Model A

Anthropic

82.74/100

Estimated · Public rank #1

90% interval 71.2–94.3

Claude Fable 5.1 vs Qwen3.5 397B

Updated September 1, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Qwen3.5 397B

Alibaba

57.75/100

Estimated · Public rank #88

90% interval 46.2–69.3

Decision reading

Claude Fable 5.1 has the higher public score, 82.74 versus 57.75, and the 90% score intervals do not overlap.

2 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
Chat turn cost
1K fresh input + 500 output tokens
Qwen3.5 397B
Qwen3.5 397B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates

Show secondary and unsupported calls

Repository review cost
50K fresh input + 3K output tokens
Qwen3.5 397B
Qwen3.5 397B 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
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
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

What is actually comparable

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

16 Claude Fable 5.1 only

2 Shared

36 Qwen3.5 397B only

Shared results: 2
Claude Fable 5.1 only: 16
Qwen3.5 397B only: 36
Like-for-like categories: 0 / 8

2 categories use 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.

Coding

Directional only

Claude Fable 5.1: 81.2
Qwen3.5 397B: 66.5
Weighted basis: 1 vs 2 rows
Reading: Directional only

Knowledge

Directional only

Claude Fable 5.1: 65.0
Qwen3.5 397B: 56.6
Weighted basis: 1 vs 4 rows
Reading: Directional only

Agentic

Not comparable

Claude Fable 5.1: Not measured
Qwen3.5 397B: 56.5
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Reasoning

Not comparable

Claude Fable 5.1: 90.0
Qwen3.5 397B: 63.2
Weighted basis: 1 vs 1 rows
Reading: Not comparable

Math

Not comparable

Claude Fable 5.1: Not measured
Qwen3.5 397B: 90.6
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Multilingual

Not comparable

Claude Fable 5.1: Not measured
Qwen3.5 397B: 84.7
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Multimodal

Not comparable

Claude Fable 5.1: Not measured
Qwen3.5 397B: 79.6
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Instruction following

Not comparable

Claude Fable 5.1: Not measured
Qwen3.5 397B: 92.6
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Claude Fable 5.1 and Qwen3.5 397B
Category	Claude Fable 5.1	Qwen3.5 397B	Weighted basis	Reading
Coding	81.2	66.5	Directional only1 vs 2 rows	Directional only
Knowledge	65.0	56.6	Directional only1 vs 4 rows	Directional only
Agentic	Not measured	56.5	Not comparable0 vs 2 rows	Not comparable
Reasoning	90.0	63.2	Not comparable1 vs 1 rows	Not comparable
Math	Not measured	90.6	Not comparable0 vs 2 rows	Not comparable
Multilingual	Not measured	84.7	Not comparable0 vs 1 rows	Not comparable
Multimodal	Not measured	79.6	Not comparable0 vs 2 rows	Not comparable
Instruction following	Not measured	92.6	Not comparable0 vs 1 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.

HLE
Knowledge
Claude Fable 5.1: 65%Qwen3.5 397B: 28.7%Normalized gap 36.3Claude Fable 5.1 source Qwen3.5 397B source
SWE-bench Pro
Coding
Claude Fable 5.1: 81.2%Qwen3.5 397B: 50.9%Normalized gap 30.3Claude Fable 5.1 source Qwen3.5 397B 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
Qwen3.5 397B: $0.0024; Fits in one request

Qwen3.5 397B 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
Qwen3.5 397B: $0.0408; Fits in one request

Qwen3.5 397B 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
Qwen3.5 397B: $0.168; Does not fit in one request; Cached input priced at the published list-input rate

Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationClaude Fable 5.1Qwen3.5 397B

