Model A

Anthropic

80.9/100

Supported · Public rank #3

90% interval 78.7–83.1

Claude Fable 5 vs Qwen3.6-27B

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

Model B

Qwen3.6-27B

Alibaba

52.72/100

Estimated · Public rank #120

90% interval 47.0–58.5

Decision reading

Claude Fable 5 has the higher public score, 80.9 versus 52.72, 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.

Coding work
Code generation, repair, and software-engineering tasks
Claude Fable 5
Claude Fable 5 leads on the public coding lane, 76.9 to 42.6, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Agentic work
Tool use, computer use, and multi-step task completion
Claude Fable 5
Claude Fable 5 leads on the public agentic lane, 74.8 to 33.9, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
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

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.

14 Claude Fable 5 only

4 Shared

34 Qwen3.6-27B only

Shared results: 4
Claude Fable 5 only: 14
Qwen3.6-27B only: 34
Like-for-like categories: 2 / 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.

Agentic

Like-for-like

Claude Fable 5: 74.8; Supported · #3/151
Qwen3.6-27B: 33.9; Supported · #133/151
Basis: BenchAlign lane · 4 vs 6 public rows
Reading: Claude Fable 5 leads

Coding

Like-for-like

Claude Fable 5: 76.9; Supported · #2/183
Qwen3.6-27B: 42.6; Supported · #128/183
Basis: BenchAlign lane · 10 vs 6 public rows
Reading: Claude Fable 5 leads

Knowledge

Directional only

Claude Fable 5: 83.5; Supported · #2/181
Qwen3.6-27B: 49.0; Estimated · #95/181
Basis: BenchAlign lane · 2 vs 6 public rows
Reading: Directional only

Instruction following

Directional only

Claude Fable 5: 78.3; #54/120
Qwen3.6-27B: 82.2; #50/120
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Directional only

Reasoning

Not comparable

Claude Fable 5: 76.2; #11/22
Qwen3.6-27B: 73.7; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Fable 5: Not ranked
Qwen3.6-27B: 72.8; Unranked · 5 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Claude Fable 5: Not ranked
Qwen3.6-27B: 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
Qwen3.6-27B: 51.9; #35/48
Basis: Provisional lane · 1 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Fable 5 and Qwen3.6-27B
Category	Claude Fable 5	Qwen3.6-27B	Basis	Reading
Agentic	74.8Supported · #3/151	33.9Supported · #133/151	Like-for-likeBenchAlign lane · 4 vs 6 public rows	Claude Fable 5 leads
Coding	76.9Supported · #2/183	42.6Supported · #128/183	Like-for-likeBenchAlign lane · 10 vs 6 public rows	Claude Fable 5 leads
Knowledge	83.5Supported · #2/181	49.0Estimated · #95/181	Directional onlyBenchAlign lane · 2 vs 6 public rows	Directional only
Instruction following	78.3#54/120	82.2#50/120	Directional onlyProvisional lane · 0 vs 0 weighted rows	Directional only
Reasoning	76.2#11/22	73.7Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	72.8Unranked · 5 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multimodal	62.5Unranked · 2 rankable rows	51.9#35/48	Not comparableProvisional lane · 1 vs 2 weighted rows	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.

SWE-bench Pro
Coding
Claude Fable 5: 80%Qwen3.6-27B: 53.5%Normalized gap 26.5Claude Fable 5 source Qwen3.6-27B source
Terminal-Bench 2.0
Agentic
Claude Fable 5: 84.3%Qwen3.6-27B: 59.3%Normalized gap 25.0Claude Fable 5 source Qwen3.6-27B source
SWE-bench Verified
Coding
Claude Fable 5: 95%Qwen3.6-27B: 77.2%Normalized gap 17.8Claude Fable 5 source Qwen3.6-27B 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: $0.035; Fits in one request
Qwen3.6-27B: Self-hosted; infrastructure cost varies; Fits in one request

Qwen3.6-27B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5: $0.65; Fits in one request
Qwen3.6-27B: Self-hosted; infrastructure cost varies; Fits in one request

Qwen3.6-27B 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
Qwen3.6-27B: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable

