Model A

Anthropic

80.9/100

Supported · Public rank #3

90% interval 78.7–83.1

Claude Fable 5 vs Gemma 4 31B

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

Model B

Gemma 4 31B

Google

58.69/100

Supported · Public rank #83

90% interval 42.8–74.6

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.

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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 43.5, 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 27.6, 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.

18 Claude Fable 5 only

8 Gemma 4 31B only

Shared results: 0
Claude Fable 5 only: 18
Gemma 4 31B only: 8
Like-for-like categories: 3 / 8

1 category rests 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
Gemma 4 31B: 27.6; Supported · #140/151
Basis: BenchAlign lane · 4 vs 1 public rows
Reading: Claude Fable 5 leads

Coding

Like-for-like

Claude Fable 5: 76.9; Supported · #2/183
Gemma 4 31B: 43.5; Supported · #123/183
Basis: BenchAlign lane · 10 vs 2 public rows
Reading: Claude Fable 5 leads

Knowledge

Like-for-like

Claude Fable 5: 83.5; Supported · #2/181
Gemma 4 31B: 47.9; Supported · #104/181
Basis: BenchAlign lane · 2 vs 4 public rows
Reading: Claude Fable 5 leads

Instruction following

Directional only

Claude Fable 5: 78.3; #54/120
Gemma 4 31B: 92.6; #12/120
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Directional only

Reasoning

Not comparable

Claude Fable 5: 76.2; #11/22
Gemma 4 31B: 70.1; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Fable 5: Not ranked
Gemma 4 31B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Claude Fable 5: Not ranked
Gemma 4 31B: 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
Gemma 4 31B: 58.4; #30/48
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Fable 5 and Gemma 4 31B
Category	Claude Fable 5	Gemma 4 31B	Basis	Reading
Agentic	74.8Supported · #3/151	27.6Supported · #140/151	Like-for-likeBenchAlign lane · 4 vs 1 public rows	Claude Fable 5 leads
Coding	76.9Supported · #2/183	43.5Supported · #123/183	Like-for-likeBenchAlign lane · 10 vs 2 public rows	Claude Fable 5 leads
Knowledge	83.5Supported · #2/181	47.9Supported · #104/181	Like-for-likeBenchAlign lane · 2 vs 4 public rows	Claude Fable 5 leads
Instruction following	78.3#54/120	92.6#12/120	Directional onlyProvisional lane · 0 vs 0 weighted rows	Directional only
Reasoning	76.2#11/22	70.1Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 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	58.4#30/48	Not comparableProvisional lane · 1 vs 1 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.

A shared-evidence shape is not available.

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

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
Gemma 4 31B: Self-hosted; infrastructure cost varies; Fits in one request

Gemma 4 31B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5: $0.65; Fits in one request
Gemma 4 31B: Self-hosted; infrastructure cost varies; Fits in one request

Gemma 4 31B 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
Gemma 4 31B: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable

Gemma 4 31B

Reasoning

Weight access

Claude Fable 5

Proprietary

Gemma 4 31B

Open Weight

License

Claude Fable 5

Proprietary

Gemma 4 31B

Open Weight

Release date

Claude Fable 5

2026-06-09

Gemma 4 31B

2026-04-02

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: The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
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.

Gemma 4 31B

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 evidence26 rows

Agentic

Terminal-Bench 3.0
Claude Fable 534.0%
Source
Gemma 4 31B—
Not directly comparable
Terminal-Bench 2.0
Claude Fable 584.3%
Source
Gemma 4 31B—
Not directly comparable
OSWorld-Verified
Claude Fable 585%
Source
Gemma 4 31B—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Fable 580.5%
Source
Gemma 4 31B—
Not directly comparable
Gert Labs
Claude Fable 5—
Gemma 4 31B35.26%
Source
Not directly comparable

Coding

SWE-bench Verified
Claude Fable 595%
Source
Gemma 4 31B—
Not directly comparable
SWE-bench Pro
Claude Fable 580%
Source
Gemma 4 31B—
Not directly comparable
FrontierSWE v2
Claude Fable 548.0%
Source
Gemma 4 31B—
Not directly comparable
FrontierCode 1.1 Main
Claude Fable 553.5%
Source
Gemma 4 31B—
Not directly comparable
Terminal-Bench 2.0
Claude Fable 584.3%
Source
Gemma 4 31B—
Not directly comparable
cursorBench31
Claude Fable 570.6%
Source
Gemma 4 31B—
Not directly comparable
cursorBench32
Claude Fable 570.5%
Source
Gemma 4 31B—
Not directly comparable
VulcanBench v3
Claude Fable 589.5%
Source
Gemma 4 31B—
Not directly comparable
LiveCodeBench (Vals)
Claude Fable 589.8%
Source
Gemma 4 31B—
Not directly comparable
SWE-bench (Vals)
Claude Fable 595.0%
Source
Gemma 4 31B—
Not directly comparable
SWE-Rebench
Claude Fable 5—
Gemma 4 31B41.6%
Source
Not directly comparable
React Native Evals
Claude Fable 5—
Gemma 4 31B75.2%
Source
Not directly comparable

Knowledge

GPQA Diamond (Vals)
Claude Fable 593.2%
Source
Gemma 4 31B—
Not directly comparable
MMLU-Pro (Vals)
Claude Fable 591.5%
Source
Gemma 4 31B—
Not directly comparable
GPQA
Claude Fable 5—
Gemma 4 31B84.3%
Source
Not directly comparable
MMLU-Pro
Claude Fable 5—
Gemma 4 31B85.2%
Source
Not directly comparable
HLE
Claude Fable 5—
Gemma 4 31B26.5%
Source
Not directly comparable
HLE w/o tools
Claude Fable 5—
Gemma 4 31B19.5%
Source
Not directly comparable

Multimodal

Blueprint-Bench 2
Claude Fable 538.6%
Source
Gemma 4 31B—
Not directly comparable
OfficeQA Pro
Claude Fable 557.9%
Source
Gemma 4 31B—
Not directly comparable
MMMU-Pro
Claude Fable 5—
Gemma 4 31B76.9%
Source
Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5 or Gemma 4 31B?

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 or Gemma 4 31B?

Claude Fable 5 leads the public coding lane, 76.9 to 43.5, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Claude Fable 5 or Gemma 4 31B?

Claude Fable 5 leads the public agentic tasks lane, 74.8 to 27.6, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Claude Fable 5 or Gemma 4 31B?

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 Gemma 4 31B?

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

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 4, 2026

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Claude Fable 5 vs Gemma 4 31B

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

Multimodal

Frequently asked questions

Which is better, Claude Fable 5 or Gemma 4 31B?

Which is better for coding, Claude Fable 5 or Gemma 4 31B?

Which is better for agentic tasks, Claude Fable 5 or Gemma 4 31B?

Which costs less, Claude Fable 5 or Gemma 4 31B?

Which has the larger context window, Claude Fable 5 or Gemma 4 31B?

Related comparisons

Watch Claude Fable 5 vs Gemma 4 31B