Context window

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

Claude Fable 5.1

Claude Fable 5.1 and Claude Mythos 5.1 system card

Qwen3.5 397B

128K

API model ID

Claude Fable 5.1

claude-fable-5-1

Anthropic Fable 5.1 and Mythos 5.1 launch

Qwen3.5 397B

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 launch

Qwen3.5 397B

Not published

Documented inputs

Claude Fable 5.1

Not sourced

Qwen3.5 397B

Not sourced

Documented outputs

Claude Fable 5.1

Not sourced

Qwen3.5 397B

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 launch

Qwen3.5 397B

Not sourced

Reasoning profile

Claude Fable 5.1

Reasoning

Qwen3.5 397B

Non-Reasoning

Weight access

Claude Fable 5.1

Proprietary

Qwen3.5 397B

Open Weight

License

Claude Fable 5.1

Proprietary

Qwen3.5 397B

Open Weight

Release date

Claude Fable 5.1

2026-09-01

Qwen3.5 397B

2026-02-16

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: Claude Fable 5.1 has the higher public score, 82.74 versus 57.75, and the 90% score intervals do not overlap.
Workload cost: Repository review: $0.65 vs $0.0408. Cache-heavy agent loop: $0.75 vs $0.168.
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 evidence54 rows

Agentic

Terminal-Bench 4.0
Claude Fable 5.155.80%
Source
Qwen3.5 397B—
Not directly comparable
Terminal-Bench-Science 0.1
Claude Fable 5.152.6%
Source
Qwen3.5 397B—
Not directly comparable
OSWorld 2.0
Claude Fable 5.141.7%
Source
Qwen3.5 397B—
Not directly comparable
AutomationBench
Claude Fable 5.131.4%
Source
Qwen3.5 397B—
Not directly comparable
Toolathlon-Verified
Claude Fable 5.177.8%
Source
Qwen3.5 397B—
Not directly comparable
Toolathlon Verified Pass@3
Claude Fable 5.181.5%
Source
Qwen3.5 397B—
Not directly comparable
Toolathlon Verified Pass³
Claude Fable 5.173.1%
Source
Qwen3.5 397B—
Not directly comparable
Toolathlon Verified avg. turns
Claude Fable 5.123.7 turns
Source
Qwen3.5 397B—
Not directly comparable
Terminal-Bench 2.0
Claude Fable 5.1—
Qwen3.5 397B52.5%
Source
Not directly comparable
BrowseComp
Claude Fable 5.1—
Qwen3.5 397B62%
Source
Not directly comparable
Claw-Eval
Claude Fable 5.1—
Qwen3.5 397B56.8%
Source
Not directly comparable
QwenClawBench
Claude Fable 5.1—
Qwen3.5 397B51.8%
Source
Not directly comparable
τ³-bench results
Claude Fable 5.1—
Qwen3.5 397B68.4%
Source
Not directly comparable
VITA-Bench
Claude Fable 5.1—
Qwen3.5 397B43.7%
Source
Not directly comparable
DeepPlanning
Claude Fable 5.1—
Qwen3.5 397B37.6%
Source
Not directly comparable
Toolathlon
Claude Fable 5.1—
Qwen3.5 397B36.3%
Source
Not directly comparable
MCP Atlas
Claude Fable 5.1—
Qwen3.5 397B46.1%
Source
Not directly comparable
MCP-Tasks
Claude Fable 5.1—
Qwen3.5 397B74.2%
Source
Not directly comparable
WideResearch
Claude Fable 5.1—
Qwen3.5 397B74.0%
Source
Not directly comparable
Gert Labs
Claude Fable 5.1—
Qwen3.5 397B46.76%
Source
Not directly comparable
ResearchClawBench
Claude Fable 5.1—
Qwen3.5 397B14.2%
Source
Not directly comparable

Coding

SWE-bench Pro
Claude Fable 5.181.2%
Source
Qwen3.5 397B50.9%
Source
Claude Fable 5.1 leads this result
SWE Multilingual
Claude Fable 5.189.1%
Source
Qwen3.5 397B—
Not directly comparable
SWE Multimodal
Claude Fable 5.154.7%
Source
Qwen3.5 397B—
Not directly comparable
deepSwe
Claude Fable 5.167.4%
Source
Qwen3.5 397B—
Not directly comparable
ProgramBench
Claude Fable 5.187.6%
Source
Qwen3.5 397B—
Not directly comparable
cursorBench32
Claude Fable 5.173.4%
Source
Qwen3.5 397B—
Not directly comparable
SWE-bench Verified
Claude Fable 5.1—
Qwen3.5 397B76.2%
Source
Not directly comparable
LiveCodeBench v6
Claude Fable 5.1—
Qwen3.5 397B83.6%
Source
Not directly comparable

