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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
Model A
Apodex 1.1

Apodex

56.11/100

Estimated · Public rank #98

90% interval 44.6–67.6

Apodex 1.1 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

Claude Fable 5.1 has the higher public score, 82.74 versus 56.11, and the 90% score intervals do not overlap.

1 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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

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

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    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

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

    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
1
Apodex 1.1 only
9
Claude Fable 5.1 only
17
Like-for-like categories
1 / 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.

Knowledge

Like-for-like
Apodex 1.1
56.1
Claude Fable 5.1
65.0
Weighted basis
1 vs 1 rows
Reading
Claude Fable 5.1 leads

Agentic

Not comparable
Apodex 1.1
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Apodex 1.1
77.7
Claude Fable 5.1
81.2
Weighted basis
1 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
Apodex 1.1
Not measured
Claude Fable 5.1
90.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Math

Not comparable
Apodex 1.1
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Apodex 1.1
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Apodex 1.1
Not measured
Claude Fable 5.1
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Apodex 1.1
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

Apodex 1.1
API rate not published
Fit state unavailable
Claude Fable 5.1
$0.035
Fits in one request

Apodex 1.1 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Apodex 1.1
API rate not published
Fit state unavailable
Claude Fable 5.1
$0.65
Fits in one request

Apodex 1.1 has no comparable published API token rate.

Cache-heavy agent loop

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

Apodex 1.1
API rate not published
Fit state unavailable
Cached-input rate unavailable
Claude Fable 5.1
$0.75
Fits in one request

Apodex 1.1 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.

Cached-input rate

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

Apodex 1.1

No comparable hosted API rate

Apodex pricing

Claude Fable 5.1

$0.25 per 1M cached input tokens

Anthropic Fable 5.1 launch

Documented inputs

Apodex 1.1

Not sourced

Claude Fable 5.1

Not sourced

Documented outputs

Apodex 1.1

Not sourced

Claude Fable 5.1

Not sourced

Reasoning profile

Apodex 1.1

Reasoning

Claude Fable 5.1

Reasoning

Weight access

Apodex 1.1

Proprietary

Claude Fable 5.1

Proprietary

License

Apodex 1.1

Proprietary

Claude Fable 5.1

Proprietary

Release date

Apodex 1.1

2026-08-24

Claude Fable 5.1

2026-09-01

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 5.1 has the higher public score, 82.74 versus 56.11, and the 90% score intervals do not overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
A complete documented context comparison is not available.

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 evidence27 rows

Agentic

  • Terminal-Bench 2.1

    Apodex 1.170.8%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • HLE w/ tools

    Apodex 1.156.1%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • APEX-Agents

    Apodex 1.138.5%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • DeepSearchQA

    Apodex 1.192.4%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • Terminal-Bench 4.0

    Apodex 1.1—
    Claude Fable 5.155.80%
    Source

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Apodex 1.1—
    Claude Fable 5.152.6%
    Source

    Not directly comparable

  • OSWorld 2.0

    Apodex 1.1—
    Claude Fable 5.141.7%
    Source

    Not directly comparable

  • AutomationBench

    Apodex 1.1—
    Claude Fable 5.131.4%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Apodex 1.1—
    Claude Fable 5.177.8%
    Source

    Not directly comparable

  • Toolathlon Verified Pass@3

    Apodex 1.1—
    Claude Fable 5.181.5%
    Source

    Not directly comparable

  • Toolathlon Verified Pass³

    Apodex 1.1—
    Claude Fable 5.173.1%
    Source

    Not directly comparable

  • Toolathlon Verified avg. turns

    Apodex 1.1—
    Claude Fable 5.123.7 turns
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Apodex 1.170.8%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • SWE-bench Verified

    Apodex 1.177.7%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • SWE-bench Pro

    Apodex 1.1—
    Claude Fable 5.181.2%
    Source

    Not directly comparable

  • SWE Multilingual

    Apodex 1.1—
    Claude Fable 5.189.1%
    Source

    Not directly comparable

  • SWE Multimodal

    Apodex 1.1—
    Claude Fable 5.154.7%
    Source

    Not directly comparable

  • deepSwe

    Apodex 1.1—
    Claude Fable 5.167.4%
    Source

    Not directly comparable

  • ProgramBench

    Apodex 1.1—
    Claude Fable 5.187.6%
    Source

    Not directly comparable

  • cursorBench32

    Apodex 1.1—
    Claude Fable 5.173.4%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-1

    Apodex 1.1—
    Claude Fable 5.197.50%
    Source

    Not directly comparable

  • ARC-AGI-2

    Apodex 1.1—
    Claude Fable 5.190%
    Source

    Not directly comparable

Knowledge

  • HLE

    Apodex 1.156.1%
    Source
    Claude Fable 5.165%
    Source

    Claude Fable 5.1 leads this result

  • FrontierScience Research

    Apodex 1.163.3%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Apodex 1.135.3%
    Source
    Claude Fable 5.1—

    Not directly comparable

  • HLE w/o tools

    Apodex 1.1—
    Claude Fable 5.160.9%
    Source

    Not directly comparable

Math

  • IMO 2026

    Apodex 1.131/42
    Source
    Claude Fable 5.1—

    Not directly comparable

Frequently asked questions

Which is better, Apodex 1.1 or Claude Fable 5.1?

Claude Fable 5.1 has the higher public score, 82.74 versus 56.11, 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, Apodex 1.1 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, Apodex 1.1 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, Apodex 1.1 or Claude Fable 5.1?

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, Apodex 1.1 or Claude Fable 5.1?

A complete documented context-window comparison is not available.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 1, 2026

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