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Model A
Claude Fable 5

Anthropic

80.9/100

Supported · Public rank #3

90% interval 78.783.1

Claude Fable 5 vs o1-preview

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
o1-preview

OpenAI

47.79/100

Supported · Public rank #155

90% interval 31.564.1

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 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

    Claude Fable 5

    Claude Fable 5 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Claude Fable 5

    Claude Fable 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

    Claude Fable 5

    Claude Fable 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

    O1-preview is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    O1-preview is not ranked on the public lane for agentic, so no winner is named for agentic.

    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. o1-preview does not fit this workload in one request. o1-preview 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 Fable 5 only
18
o1-preview only
0
Like-for-like categories
0 / 8

2 categories rest 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.

Coding

Directional only
Claude Fable 5
76.9
Supported · #2/183
o1-preview
45.8
Estimated · #104/183
Basis
BenchAlign lane · 10 vs 0 public rows
Reading
Directional only

Knowledge

Directional only
Claude Fable 5
83.5
Supported · #2/181
o1-preview
46.5
Estimated · #108/181
Basis
BenchAlign lane · 2 vs 0 public rows
Reading
Directional only

Agentic

Not comparable
Claude Fable 5
74.8
Supported · #3/151
o1-preview
Not ranked
Basis
BenchAlign lane · 4 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Fable 5
76.2
#11/22
o1-preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5
Not ranked
o1-preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5
Not ranked
o1-preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5
62.5
Unranked · 2 rankable rows
o1-preview
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Fable 5
78.3
#54/120
o1-preview
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.

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 Fable 5
$0.035
Fits in one request
o1-preview
$0.045
Fits in one request

Claude Fable 5 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
o1-preview
$0.93
Fits in one request

Claude Fable 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

Claude Fable 5
$0.9
Fits in one request
o1-preview
$3.90
Does not fit in one request
Cached input priced at the published list-input rate

o1-preview does not fit this workload in one request. o1-preview 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.

Context window

Maximum documented context; output-token limits may be lower.

Claude Fable 5

o1-preview

200K

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

o1-preview

Not published

Reasoning profile

Claude Fable 5

Reasoning

o1-preview

Reasoning

Weight access

Claude Fable 5

Proprietary

o1-preview

Proprietary

License

Claude Fable 5

Proprietary

o1-preview

Proprietary

Release date

Claude Fable 5

2026-06-09

o1-preview

2024-09-12

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.65 vs $0.93. Cache-heavy agent loop: $0.9 vs $3.90.
Context tradeoff
Claude Fable 5 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 evidence18 rows

Agentic

  • Terminal-Bench 3.0

    Claude Fable 534.0%
    Source
    o1-preview

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    o1-preview

    Not directly comparable

  • OSWorld-Verified

    Claude Fable 585%
    Source
    o1-preview

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 580.5%
    Source
    o1-preview

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Fable 595%
    Source
    o1-preview

    Not directly comparable

  • SWE-bench Pro

    Claude Fable 580%
    Source
    o1-preview

    Not directly comparable

  • FrontierSWE v2

    Claude Fable 548.0%
    Source
    o1-preview

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Fable 553.5%
    Source
    o1-preview

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    o1-preview

    Not directly comparable

  • cursorBench31

    Claude Fable 570.6%
    Source
    o1-preview

    Not directly comparable

  • cursorBench32

    Claude Fable 570.5%
    Source
    o1-preview

    Not directly comparable

  • VulcanBench v3

    Claude Fable 589.5%
    Source
    o1-preview

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Fable 589.8%
    Source
    o1-preview

    Not directly comparable

  • SWE-bench (Vals)

    Claude Fable 595.0%
    Source
    o1-preview

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Fable 593.2%
    Source
    o1-preview

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 591.5%
    Source
    o1-preview

    Not directly comparable

Multimodal

  • Blueprint-Bench 2

    Claude Fable 538.6%
    Source
    o1-preview

    Not directly comparable

  • OfficeQA Pro

    Claude Fable 557.9%
    Source
    o1-preview

    Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5 or o1-preview?

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 Fable 5 or o1-preview?

Claude Fable 5 scores higher for coding on the public lane, 76.9 to 45.8. O1-preview is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; 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 o1-preview?

O1-preview is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Fable 5 or o1-preview?

For the stated presets, chat costs $0.035 on Claude Fable 5 and $0.045 on o1-preview; repository review costs $0.65 and $0.93; the cache-heavy agent loop costs $0.9 and $3.90. o1-preview does not fit this workload in one request. o1-preview has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Fable 5 or o1-preview?

Claude Fable 5 has the larger documented context window: 1M, compared with 200K.

Related comparisons

Last updated September 4, 2026

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