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Claude Fable 5.1 vs Mistral Small 4

Updated October 17, 2026. Rank says Claude Fable 5.1 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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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.

Model A
Anthropic logo
Claude Fable 5.1

Anthropic

83.18/100

Supported · Public rank #4

90% interval 79.9–86.5

Model B
Mistral logo
Mistral Small 4

Mistral

34.71/100

Estimated · Public rank #156

Conditional range 25.0–44.4

Shared results
0
Claude Fable 5.1 only
33
Mistral Small 4 only
0
Like-for-like categories
0 / 8
Supported: Claude Fable 5.1 · Estimated: Mistral Small 4. Conditional ranges do not establish rank confidence.How 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 5.1

    Claude Fable 5.1 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Mistral Small 4

    Mistral Small 4 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Mistral Small 4

    Mistral Small 4 has the lower estimated token cost for this stated workload. Mistral Small 4 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback
Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    Mistral Small 4

    Mistral Small 4 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

    Mistral Small 4 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

    Mistral Small 4 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

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.

76.8Claude Fable 5.118.6Mistral Small 4

Directional only · BenchAlign v5.8

Claude Fable 5.1 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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

Open the coding leaderboardShortlist models for this job
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.

3 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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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 5.1
80.9
Supported · #2/128
Mistral Small 4
14.1
Estimated · #116/128
Basis
BenchAlign v5.8 lane · 12 vs 0 public rows
Reading
Directional only

Coding

Directional only
Claude Fable 5.1
76.8
Supported · #3/150
Mistral Small 4
18.6
Estimated · #122/150
Basis
BenchAlign v5.8 lane · 11 vs 0 public rows
Reading
Directional only

Knowledge

Directional only
Claude Fable 5.1
86.9
Supported · #2/184
Mistral Small 4
34.2
Estimated · #138/184
Basis
BenchAlign v5.8 lane · 4 vs 0 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Fable 5.1
85.2
#4/28
Mistral Small 4
60.0
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5.1
Not ranked
Mistral Small 4
48.2
Unranked · 1 rankable row
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5.1
Not ranked
Mistral Small 4
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Fable 5.1
Not ranked
Mistral Small 4
57.1
#85/148
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5.1
96.8
Unranked · 2 rankable rows
Mistral Small 4
Not ranked
Basis
Provisional lane · 2 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 v5.8) 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 5.1
$0.035
Fits in one request
Mistral Small 4
$0.00045
Fits in one request

Mistral Small 4 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5.1
$0.65
Fits in one request
Mistral Small 4
$0.0093
Fits in one request

Mistral Small 4 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 5.1
$0.75
Fits in one request
Mistral Small 4
$0.039
Fits in one request
Cached input priced at the published list-input rate

Mistral Small 4 has the lower modeled cost

Mistral Small 4 has no published cached-input rate, so cached tokens use its listed input 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

$0.25 per 1M cached input tokens

Anthropic Fable 5.1 launch

Mistral Small 4

Not published

Documented inputs

Claude Fable 5.1

Not sourced

Mistral Small 4

Not sourced

Documented outputs

Claude Fable 5.1

Not sourced

Mistral Small 4

Not sourced

Reasoning profile

Claude Fable 5.1

Reasoning

Mistral Small 4

Non-Reasoning

Weight access

Claude Fable 5.1

Proprietary

Mistral Small 4

Open Weight

License

Claude Fable 5.1

Proprietary

Mistral Small 4

Open Weight

Release date

Claude Fable 5.1

2026-09-01

Mistral Small 4

2026-03-16

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 $0.0093. Cache-heavy agent loop: $0.75 vs $0.039.
Context tradeoff
Claude Fable 5.1 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Fable 5.1 or Mistral Small 4?

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 5.1 or Mistral Small 4?

Claude Fable 5.1 scores higher for coding on the public lane, 76.8 to 18.6. Mistral Small 4 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 5.1 or Mistral Small 4?

Claude Fable 5.1 scores higher for agentic tasks on the public lane, 80.9 to 14.1. Mistral Small 4 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 5.1 or Mistral Small 4?