Qwen3.6-27B 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 5Qwen3.6-27B

Context window

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

Claude Fable 5

Anthropic model overview

Qwen3.6-27B

262K

API model ID

Claude Fable 5

claude-fable-5

Anthropic model overview

Qwen3.6-27B

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 per 1M cached input tokens

Claude API pricing

Qwen3.6-27B

No comparable hosted API rate

Documented inputs

Claude Fable 5

text, image

Anthropic model overview

Qwen3.6-27B

Not sourced

Documented outputs

Claude Fable 5

text

Anthropic model overview

Qwen3.6-27B

Not sourced

Provider availability

Claude Fable 5

Generally Available · Claude API

Anthropic model overview

Qwen3.6-27B

Not sourced

Reasoning profile

Claude Fable 5

Reasoning

Qwen3.6-27B

Reasoning

Weight access

Claude Fable 5

Proprietary

Qwen3.6-27B

Open Weight

License

Claude Fable 5

Proprietary

Qwen3.6-27B

Open Weight

Release date

Claude Fable 5

2026-06-09

Qwen3.6-27B

2026-04-21

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 52.72, 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.

Self-host vs API cost

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

Claude Fable 5

API / mo$0

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Qwen3.6-27B

API / mo$0

Self-host / mo$429

Break-even—

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 evidence52 rows

Agentic

Terminal-Bench 3.0
Claude Fable 534.0%
Source
Qwen3.6-27B—
Not directly comparable
Terminal-Bench 2.0
Claude Fable 584.3%
Source
Qwen3.6-27B59.3%
Source
Claude Fable 5 leads this result
OSWorld-Verified
Claude Fable 585%
Source
Qwen3.6-27B—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Fable 580.5%
Source
Qwen3.6-27B—
Not directly comparable
Claw-Eval
Claude Fable 5—
Qwen3.6-27B72.4%
Source
Not directly comparable
QwenClawBench
Claude Fable 5—
Qwen3.6-27B53.4%
Source
Not directly comparable
QwenWebBench
Claude Fable 5—
Qwen3.6-27B1487
Source
Not directly comparable
AndroidWorld
Claude Fable 5—
Qwen3.6-27B70.3%
Source
Not directly comparable
Gert Labs
Claude Fable 5—
Qwen3.6-27B54.84%
Source
Not directly comparable

Coding

SWE-bench Verified
Claude Fable 595%
Source
Qwen3.6-27B77.2%
Source
Claude Fable 5 leads this result
SWE-bench Pro
Claude Fable 580%
Source
Qwen3.6-27B53.5%
Source
Claude Fable 5 leads this result
FrontierSWE v2
Claude Fable 548.0%
Source
Qwen3.6-27B—
Not directly comparable
FrontierCode 1.1 Main
Claude Fable 553.5%
Source
Qwen3.6-27B—
Not directly comparable
Terminal-Bench 2.0
Claude Fable 584.3%
Source
Qwen3.6-27B59.3%
Source
Claude Fable 5 leads this result
cursorBench31
Claude Fable 570.6%
Source
Qwen3.6-27B—
Not directly comparable
cursorBench32
Claude Fable 570.5%
Source
Qwen3.6-27B—
Not directly comparable
VulcanBench v3
Claude Fable 589.5%
Source
Qwen3.6-27B—
Not directly comparable
LiveCodeBench (Vals)
Claude Fable 589.8%
Source
Qwen3.6-27B—
Not directly comparable
SWE-bench (Vals)
Claude Fable 595.0%
Source
Qwen3.6-27B—
Not directly comparable
SWE Multilingual
Claude Fable 5—
Qwen3.6-27B71.3%
Source
Not directly comparable
LiveCodeBench
Claude Fable 5—
Qwen3.6-27B83.9%
Source
Not directly comparable
NL2Repo
Claude Fable 5—
Qwen3.6-27B36.2%
Source
Not directly comparable

