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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 MAI-Thinking-1

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

Microsoft logo
Model B
MAI-Thinking-1

Microsoft

52.27/100

Estimated · Public rank #123

90% interval 42.462.1

Decision reading

Claude Fable 5 has the higher public score, 80.9 versus 52.27, and the 90% score intervals do not overlap.

4 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

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    MAI-Thinking-1 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

    MAI-Thinking-1 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

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
4
Claude Fable 5 only
14
MAI-Thinking-1 only
10
Like-for-like categories
0 / 8

4 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.

Agentic

Directional only
Claude Fable 5
74.8
Supported · #3/151
MAI-Thinking-1
51.7
Estimated · #53/151
Basis
BenchAlign lane · 4 vs 1 public rows
Reading
Directional only

Coding

Directional only
Claude Fable 5
76.9
Supported · #2/183
MAI-Thinking-1
51.8
Estimated · #60/183
Basis
BenchAlign lane · 10 vs 4 public rows
Reading
Directional only

Knowledge

Directional only
Claude Fable 5
83.5
Supported · #2/181
MAI-Thinking-1
53.3
Estimated · #68/181
Basis
BenchAlign lane · 2 vs 4 public rows
Reading
Directional only

Instruction following

Directional only
Claude Fable 5
78.3
#54/120
MAI-Thinking-1
94.7
#1/120
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Directional only

Reasoning

Not comparable
Claude Fable 5
76.2
#11/22
MAI-Thinking-1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5
Not ranked
MAI-Thinking-1
73.4
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5
Not ranked
MAI-Thinking-1
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
MAI-Thinking-1
Not ranked
Basis
Provisional lane · 1 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.

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

Claude Fable 5
$0.035
Fits in one request
MAI-Thinking-1
API rate not published
Fits in one request

MAI-Thinking-1 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5
$0.65
Fits in one request
MAI-Thinking-1
API rate not published
Fits in one request

MAI-Thinking-1 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
MAI-Thinking-1
API rate not published
Fits in one request
Cached-input rate unavailable

MAI-Thinking-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.

Context window

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

Claude Fable 5

MAI-Thinking-1

256K

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

MAI-Thinking-1

No comparable hosted API rate

Reasoning profile

Claude Fable 5

Reasoning

MAI-Thinking-1

Reasoning

Weight access

Claude Fable 5

Proprietary

MAI-Thinking-1

Proprietary

License

Claude Fable 5

Proprietary

MAI-Thinking-1

Proprietary

Release date

Claude Fable 5

2026-06-09

MAI-Thinking-1

2026-06-02

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, 80.9 versus 52.27, 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.

Benchmark evidence

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

Browse raw public benchmark evidence28 rows

Agentic

  • Terminal-Bench 3.0

    Claude Fable 534.0%
    Source
    MAI-Thinking-1

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    MAI-Thinking-146%
    Source

    Claude Fable 5 leads this result

  • OSWorld-Verified

    Claude Fable 585%
    Source
    MAI-Thinking-1

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 580.5%
    Source
    MAI-Thinking-1

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Fable 595%
    Source
    MAI-Thinking-173.5%
    Source

    Claude Fable 5 leads this result

  • SWE-bench Pro

    Claude Fable 580%
    Source
    MAI-Thinking-152.8%
    Source

    Claude Fable 5 leads this result

  • FrontierSWE v2

    Claude Fable 548.0%
    Source
    MAI-Thinking-1

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Fable 553.5%
    Source
    MAI-Thinking-1

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    MAI-Thinking-146.0%
    Source

    Claude Fable 5 leads this result

  • cursorBench31

    Claude Fable 570.6%
    Source
    MAI-Thinking-1

    Not directly comparable

  • cursorBench32

    Claude Fable 570.5%
    Source
    MAI-Thinking-1

    Not directly comparable

  • VulcanBench v3

    Claude Fable 589.5%
    Source
    MAI-Thinking-1

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Fable 589.8%
    Source
    MAI-Thinking-1

    Not directly comparable

  • SWE-bench (Vals)

    Claude Fable 595.0%
    Source
    MAI-Thinking-1

    Not directly comparable

  • LiveCodeBench v6

    Claude Fable 5
    MAI-Thinking-187.7%
    Source

    Not directly comparable

Reasoning

  • Graphwalks BFS 128K

    Claude Fable 5
    MAI-Thinking-190%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Fable 593.2%
    Source
    MAI-Thinking-1

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 591.5%
    Source
    MAI-Thinking-1

    Not directly comparable

  • GPQA

    Claude Fable 5
    MAI-Thinking-184.2%
    Source

    Not directly comparable

  • GPQA-D

    Claude Fable 5
    MAI-Thinking-184.2%
    Source

    Not directly comparable

  • MMLU-Pro

    Claude Fable 5
    MAI-Thinking-185%
    Source

    Not directly comparable

  • SimpleQA

    Claude Fable 5
    MAI-Thinking-131%
    Source

    Not directly comparable

Math

  • AIME 2025

    Claude Fable 5
    MAI-Thinking-197%
    Source

    Not directly comparable

  • AIME26

    Claude Fable 5
    MAI-Thinking-194.5%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Claude Fable 5
    MAI-Thinking-184.9%
    Source

    Not directly comparable

Multimodal

  • Blueprint-Bench 2

    Claude Fable 538.6%
    Source
    MAI-Thinking-1

    Not directly comparable

  • OfficeQA Pro

    Claude Fable 557.9%
    Source
    MAI-Thinking-1

    Not directly comparable

Instruction following

  • IFBench

    Claude Fable 5
    MAI-Thinking-185%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5 or MAI-Thinking-1?

Claude Fable 5 has the higher public score, 80.9 versus 52.27, 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 MAI-Thinking-1?

Claude Fable 5 scores higher for coding on the public lane, 76.9 to 51.8. MAI-Thinking-1 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 MAI-Thinking-1?

Claude Fable 5 scores higher for agentic tasks on the public lane, 74.8 to 51.7. MAI-Thinking-1 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 MAI-Thinking-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, Claude Fable 5 or MAI-Thinking-1?

Claude Fable 5 has the larger documented context window: 1M, compared with 256K.

Related comparisons

Last updated September 4, 2026

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