Claude Fable 5.2 vs Gemini 3.7 Flash

Updated November 9, 2026. Rank says Claude Fable 5.2 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Claude Fable 5.2 has the higher public point estimate, 91.19 versus 66.25. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Claude Fable 5.2

Anthropic

91.19/100

Estimated · Public rank #1

Conditional range 76.8–100.0

Model B

Gemini 3.7 Flash

Google

66.25/100

Supported · Public rank #25

90% interval 60.0–72.5

Shared results: 3
Claude Fable 5.2 only: 27
Gemini 3.7 Flash only: 27
Like-for-like categories: 2 / 8

Estimated: Claude Fable 5.2 · Supported: Gemini 3.7 Flash. Conditional ranges do not establish rank confidence.How the comparison works

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.

Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash 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
Gemini 3.7 Flash
Gemini 3.7 Flash 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
Claude Fable 5.2 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
Claude Fable 5.2 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

86.9Claude Fable 5.257.7Gemini 3.7 Flash

Directional only · BenchAlign v5.8

Claude Fable 5.2 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

AutomationBenchAgentic
Normalized gap 21.0
Claude Fable 5.2:51.4%
Gemini 3.7 Flash:30.4%
Claude Fable 5.2 source Gemini 3.7 Flash source

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, 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.

Reasoning

Like-for-like

Claude Fable 5.2: 90.7; Supported · #1/157
Gemini 3.7 Flash: 62.9; Supported · #24/157
Basis: BenchAlign v5.8 lane · 3 vs 3 public rows
Reading: Claude Fable 5.2 leads

Knowledge

Like-for-like

Claude Fable 5.2: 97.6; Supported · #1/179
Gemini 3.7 Flash: 70.1; Supported · #15/179
Basis: BenchAlign v5.8 lane · 3 vs 6 public rows
Reading: Claude Fable 5.2 leads

Agentic

Directional only

Claude Fable 5.2: 90.7; Estimated · #1/132
Gemini 3.7 Flash: 60.9; Supported · #24/132
Basis: BenchAlign v5.8 lane · 8 vs 9 public rows
Reading: Directional only

Coding

Directional only

Claude Fable 5.2: 86.9; Estimated · #1/158
Gemini 3.7 Flash: 57.7; Supported · #25/158
Basis: BenchAlign v5.8 lane · 8 vs 6 public rows
Reading: Directional only

Multimodal

Directional only

Claude Fable 5.2: 89.8; Estimated · #1/67
Gemini 3.7 Flash: 70.1; Supported · #14/67
Basis: BenchAlign v5.8 lane · 6 vs 4 public rows
Reading: Directional only

Multilingual

Not comparable

Claude Fable 5.2: Not ranked
Gemini 3.7 Flash: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Claude Fable 5.2: Not ranked
Gemini 3.7 Flash: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Fable 5.2: Not ranked
Gemini 3.7 Flash: 71.3; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Fable 5.2 and Gemini 3.7 Flash
Category	Claude Fable 5.2	Gemini 3.7 Flash	Basis	Reading
Reasoning	90.7Supported · #1/157	62.9Supported · #24/157	Like-for-likeBenchAlign v5.8 lane · 3 vs 3 public rows	Claude Fable 5.2 leads
Knowledge	97.6Supported · #1/179	70.1Supported · #15/179	Like-for-likeBenchAlign v5.8 lane · 3 vs 6 public rows	Claude Fable 5.2 leads
Agentic	90.7Estimated · #1/132	60.9Supported · #24/132	Directional onlyBenchAlign v5.8 lane · 8 vs 9 public rows	Directional only
Coding	86.9Estimated · #1/158	57.7Supported · #25/158	Directional onlyBenchAlign v5.8 lane · 8 vs 6 public rows	Directional only
Multimodal	89.8Estimated · #1/67	70.1Supported · #14/67	Directional onlyBenchAlign v5.8 lane · 6 vs 4 public rows	Directional only
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	71.3Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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 5.2: $0.028; Fits in one request
Gemini 3.7 Flash: $0.00262; Fits in one request

Gemini 3.7 Flash has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5.2: $0.52; Fits in one request
Gemini 3.7 Flash: $0.04875; Fits in one request

Gemini 3.7 Flash 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 5.2: $0.6; Fits in one request
Gemini 3.7 Flash: $0.0675; Fits in one request

Gemini 3.7 Flash has the lower modeled cost

Costs use the listed standard API rates.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