Reasoning

ARC-AGI-1
Claude Fable 5.197.50%
Source
Qwen3.5 397B—
Not directly comparable
ARC-AGI-2
Claude Fable 5.190%
Source
Qwen3.5 397B—
Not directly comparable
LongBench v2
Claude Fable 5.1—
Qwen3.5 397B63.2%
Source
Not directly comparable
AI-Needle
Claude Fable 5.1—
Qwen3.5 397B68.7%
Source
Not directly comparable

Knowledge

HLE
Claude Fable 5.165%
Source
Qwen3.5 397B28.7%
Source
Claude Fable 5.1 leads this result
HLE w/o tools
Claude Fable 5.160.9%
Source
Qwen3.5 397B—
Not directly comparable
GPQA
Claude Fable 5.1—
Qwen3.5 397B88.4%
Source
Not directly comparable
SuperGPQA
Claude Fable 5.1—
Qwen3.5 397B70.4%
Source
Not directly comparable
MMLU-Pro
Claude Fable 5.1—
Qwen3.5 397B87.8%
Source
Not directly comparable
MMLU-Redux
Claude Fable 5.1—
Qwen3.5 397B94.9%
Source
Not directly comparable
C-Eval
Claude Fable 5.1—
Qwen3.5 397B93%
Source
Not directly comparable

Math

AIME26
Claude Fable 5.1—
Qwen3.5 397B93.3%
Source
Not directly comparable
HMMT Feb 2025
Claude Fable 5.1—
Qwen3.5 397B94.8%
Source
Not directly comparable
HMMT Nov 2025
Claude Fable 5.1—
Qwen3.5 397B92.7%
Source
Not directly comparable
HMMT Feb 2026
Claude Fable 5.1—
Qwen3.5 397B87.9%
Source
Not directly comparable
MMAnswerBench
Claude Fable 5.1—
Qwen3.5 397B80.9%
Source
Not directly comparable

Multilingual

MMLU-ProX
Claude Fable 5.1—
Qwen3.5 397B84.7%
Source
Not directly comparable
NOVA-63
Claude Fable 5.1—
Qwen3.5 397B59.1%
Source
Not directly comparable

Multimodal

MMMU-Pro
Claude Fable 5.1—
Qwen3.5 397B79%
Source
Not directly comparable
MathVision
Claude Fable 5.1—
Qwen3.5 397B88.6%
Source
Not directly comparable
CharXiv
Claude Fable 5.1—
Qwen3.5 397B80.8%
Source
Not directly comparable
VideoMMMU
Claude Fable 5.1—
Qwen3.5 397B84.7%
Source
Not directly comparable
ScreenSpot Pro
Claude Fable 5.1—
Qwen3.5 397B65.6%
Source
Not directly comparable
V*
Claude Fable 5.1—
Qwen3.5 397B95.8%
Source
Not directly comparable

Instruction following

IFEval
Claude Fable 5.1—
Qwen3.5 397B92.6%
Source
Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5.1 or Qwen3.5 397B?

Claude Fable 5.1 has the higher public score, 82.74 versus 57.75, 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 5.1 or Qwen3.5 397B?

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 Qwen3.5 397B?

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 Qwen3.5 397B?

For the stated presets, chat costs $0.035 on Claude Fable 5.1 and $0.0024 on Qwen3.5 397B; repository review costs $0.65 and $0.0408; the cache-heavy agent loop costs $0.75 and $0.168. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B 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 Qwen3.5 397B?

Claude Fable 5.1 has the larger documented context window: 1M, compared with 128K.

Related comparisons

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Last updated September 1, 2026

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Claude Fable 5.1 vs Qwen3.5 397B

Which one for your work

Long documents

Chat turn cost

Repository review cost

Coding work

Agentic work

Cache-heavy agent loop cost

What is actually comparable

Category results, on a stated basis

Coding

Knowledge

Agentic

Reasoning

Math

Multilingual

Multimodal

Instruction following

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

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Claude Fable 5.1 or Qwen3.5 397B?

Which is better for coding, Claude Fable 5.1 or Qwen3.5 397B?

Which is better for agentic tasks, Claude Fable 5.1 or Qwen3.5 397B?

Which costs less, Claude Fable 5.1 or Qwen3.5 397B?

Which has the larger context window, Claude Fable 5.1 or Qwen3.5 397B?

Related comparisons

Watch Claude Fable 5.1 vs Qwen3.5 397B