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BenchLM

Claude Fable 5 vs dots3-note Preview

Updated September 28, 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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Decision reading

Claude Fable 5 has the higher public score, 78.89 versus 62.64, 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.

Model A
Anthropic logo

Anthropic

78.89/100

Supported · Public rank #7

90% interval 75.9–81.9

Model B

Dots Studio

62.64/100

Estimated · Public rank #39

90% interval 52.8–72.5

Shared results
5
Claude Fable 5 only
16
dots3-note Preview only
26
Like-for-like categories
0 / 8
Supported: Claude Fable 5 · Estimated: dots3-note PreviewHow the comparison works

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
Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Dots3-note Preview is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited
  • Agentic work

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

    Not enough matched evidence

    Dots3-note Preview is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    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

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.

72.9Claude Fable 5—dots3-note Preview

Not comparable · BenchAlign v5.7

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 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

Directional only
Claude Fable 5
73.8
Supported · #4/117
dots3-note Preview
56.4
Estimated · #28/117
Basis
BenchAlign v5.7 lane · 5 vs 9 public rows
Reading
Directional only

Instruction following

Directional only
Claude Fable 5
75.7
#58/124
dots3-note Preview
85.2
#37/124
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Directional only

Coding

Not comparable
Claude Fable 5
72.9
Supported · #5/142
dots3-note Preview
Not ranked
Basis
BenchAlign v5.7 lane · 10 vs 7 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Fable 5
80.7
Unranked · 4 rankable rows
dots3-note Preview
72.9
Unranked · 1 rankable row
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5
62.6
Unranked · 2 rankable rows
dots3-note Preview
67.2
Unranked · 10 rankable rows
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Fable 5
81.7
Supported · #4/168
dots3-note Preview
Not ranked
Basis
BenchAlign v5.7 lane · 2 vs 1 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5
Not ranked
dots3-note Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5
Not ranked
dots3-note 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 v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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
dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request

dots3-note Preview has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5
$0.65
Fits in one request
dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request

dots3-note Preview has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Fable 5
$0.9
Fits in one request
dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

dots3-note Preview has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

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

dots3-note Preview

No comparable hosted API rate

dots3-note Preview model card

Provider availability

Claude Fable 5

Generally Available · Claude API

Anthropic model overview

dots3-note Preview

Not sourced

Reasoning profile

Claude Fable 5

Reasoning

dots3-note Preview

Reasoning

Weight access

Claude Fable 5

Proprietary

dots3-note Preview

Open Weight

License

Claude Fable 5

Proprietary

dots3-note Preview

Open Weight

Release date

Claude Fable 5

2026-06-09

dots3-note Preview

2026-08-14

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, 78.89 versus 62.64, and the 90% score intervals do not overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Claude Fable 5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Fable 5 or dots3-note Preview?

Claude Fable 5 has the higher public score, 78.89 versus 62.64, 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 dots3-note Preview?

Dots3-note Preview is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude Fable 5 or dots3-note Preview?

Claude Fable 5 scores higher for agentic tasks on the public lane, 73.8 to 56.4. Dots3-note Preview is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Fable 5 or dots3-note Preview?

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, Claude Fable 5 or dots3-note Preview?

Claude Fable 5 has the larger documented context window: 1M, compared with 512K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence47 rows

Agentic

  • Terminal-Bench 3.0

    Claude Fable 534.0%
    Source
    dots3-note Preview—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Fable 584.3%
    Source
    dots3-note Preview75.1%
    Source

    Claude Fable 5 leads this result

  • OSWorld-Verified

    Claude Fable 585%
    Source
    dots3-note Preview—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 580.5%
    Source
    dots3-note Preview—

    Not directly comparable

  • ApprenticeBench

    Claude Fable 534%
    Source
    dots3-note Preview—

    Not directly comparable

  • Claw-Eval

    Claude Fable 5—
    dots3-note Preview73.4%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Claude Fable 5—
    dots3-note Preview55.6%
    Source