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

SpecificationClaude Fable 5.2Gemini 3.7 Flash

Context window

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

Claude Fable 5.2

Anthropic Claude Fable 5.2 model documentation

Gemini 3.7 Flash

Google Gemini 3.7 Flash API documentation

API model ID

Claude Fable 5.2

claude-fable-5-2

Anthropic Claude Fable 5.2 model documentation

Gemini 3.7 Flash

gemini-3.7-flash

Google Gemini 3.7 Flash API documentation

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Fable 5.2

$0.2 per 1M cached input tokens

Claude API pricing

Gemini 3.7 Flash

$0.075 per 1M cached input tokens

Google Gemini API pricing

Documented inputs

Claude Fable 5.2

text, image

Anthropic Claude Mythos 5.2 model documentation

Gemini 3.7 Flash

text, image, video, audio, pdf

Google Gemini 3.7 Flash API documentation

Documented outputs

Claude Fable 5.2

text

Anthropic Claude Mythos 5.2 model documentation

Gemini 3.7 Flash

text

Google Gemini 3.7 Flash API documentation

Provider availability

Claude Fable 5.2

Generally Available · Claude API, Claude products, AWS, Google Cloud, Microsoft Azure

Anthropic Fable 5.2 and Mythos 5.2 launch

Gemini 3.7 Flash

Generally Available · Gemini API, Google AI Studio, Gemini App - Spark, Gemini Enterprise App, Gemini Enterprise Agent Platform, Google Antigravity

Google DeepMind Gemini 3.7 Flash model card

Reasoning profile

Claude Fable 5.2

Reasoning

Gemini 3.7 Flash

Reasoning

Weight access

Claude Fable 5.2

Proprietary

Gemini 3.7 Flash

Proprietary

License

Claude Fable 5.2

Proprietary

Gemini 3.7 Flash

Proprietary

Release date

Claude Fable 5.2

2026-11-09

Gemini 3.7 Flash

2026-08-13

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 5.2 has the higher public point estimate, 91.19 versus 66.25. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
Workload cost: Repository review: $0.52 vs $0.04875. Cache-heavy agent loop: $0.6 vs $0.0675.
Context tradeoff: Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Fable 5.2 or Gemini 3.7 Flash?

Claude Fable 5.2 has the higher public point estimate, 91.19 versus 66.25. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude Fable 5.2 or Gemini 3.7 Flash?

Claude Fable 5.2 scores higher for coding on the public lane, 86.9 to 57.7. Claude Fable 5.2 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 5.2 or Gemini 3.7 Flash?

Claude Fable 5.2 scores higher for agentic tasks on the public lane, 90.7 to 60.9. Claude Fable 5.2 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 5.2 or Gemini 3.7 Flash?

For the stated presets, chat costs $0.028 on Claude Fable 5.2 and $0.00263 on Gemini 3.7 Flash; repository review costs $0.52 and $0.04875; the cache-heavy agent loop costs $0.6 and $0.0675. Costs use the listed standard API rates.

Which has the larger context window, Claude Fable 5.2 or Gemini 3.7 Flash?

Both models list the same context window, 1M.

Benchmark evidence

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

Browse raw public benchmark evidence57 rows

Agentic

Terminal-Bench 4.0
Claude Fable 5.267.60%
Source
Gemini 3.7 Flash—
Not directly comparable
Terminal-Bench-Science 0.1
Claude Fable 5.274.6%
Source
Gemini 3.7 Flash—
Not directly comparable
AutomationBench
Claude Fable 5.251.4%
Source
Gemini 3.7 Flash30.4%
Source
Claude Fable 5.2 leads this result
OSWorld 2.1 Offline
Claude Fable 5.289.3%
Source
Gemini 3.7 Flash—
Not directly comparable
WANDR
Claude Fable 5.282.1%
Source
Gemini 3.7 Flash—
Not directly comparable
Remote Labor Index
Claude Fable 5.241.3%
Source
Gemini 3.7 Flash—
Not directly comparable
RoboDojo Sim
Claude Fable 5.264.9%
Source
Gemini 3.7 Flash—
Not directly comparable
DRACO
Claude Fable 5.287.7%
Source
Gemini 3.7 Flash—
Not directly comparable
Terminal-Bench 4.1
Claude Fable 5.2—
Gemini 3.7 Flash12.40%
Source
Not directly comparable
Terminal-Bench 2.1
Claude Fable 5.2—
Gemini 3.7 Flash85.8%
Source
Not directly comparable
Terminal-Bench 3.0
Claude Fable 5.2—
Gemini 3.7 Flash14.9%
Source
Not directly comparable
OSWorld 2.0
Claude Fable 5.2—
Gemini 3.7 Flash47.9%
Source
Not directly comparable
Agents' Last Exam
Claude Fable 5.2—
Gemini 3.7 Flash26.3%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Fable 5.2—
Gemini 3.7 Flash77.5%
Source
Not directly comparable
ApprenticeBench
Claude Fable 5.2—
Gemini 3.7 Flash16%
Source
Not directly comparable
MazeBench
Claude Fable 5.2—
Gemini 3.7 Flash1%
Source
Not directly comparable

