

    Claude Fable 5.1

    Claude Fable 5.1 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

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    No clear pick

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    No clear pick

    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
Claude Fable 5 only
10
Claude Fable 5.1 only
16
Like-for-like categories
0 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Coding

Directional only
Claude Fable 5
89.2
Claude Fable 5.1
81.2
Weighted basis
2 vs 1 rows
Reading
Directional only

Agentic

Not comparable
Claude Fable 5
84.6
Claude Fable 5.1
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Fable 5
Not measured
Claude Fable 5.1
90.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Fable 5
Not measured
Claude Fable 5.1
65.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5
57.9
Claude Fable 5.1
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Fable 5
Not measured
Claude Fable 5.1
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.

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
Claude Fable 5.1
$0.035
Fits in one request

Modeled costs are equal

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5
$0.65
Fits in one request
Claude Fable 5.1
$0.65
Fits in one request

Modeled costs are equal

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
Claude Fable 5.1
$0.75
Fits in one request

Claude Fable 5.1 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

Claude Fable 5.1

$0.25 per 1M cached input tokens

Anthropic Fable 5.1 launch

Reasoning profile

Claude Fable 5

Reasoning

Claude Fable 5.1

Reasoning

Weight access

Claude Fable 5

Proprietary

Claude Fable 5.1

Proprietary

License

Claude Fable 5

Proprietary

Claude Fable 5.1

Proprietary

Release date

Claude Fable 5

2026-06-09

Claude Fable 5.1

2026-09-01

If you are considering the documented upgrade path
Deployment change
Both entries list Anthropic as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
Claude Fable 5.1 has the higher public score estimate, 82.74 versus 82.49, but the 90% score intervals overlap.
Workload cost
Repository review: $0.65 vs $0.65. Cache-heavy agent loop: $0.9 vs $0.75.
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 evidence28 rows

Agentic

  • Terminal-Bench 3.0

    Claude Fable 534.0%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • OSWorld-Verified

    Claude Fable 585%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • Terminal-Bench 4.0

    Claude Fable 5—
    Claude Fable 5.155.80%
    Source

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Fable 5—
    Claude Fable 5.152.6%
    Source

    Not directly comparable

  • OSWorld 2.0

    Claude Fable 5—
    Claude Fable 5.141.7%
    Source

    Not directly comparable

  • AutomationBench

    Claude Fable 5—
    Claude Fable 5.131.4%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Claude Fable 5—
    Claude Fable 5.177.8%
    Source

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Fable 5—
    Claude Fable 5.181.5%
    Source

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Fable 5—
    Claude Fable 5.173.1%
    Source

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Fable 5—
    Claude Fable 5.123.7 turns
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Fable 595%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • SWE-bench Pro

    Claude Fable 580%
    Source
    Claude Fable 5.181.2%
    Source

    Claude Fable 5.1 leads this result

  • FrontierCode 1.1 Main

    Claude Fable 553.5%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • cursorBench31

    Claude Fable 570.6%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • cursorBench32

    Shared source
    Claude Fable 570.5%
    Claude Fable 5.173.4%

    Claude Fable 5.1 leads this result

  • VulcanBench v3

    Claude Fable 589.5%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • SWE Multilingual

    Claude Fable 5—
    Claude Fable 5.189.1%
    Source

    Not directly comparable

  • SWE Multimodal

    Claude Fable 5—
    Claude Fable 5.154.7%
    Source

    Not directly comparable

  • deepSwe

    Claude Fable 5—
    Claude Fable 5.167.4%
    Source

    Not directly comparable

  • ProgramBench

    Claude Fable 5—
    Claude Fable 5.187.6%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-1

    Claude Fable 5—
    Claude Fable 5.197.50%
    Source

    Not directly comparable

  • ARC-AGI-2

    Claude Fable 5—
    Claude Fable 5.190%
    Source

    Not directly comparable

Knowledge

  • HLE

    Claude Fable 5—
    Claude Fable 5.165%
    Source

    Not directly comparable

  • HLE w/o tools

    Claude Fable 5—
    Claude Fable 5.160.9%
    Source

    Not directly comparable

Multimodal

  • Blueprint-Bench 2

    Claude Fable 538.6%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • OfficeQA Pro

    Claude Fable 557.9%
    Source
    Claude Fable 5.1—

    Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5 or Claude Fable 5.1?

Claude Fable 5.1 has the higher public score estimate, 82.74 versus 82.49, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Fable 5 or Claude Fable 5.1?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Fable 5 or Claude Fable 5.1?

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, Claude Fable 5 or Claude Fable 5.1?

For the stated presets, chat costs $0.035 on Claude Fable 5 and $0.035 on Claude Fable 5.1; repository review costs $0.65 and $0.65; the cache-heavy agent loop costs $0.9 and $0.75. Costs use the listed standard API rates.

Which has the larger context window, Claude Fable 5 or Claude Fable 5.1?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 1, 2026

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