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BenchLM

Claude Fable 5.1 vs Qwen3.8-Omni-Flash

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

4 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Anthropic logo
Model A
Claude Fable 5.1

Anthropic

84.74/100

Supported · Public rank #1

90% interval 78.5–90.9

Alibaba logo
Model B
Qwen3.8-Omni-Flash

Alibaba

—

Evidence status unavailable

90% interval unavailable

Updated September 18, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Qwen3.8-Omni-Flash 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

    Qwen3.8-Omni-Flash is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • 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 5.1 only
22
Qwen3.8-Omni-Flash only
15
Like-for-like categories
0 / 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.

Coding

Directional only
Claude Fable 5.1
83.8
Supported · #1/154
Qwen3.8-Omni-Flash
53.5
Estimated · #45/154
Basis
BenchAlign lane · 10 vs 5 public rows
Reading
Directional only

Knowledge

Directional only
Claude Fable 5.1
86.7
Supported · #1/184
Qwen3.8-Omni-Flash
54.9
Estimated · #54/184
Basis
BenchAlign lane · 4 vs 3 public rows
Reading
Directional only

Agentic

Not comparable
Claude Fable 5.1
80.2
Supported · #1/154
Qwen3.8-Omni-Flash
Not ranked
Basis
BenchAlign lane · 10 vs 2 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Fable 5.1
79.4
#2/20
Qwen3.8-Omni-Flash
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5.1
Not ranked
Qwen3.8-Omni-Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5.1
Not ranked
Qwen3.8-Omni-Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5.1
Not ranked
Qwen3.8-Omni-Flash
85.1
Unranked · 7 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Fable 5.1
Not ranked
Qwen3.8-Omni-Flash
87.7
#29/124
Basis
Provisional lane · 0 vs 1 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 5.1
$0.035
Fits in one request
Qwen3.8-Omni-Flash
API rate not published
Fits in one request

Qwen3.8-Omni-Flash 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
Qwen3.8-Omni-Flash
API rate not published
Fits in one request

Qwen3.8-Omni-Flash 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
Qwen3.8-Omni-Flash
API rate not published
Fits in one request
Cached-input rate unavailable

Qwen3.8-Omni-Flash 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.

Documented inputs

Claude Fable 5.1

Not sourced

Qwen3.8-Omni-Flash

Not sourced

Documented outputs

Claude Fable 5.1

Not sourced

Qwen3.8-Omni-Flash

Not sourced

Reasoning profile

Claude Fable 5.1

Reasoning

Qwen3.8-Omni-Flash

Reasoning

Weight access

Claude Fable 5.1

Proprietary

Qwen3.8-Omni-Flash

Proprietary

License

Claude Fable 5.1

Proprietary

Qwen3.8-Omni-Flash

Proprietary

Release date

Claude Fable 5.1

2026-09-01

Qwen3.8-Omni-Flash

2026-09-18

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 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 evidence41 rows

Agentic

  • Terminal-Bench 4.0

    Claude Fable 5.155.80%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Fable 5.152.6%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • OSWorld 2.0

    Claude Fable 5.141.7%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • AutomationBench

    Claude Fable 5.131.4%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • Toolathlon-Verified

    Claude Fable 5.177.8%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Fable 5.181.5%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Fable 5.173.1%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Fable 5.123.7 turns
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 5.185.0%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • ApprenticeBench

    Claude Fable 5.172%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • CoWorkBench

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash75.3%
    Source

    Not directly comparable

  • AndroidWorld

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash87.1%
    Source

    Not directly comparable

Coding

  • Bug Hunt Bench

    Claude Fable 5.143 fixes
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • SWE-bench Pro

    Claude Fable 5.181.2%
    Source
    Qwen3.8-Omni-Flash63.3%
    Source

    Claude Fable 5.1 leads this result

  • SWE Multilingual

    Claude Fable 5.189.1%
    Source
    Qwen3.8-Omni-Flash80.5%
    Source

    Claude Fable 5.1 leads this result

  • SWE Multimodal

    Claude Fable 5.154.7%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • DeepSWE

    Claude Fable 5.167.4%
    Source
    Qwen3.8-Omni-Flash57.8%
    Source

    Claude Fable 5.1 leads this result

  • FrontierSWE v2

    Claude Fable 5.156.3%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • ProgramBench

    Claude Fable 5.187.6%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • cursorBench32

    Claude Fable 5.173.4%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Fable 5.190.5%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • cursorBench40

    Claude Fable 5.151.8%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • NL2Repo

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash48.9%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash92.6%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-1

    Claude Fable 5.197.50%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • ARC-AGI-2

    Claude Fable 5.190%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

Knowledge

  • HLE

    Claude Fable 5.165%
    Source
    Qwen3.8-Omni-Flash36.5%
    Source

    Claude Fable 5.1 leads this result

  • HLE w/o tools

    Claude Fable 5.160.9%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Fable 5.193.4%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 5.192.4%
    Source
    Qwen3.8-Omni-Flash—

    Not directly comparable

  • GPQA

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash91%
    Source

    Not directly comparable

  • GPQA-D

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash91.0%
    Source

    Not directly comparable

Multimodal

  • Vision2Web

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash62.9%
    Source

    Not directly comparable

  • ERQA

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash71.0%
    Source

    Not directly comparable

  • LVBench

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash76.9%
    Source

    Not directly comparable

  • RealWorldQA

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash87.7%
    Source

    Not directly comparable

  • MathVision

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash91.8%
    Source

    Not directly comparable

  • MathVision w/ Python

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash96.2%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash83.5%
    Source

    Not directly comparable

  • CharXiv

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash91.4%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Claude Fable 5.1—
    Qwen3.8-Omni-Flash81.5%
    Source

    Not directly comparable

Questions

Which is better, Claude Fable 5.1 or Qwen3.8-Omni-Flash?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude Fable 5.1 or Qwen3.8-Omni-Flash?

Claude Fable 5.1 scores higher for coding on the public lane, 83.8 to 53.5. Qwen3.8-Omni-Flash 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 Qwen3.8-Omni-Flash?

Qwen3.8-Omni-Flash is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Fable 5.1 or Qwen3.8-Omni-Flash?

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 Qwen3.8-Omni-Flash?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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