Reasoning
Like-for-like- Claude Fable 5.1
- 90.0
- dots3-note Preview
- 81.4
- Weighted basis
- 1 vs 1 rows
- Reading
- Claude Fable 5.1 leads
Claude Fable 5.1 vs dots3-note Preview
Updated September 1, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Fable 5.1 has the higher public score estimate, 82.74 versus 68.69, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
5 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
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
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.
13 Claude Fable 5.1 only
5 Shared
26 dots3-note Preview only
- Shared results
- 5
- Claude Fable 5.1 only
- 13
- dots3-note Preview only
- 26
- Like-for-like categories
- 2 / 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.
Knowledge
Like-for-like- Claude Fable 5.1
- 65.0
- dots3-note Preview
- 52.6
- Weighted basis
- 1 vs 1 rows
- Reading
- Claude Fable 5.1 leads
Coding
Directional only- Claude Fable 5.1
- 81.2
- dots3-note Preview
- 71.7
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Agentic
Not comparable- Claude Fable 5.1
- Not measured
- dots3-note Preview
- 83.3
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Math
Not comparable- Claude Fable 5.1
- Not measured
- dots3-note Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Fable 5.1
- Not measured
- dots3-note Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Fable 5.1
- Not measured
- dots3-note Preview
- 79.1
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Fable 5.1
- Not measured
- dots3-note Preview
- 85.1
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
| Category | Claude Fable 5.1 | dots3-note Preview | Weighted basis | Reading |
|---|---|---|---|---|
| Reasoning | 90.0 | 81.4 | Like-for-like1 vs 1 rows | Claude Fable 5.1 leads |
| Knowledge | 65.0 | 52.6 | Like-for-like1 vs 1 rows | Claude Fable 5.1 leads |
| Coding | 81.2 | 71.7 | Directional only1 vs 2 rows | Directional only |
| Agentic | Not measured | 83.3 | Not comparable0 vs 1 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | 79.1 | Not comparable0 vs 1 rows | Not comparable |
| Instruction following | Not measured | 85.1 | Not comparable0 vs 2 rows | 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.
SWE-bench Pro
Coding
Claude Fable 5.1: 81.2%dots3-note Preview: 61%Normalized gap 20.2Claude Fable 5.1 source dots3-note Preview sourceHLE
Knowledge
Claude Fable 5.1: 65%dots3-note Preview: 52.6%Normalized gap 12.4Claude Fable 5.1 source dots3-note Preview sourceARC-AGI-2
Reasoning
Claude Fable 5.1: 90%dots3-note Preview: 81.4%Normalized gap 8.6Claude Fable 5.1 source dots3-note Preview source
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 5.1
- $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 5.1
- $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 5.1
- $0.75
- 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.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Fable 5.1dots3-note Preview
Context window
Maximum documented context; output-token limits may be lower.
Claude Fable 5.1
dots3-note Preview
API model ID
Claude Fable 5.1
claude-fable-5-1
Anthropic Fable 5.1 and Mythos 5.1 launchdots3-note Preview
Not sourced
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
$0.25 per 1M cached input tokens
Anthropic Fable 5.1 launchdots3-note Preview
No comparable hosted API rate
dots3-note Preview model cardDocumented inputs
Claude Fable 5.1
Not sourced
dots3-note Preview
Not sourced
Documented outputs
Claude Fable 5.1
Not sourced
dots3-note Preview
Not sourced
Provider availability
Claude Fable 5.1
Generally Available · Claude API, Claude products, AWS, Google Cloud, Microsoft Azure
Anthropic Fable 5.1 and Mythos 5.1 launchdots3-note Preview
Not sourced
Reasoning profile
Claude Fable 5.1
Reasoning
dots3-note Preview
Reasoning
Weight access
Claude Fable 5.1
Proprietary
dots3-note Preview
Open Weight
License
Claude Fable 5.1
Proprietary
dots3-note Preview
Open Weight
Release date
Claude Fable 5.1
2026-09-01
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 5.1 has the higher public score estimate, 82.74 versus 68.69, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- 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 evidence44 rows