    Not directly comparable

  • skillsBench

    Claude Fable 5—
    dots3-note Preview52.8%
    Source

    Not directly comparable

  • APEX-Agents

    Claude Fable 5—
    dots3-note Preview30.8%
    Source

    Not directly comparable

  • BrowseComp

    Claude Fable 5—
    dots3-note Preview83.3%
    Source

    Not directly comparable

  • HLE w/ tools

    Claude Fable 5—
    dots3-note Preview52.6%
    Source

    Not directly comparable

  • DeepSearchQA

    Claude Fable 5—
    dots3-note Preview92.1%
    Source

    Not directly comparable

  • WideResearch

    Claude Fable 5—
    dots3-note Preview78.9%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Fable 595%
    Source
    dots3-note Preview78.4%
    Source

    Claude Fable 5 leads this result

  • SWE-bench Pro

    Claude Fable 580%
    Source
    dots3-note Preview61%
    Source

    Claude Fable 5 leads this result

  • FrontierSWE v2

    Claude Fable 547.0%
    Source
    dots3-note Preview—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Fable 553.5%
    Source
    dots3-note Preview—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Fable 584.3%
    Source
    dots3-note Preview75.1%
    Source

    Claude Fable 5 leads this result

  • cursorBench31

    Claude Fable 570.6%
    Source
    dots3-note Preview—

    Not directly comparable

  • cursorBench32

    Claude Fable 570.5%
    Source
    dots3-note Preview—

    Not directly comparable

  • VulcanBench v3

    Claude Fable 589.5%
    Source
    dots3-note Preview—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Fable 589.8%
    Source
    dots3-note Preview—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Fable 595.0%
    Source
    dots3-note Preview—

    Not directly comparable

  • Codeforces

    Claude Fable 5—
    dots3-note Preview3056.0
    Source

    Not directly comparable

  • LiveCodeBench v6

    Claude Fable 5—
    dots3-note Preview91.5%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude Fable 5—
    dots3-note Preview75.7%
    Source

    Not directly comparable

  • NL2Repo

    Claude Fable 5—
    dots3-note Preview49.8%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-1

    Claude Fable 598.50%
    Source
    dots3-note Preview—

    Not directly comparable

  • ARC-AGI-2

    Claude Fable 589.2%
    Source
    dots3-note Preview81.4%
    Source

    Claude Fable 5 leads this result

Multimodal

  • Blueprint-Bench 2

    Claude Fable 538.6%
    Source
    dots3-note Preview—

    Not directly comparable

  • OfficeQA Pro

    Claude Fable 557.9%
    Source
    dots3-note Preview—

    Not directly comparable

  • SimpleVQA

    Claude Fable 5—
    dots3-note Preview72.5%
    Source

    Not directly comparable

  • MMMU-Pro

    Claude Fable 5—
    dots3-note Preview79.1%
    Source

    Not directly comparable

  • MathVision

    Claude Fable 5—
    dots3-note Preview87.7%
    Source

    Not directly comparable

  • ZeroBench

    Claude Fable 5—
    dots3-note Preview19.0%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Claude Fable 5—
    dots3-note Preview83.1%
    Source

    Not directly comparable

  • GDP.pdf (no tools)

    Claude Fable 5—
    dots3-note Preview60.7%
    Source

    Not directly comparable

  • PerceptionBench

    Claude Fable 5—
    dots3-note Preview53.4%
    Source

    Not directly comparable

  • BabyVision

    Claude Fable 5—
    dots3-note Preview50.0%
    Source

    Not directly comparable

  • MMVU

    Claude Fable 5—
    dots3-note Preview79.9%
    Source

    Not directly comparable

  • VideoMMMU

    Claude Fable 5—
    dots3-note Preview86.8%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Fable 593.2%
    Source
    dots3-note Preview—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 591.5%
    Source
    dots3-note Preview—

    Not directly comparable

  • HLE

    Claude Fable 5—
    dots3-note Preview52.6%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Claude Fable 5—
    dots3-note Preview80.4%
    Source

    Not directly comparable

  • IFEval

    Claude Fable 5—
    dots3-note Preview93.9%
    Source

    Not directly comparable

Math

  • IMOAnswerBench

    Claude Fable 5—
    dots3-note Preview90.9%
    Source

    Not directly comparable

47 public results · 5 shared

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Last updated September 28, 2026