For the stated presets, chat costs $0.035 on Claude Fable 5.1 and $0.00045 on Mistral Small 4; repository review costs $0.65 and $0.0093; the cache-heavy agent loop costs $0.75 and $0.039. Mistral Small 4 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Fable 5.1 or Mistral Small 4?

Claude Fable 5.1 has the larger documented context window: 1M, compared with 256K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Claude Fable 5.1
API / mo$45,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Mistral Small 4
API / mo$563
Self-host / mo$3,495
Break-even409M/day
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence33 rows

Agentic

  • Terminal-Bench 4.0

    Claude Fable 5.155.80%
    Source
    Mistral Small 4—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Fable 5.152.6%
    Source
    Mistral Small 4—

    Not directly comparable

  • OSWorld 2.0

    Claude Fable 5.141.7%
    Source
    Mistral Small 4—

    Not directly comparable

  • AutomationBench

    Claude Fable 5.131.4%
    Source
    Mistral Small 4—

    Not directly comparable

  • Toolathlon-Verified

    Claude Fable 5.177.8%
    Source
    Mistral Small 4—

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Fable 5.181.5%
    Source
    Mistral Small 4—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Fable 5.173.1%
    Source
    Mistral Small 4—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Fable 5.123.7 turns
    Source
    Mistral Small 4—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 5.185.0%
    Source
    Mistral Small 4—

    Not directly comparable

  • ApprenticeBench

    Claude Fable 5.172%
    Source
    Mistral Small 4—

    Not directly comparable

  • CWE-bench v1

    Claude Fable 5.158.0%
    Source
    Mistral Small 4—

    Not directly comparable

  • MazeBench

    Claude Fable 5.110%
    Source
    Mistral Small 4—

    Not directly comparable

Coding

  • Bug Hunt Bench

    Claude Fable 5.143.0 fixes
    Source
    Mistral Small 4—

    Not directly comparable

  • SWE-bench Pro

    Claude Fable 5.181.2%
    Source
    Mistral Small 4—

    Not directly comparable

  • SWE Multilingual

    Claude Fable 5.189.1%
    Source
    Mistral Small 4—

    Not directly comparable

  • SWE Multimodal

    Claude Fable 5.154.7%
    Source
    Mistral Small 4—

    Not directly comparable

  • DeepSWE

    Claude Fable 5.167.4%
    Source
    Mistral Small 4—

    Not directly comparable

  • FrontierSWE v2

    Claude Fable 5.156.3%
    Source
    Mistral Small 4—

    Not directly comparable

  • ProgramBench

    Claude Fable 5.187.6%
    Source
    Mistral Small 4—

    Not directly comparable

  • CursorBench 3.2

    Claude Fable 5.173.4%
    Source
    Mistral Small 4—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Fable 5.190.5%
    Source
    Mistral Small 4—

    Not directly comparable

  • CursorBench 4.0

    Claude Fable 5.151.8%
    Source
    Mistral Small 4—

    Not directly comparable

  • PostTrainBench v1.1

    Claude Fable 5.140.2%
    Source
    Mistral Small 4—

    Not directly comparable

Reasoning

  • ARC-AGI-1

    Claude Fable 5.197.50%
    Source
    Mistral Small 4—

    Not directly comparable

  • ARC-AGI-2

    Claude Fable 5.190%
    Source
    Mistral Small 4—

    Not directly comparable

  • GraphWalks BFS 256K–1M

    Claude Fable 5.165.0%
    Source
    Mistral Small 4—

    Not directly comparable

Knowledge

  • HLE

    Claude Fable 5.165%
    Source
    Mistral Small 4—

    Not directly comparable

  • HLE w/o tools

    Claude Fable 5.160.9%
    Source
    Mistral Small 4—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Fable 5.193.4%
    Source
    Mistral Small 4—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 5.192.4%
    Source
    Mistral Small 4—

    Not directly comparable

Instruction following

  • Gray Swan IPI (15 attempts)

    Claude Fable 5.11.0%
    Source
    Mistral Small 4—

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude Fable 5.190.175%
    Source
    Mistral Small 4—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Fable 5.187.805%
    Source
    Mistral Small 4—

    Not directly comparable

33 public results · 0 shared

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Last updated October 17, 2026