Agentic
Terminal-Bench 4.0
Claude Fable 5.155.80%Sourcedots3-note Preview—Not directly comparable
Terminal-Bench-Science 0.1
Claude Fable 5.152.6%Sourcedots3-note Preview—Not directly comparable
OSWorld 2.0
Claude Fable 5.141.7%Sourcedots3-note Preview—Not directly comparable
AutomationBench
Claude Fable 5.131.4%Sourcedots3-note Preview—Not directly comparable
Toolathlon-Verified
Claude Fable 5.177.8%Sourcedots3-note Preview55.6%SourceClaude Fable 5.1 leads this result
Toolathlon Verified Pass@3
Claude Fable 5.181.5%Sourcedots3-note Preview—Not directly comparable
Toolathlon Verified Pass³
Claude Fable 5.173.1%Sourcedots3-note Preview—Not directly comparable
Toolathlon Verified avg. turns
Claude Fable 5.123.7 turnsSourcedots3-note Preview—Not directly comparable
Claw-Eval
Claude Fable 5.1—dots3-note Preview73.4%SourceNot directly comparable
Terminal-Bench 2.1
Claude Fable 5.1—dots3-note Preview75.1%SourceNot directly comparable
skillsBench
Claude Fable 5.1—dots3-note Preview52.8%SourceNot directly comparable
APEX-Agents
Claude Fable 5.1—dots3-note Preview30.8%SourceNot directly comparable
BrowseComp
Claude Fable 5.1—dots3-note Preview83.3%SourceNot directly comparable
HLE w/ tools
Claude Fable 5.1—dots3-note Preview52.6%SourceNot directly comparable
DeepSearchQA
Claude Fable 5.1—dots3-note Preview92.1%SourceNot directly comparable
WideResearch
Claude Fable 5.1—dots3-note Preview78.9%SourceNot directly comparable
Coding
SWE-bench Pro
Claude Fable 5.181.2%Sourcedots3-note Preview61%SourceClaude Fable 5.1 leads this result
SWE Multilingual
Claude Fable 5.189.1%Sourcedots3-note Preview75.7%SourceClaude Fable 5.1 leads this result
SWE Multimodal
Claude Fable 5.154.7%Sourcedots3-note Preview—Not directly comparable
deepSwe
Claude Fable 5.167.4%Sourcedots3-note Preview—Not directly comparable
ProgramBench
Claude Fable 5.187.6%Sourcedots3-note Preview—Not directly comparable
cursorBench32
Claude Fable 5.173.4%Sourcedots3-note Preview—Not directly comparable
Codeforces
Claude Fable 5.1—dots3-note Preview3056.0SourceNot directly comparable
LiveCodeBench v6
Claude Fable 5.1—dots3-note Preview91.5%SourceNot directly comparable
Terminal-Bench 2.1
Claude Fable 5.1—dots3-note Preview75.1%SourceNot directly comparable
SWE-bench Verified
Claude Fable 5.1—dots3-note Preview78.4%SourceNot directly comparable
NL2Repo
Claude Fable 5.1—dots3-note Preview49.8%SourceNot directly comparable
Reasoning
Knowledge
Math
IMOAnswerBench
Claude Fable 5.1—dots3-note Preview90.9%SourceNot directly comparable
Multimodal
SimpleVQA
Claude Fable 5.1—dots3-note Preview72.5%SourceNot directly comparable
MMMU-Pro
Claude Fable 5.1—dots3-note Preview79.1%SourceNot directly comparable
MathVision
Claude Fable 5.1—dots3-note Preview87.7%SourceNot directly comparable
ZeroBench
Claude Fable 5.1—dots3-note Preview19.0%SourceNot directly comparable
CharXiv w/o tools
Claude Fable 5.1—dots3-note Preview83.1%SourceNot directly comparable
GDP.pdf (no tools)
Claude Fable 5.1—dots3-note Preview60.7%SourceNot directly comparable
PerceptionBench
Claude Fable 5.1—dots3-note Preview53.4%SourceNot directly comparable
BabyVision
Claude Fable 5.1—dots3-note Preview50.0%SourceNot directly comparable
MMVU
Claude Fable 5.1—dots3-note Preview79.9%SourceNot directly comparable
VideoMMMU
Claude Fable 5.1—dots3-note Preview86.8%SourceNot directly comparable
Instruction following
Frequently asked questions
Which is better, Claude Fable 5.1 or dots3-note Preview?
Claude Fable 5.1 has the higher public score estimate, 82.74 versus 68.69, 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 5.1 or dots3-note Preview?
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 5.1 or dots3-note Preview?
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 5.1 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 5.1 or dots3-note Preview?
Claude Fable 5.1 has the larger documented context window: 1M, compared with 512K.
Related comparisons
Last updated September 1, 2026
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