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Radar

Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

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BenchLM
Anthropic logo
Model A
Claude 3.5 Sonnet

Anthropic

48.36/100

Estimated · Public rank #145

90% interval 36.9–59.9

Claude 3.5 Sonnet vs Claude Fable 5.1

Updated September 1, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Anthropic logo
Model B
Claude Fable 5.1

Anthropic

82.74/100

Estimated · Public rank #1

90% interval 71.2–94.3

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 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

    Claude Fable 5.1

    Claude Fable 5.1 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Claude 3.5 Sonnet

    Claude 3.5 Sonnet 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

    Claude 3.5 Sonnet

    Claude 3.5 Sonnet 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

    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

  • 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. Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

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
0
Claude 3.5 Sonnet only
4
Claude Fable 5.1 only
18
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
Claude 3.5 Sonnet
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude 3.5 Sonnet
49.0
Claude Fable 5.1
81.2
Weighted basis
1 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
Claude 3.5 Sonnet
Not measured
Claude Fable 5.1
90.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Claude 3.5 Sonnet
59.4
Claude Fable 5.1
65.0
Weighted basis
1 vs 1 rows
Reading
Not comparable

Math

Not comparable
Claude 3.5 Sonnet
1.6
Claude Fable 5.1
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude 3.5 Sonnet
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude 3.5 Sonnet
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude 3.5 Sonnet
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.

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

Claude 3.5 Sonnet
$0.0105
Fits in one request
Claude Fable 5.1
$0.035
Fits in one request

Claude 3.5 Sonnet has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude 3.5 Sonnet
$0.195
Fits in one request
Claude Fable 5.1
$0.65
Fits in one request

Claude 3.5 Sonnet 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 3.5 Sonnet
$0.81
Does not fit in one request
Cached input priced at the published list-input rate
Claude Fable 5.1
$0.75
Fits in one request

Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet 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.

Claude 3.5 Sonnet

Not published

Claude Fable 5.1

$0.25 per 1M cached input tokens

Anthropic Fable 5.1 launch

Documented inputs

Claude 3.5 Sonnet

Not sourced

Claude Fable 5.1

Not sourced

Documented outputs

Claude 3.5 Sonnet

Not sourced

Claude Fable 5.1

Not sourced

Reasoning profile

Claude 3.5 Sonnet

Non-Reasoning

Claude Fable 5.1

Reasoning

Weight access

Claude 3.5 Sonnet

Proprietary

Claude Fable 5.1

Proprietary

License

Claude 3.5 Sonnet

Proprietary

Claude Fable 5.1

Proprietary

Release date

Claude 3.5 Sonnet

2024-06-01

Claude Fable 5.1

2026-09-01

If you already use one of these models
Deployment change
Both entries list Anthropic as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.195 vs $0.65. Cache-heavy agent loop: $0.81 vs $0.75.
Context tradeoff
Claude Fable 5.1 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 evidence22 rows

Agentic

  • Terminal-Bench 4.0

    Claude 3.5 Sonnet—
    Claude Fable 5.155.80%
    Source

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude 3.5 Sonnet—
    Claude Fable 5.152.6%
    Source

    Not directly comparable

  • OSWorld 2.0

    Claude 3.5 Sonnet—
    Claude Fable 5.141.7%
    Source

    Not directly comparable

  • AutomationBench

    Claude 3.5 Sonnet—
    Claude Fable 5.131.4%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Claude 3.5 Sonnet—
    Claude Fable 5.177.8%
    Source

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude 3.5 Sonnet—
    Claude Fable 5.181.5%
    Source

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude 3.5 Sonnet—
    Claude Fable 5.173.1%
    Source

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude 3.5 Sonnet—
    Claude Fable 5.123.7 turns
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude 3.5 Sonnet49%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • SWE-bench Pro

    Claude 3.5 Sonnet—
    Claude Fable 5.181.2%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude 3.5 Sonnet—
    Claude Fable 5.189.1%
    Source

    Not directly comparable

  • SWE Multimodal

    Claude 3.5 Sonnet—
    Claude Fable 5.154.7%
    Source

    Not directly comparable

  • deepSwe

    Claude 3.5 Sonnet—
    Claude Fable 5.167.4%
    Source

    Not directly comparable

  • ProgramBench

    Claude 3.5 Sonnet—
    Claude Fable 5.187.6%
    Source

    Not directly comparable

  • cursorBench32

    Claude 3.5 Sonnet—
    Claude Fable 5.173.4%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-1

    Claude 3.5 Sonnet—
    Claude Fable 5.197.50%
    Source

    Not directly comparable

  • ARC-AGI-2

    Claude 3.5 Sonnet—
    Claude Fable 5.190%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude 3.5 Sonnet59.4%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • HLE

    Claude 3.5 Sonnet—
    Claude Fable 5.165%
    Source

    Not directly comparable

  • HLE w/o tools

    Claude 3.5 Sonnet—
    Claude Fable 5.160.9%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude 3.5 Sonnet2.069%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude 3.5 Sonnet0.000%
    Source
    Claude Fable 5.1—

    Not directly comparable

Frequently asked questions

Which is better, Claude 3.5 Sonnet or Claude Fable 5.1?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude 3.5 Sonnet or Claude Fable 5.1?

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, Claude 3.5 Sonnet 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 3.5 Sonnet or Claude Fable 5.1?

For the stated presets, chat costs $0.0105 on Claude 3.5 Sonnet and $0.035 on Claude Fable 5.1; repository review costs $0.195 and $0.65; the cache-heavy agent loop costs $0.81 and $0.75. Claude 3.5 Sonnet does not fit this workload in one request. Claude 3.5 Sonnet has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude 3.5 Sonnet or Claude Fable 5.1?

Claude Fable 5.1 has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 1, 2026

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