Knowledge

GPQA Diamond (Vals)
Claude Fable 593.2%
Source
Qwen3.6-27B—
Not directly comparable
MMLU-Pro (Vals)
Claude Fable 591.5%
Source
Qwen3.6-27B—
Not directly comparable
MMLU-Pro
Claude Fable 5—
Qwen3.6-27B86.2%
Source
Not directly comparable
MMLU-Redux
Claude Fable 5—
Qwen3.6-27B93.5%
Source
Not directly comparable
SuperGPQA
Claude Fable 5—
Qwen3.6-27B66%
Source
Not directly comparable
C-Eval
Claude Fable 5—
Qwen3.6-27B91.4%
Source
Not directly comparable
GPQA
Claude Fable 5—
Qwen3.6-27B87.8%
Source
Not directly comparable
HLE
Claude Fable 5—
Qwen3.6-27B24%
Source
Not directly comparable

Math

HMMT Feb 2025
Claude Fable 5—
Qwen3.6-27B93.8%
Source
Not directly comparable
HMMT Nov 2025
Claude Fable 5—
Qwen3.6-27B90.7%
Source
Not directly comparable
HMMT Feb 2026
Claude Fable 5—
Qwen3.6-27B84.3%
Source
Not directly comparable
MMAnswerBench
Claude Fable 5—
Qwen3.6-27B80.8%
Source
Not directly comparable
AIME26
Claude Fable 5—
Qwen3.6-27B94.1%
Source
Not directly comparable

Multimodal

Blueprint-Bench 2
Claude Fable 538.6%
Source
Qwen3.6-27B—
Not directly comparable
OfficeQA Pro
Claude Fable 557.9%
Source
Qwen3.6-27B—
Not directly comparable
MMMU
Claude Fable 5—
Qwen3.6-27B82.9%
Source
Not directly comparable
MMMU-Pro
Claude Fable 5—
Qwen3.6-27B75.8%
Source
Not directly comparable
RealWorldQA
Claude Fable 5—
Qwen3.6-27B84.1%
Source
Not directly comparable
DynaMath
Claude Fable 5—
Qwen3.6-27B85.6%
Source
Not directly comparable
MStar
Claude Fable 5—
Qwen3.6-27B81.4%
Source
Not directly comparable
SimpleVQA
Claude Fable 5—
Qwen3.6-27B56.1%
Source
Not directly comparable
CharXiv
Claude Fable 5—
Qwen3.6-27B78.4%
Source
Not directly comparable
CC-OCR
Claude Fable 5—
Qwen3.6-27B81.2%
Source
Not directly comparable
CountBench
Claude Fable 5—
Qwen3.6-27B97.8%
Source
Not directly comparable
RefCOCO (avg)
Claude Fable 5—
Qwen3.6-27B92.5%
Source
Not directly comparable
ERQA
Claude Fable 5—
Qwen3.6-27B62.5%
Source
Not directly comparable
Video-MME (with subtitle)
Claude Fable 5—
Qwen3.6-27B87.7%
Source
Not directly comparable
VideoMMMU
Claude Fable 5—
Qwen3.6-27B84.4%
Source
Not directly comparable
MLVU (M-Avg)
Claude Fable 5—
Qwen3.6-27B86.6%
Source
Not directly comparable
V*
Claude Fable 5—
Qwen3.6-27B94.7%
Source
Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5 or Qwen3.6-27B?

Claude Fable 5 has the higher public score, 80.9 versus 52.72, 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 Qwen3.6-27B?

Claude Fable 5 leads the public coding lane, 76.9 to 42.6, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Claude Fable 5 or Qwen3.6-27B?

Claude Fable 5 leads the public agentic tasks lane, 74.8 to 33.9, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Claude Fable 5 or Qwen3.6-27B?

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 Qwen3.6-27B?

Claude Fable 5 has the larger documented context window: 1M, compared with 262K.

Related comparisons

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Last updated September 4, 2026

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Claude Fable 5 vs Qwen3.6-27B

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Knowledge

Instruction following

Reasoning

Math

Multilingual

Multimodal

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Knowledge

Math

Multimodal

Frequently asked questions

Which is better, Claude Fable 5 or Qwen3.6-27B?

Which is better for coding, Claude Fable 5 or Qwen3.6-27B?

Which is better for agentic tasks, Claude Fable 5 or Qwen3.6-27B?

Which costs less, Claude Fable 5 or Qwen3.6-27B?

Which has the larger context window, Claude Fable 5 or Qwen3.6-27B?

Related comparisons

Watch Claude Fable 5 vs Qwen3.6-27B