Coding

SWE-bench Pro
Claude Fable 5.293%
Source
Gemini 3.7 Flash—
Not directly comparable
SWE Multilingual
Claude Fable 5.296.6%
Source
Gemini 3.7 Flash—
Not directly comparable
SWE Multimodal
Claude Fable 5.274.1%
Source
Gemini 3.7 Flash—
Not directly comparable
DeepSWE
Claude Fable 5.274.3%
Source
Gemini 3.7 Flash65.3%
Source
Claude Fable 5.2 leads this result
FrontierSWE v2
Shared source
Claude Fable 5.269.9%
Gemini 3.7 Flash20.3%
Claude Fable 5.2 leads this result
ProgramBench
Claude Fable 5.285.6%
Source
Gemini 3.7 Flash—
Not directly comparable
FrontierCode 2.0
Claude Fable 5.249.1%
Source
Gemini 3.7 Flash—
Not directly comparable
CursorBench 4.0
Claude Fable 5.260.0%
Source
Gemini 3.7 Flash—
Not directly comparable
FrontierCode 1.1 Main
Claude Fable 5.2—
Gemini 3.7 Flash43.6%
Source
Not directly comparable
Terminal-Bench 2.1
Claude Fable 5.2—
Gemini 3.7 Flash85.8%
Source
Not directly comparable
LiveCodeBench (Vals)
Claude Fable 5.2—
Gemini 3.7 Flash88.7%
Source
Not directly comparable
SWE-bench (Vals)
Claude Fable 5.2—
Gemini 3.7 Flash80.8%
Source
Not directly comparable

Reasoning

ARC-AGI-3
Claude Fable 5.265.7%
Source
Gemini 3.7 Flash—
Not directly comparable
ARC-AGI-3 Provider Adapter
Claude Fable 5.294.90%
Source
Gemini 3.7 Flash—
Not directly comparable
STEM Professor Bench
Claude Fable 5.261.8%
Source
Gemini 3.7 Flash—
Not directly comparable
MRCR v2 64K-128K
Claude Fable 5.2—
Gemini 3.7 Flash97%
Source
Not directly comparable
ARC-AGI-1
Claude Fable 5.2—
Gemini 3.7 Flash95.50%
Source
Not directly comparable
ARC-AGI-2
Claude Fable 5.2—
Gemini 3.7 Flash84.6%
Source
Not directly comparable

Multimodal

Chartography (no tools)
Claude Fable 5.273.4%
Source
Gemini 3.7 Flash—
Not directly comparable
Chartography (tools)
Claude Fable 5.291.6%
Source
Gemini 3.7 Flash—
Not directly comparable
OfficeQA
Claude Fable 5.283.4%
Source
Gemini 3.7 Flash—
Not directly comparable
OfficeQA Pro
Claude Fable 5.272.9%
Source
Gemini 3.7 Flash—
Not directly comparable
BenchCAD 2.1
Claude Fable 5.275.4%
Source
Gemini 3.7 Flash—
Not directly comparable
BenchCAD 2.1 (tools)
Claude Fable 5.283.5%
Source
Gemini 3.7 Flash—
Not directly comparable
ParseBench
Claude Fable 5.2—
Gemini 3.7 Flash70.37%
Source
Not directly comparable
CharXiv w/o tools
Claude Fable 5.2—
Gemini 3.7 Flash84.5%
Source
Not directly comparable
CharXiv
Claude Fable 5.2—
Gemini 3.7 Flash88.7%
Source
Not directly comparable
LVBench
Claude Fable 5.2—
Gemini 3.7 Flash85.4%
Source
Not directly comparable

Knowledge

HLE
Claude Fable 5.274.2%
Source
Gemini 3.7 Flash—
Not directly comparable
HLE w/o tools
Claude Fable 5.273.2%
Source
Gemini 3.7 Flash—
Not directly comparable
PhysicianBench
Claude Fable 5.264.4%
Source
Gemini 3.7 Flash—
Not directly comparable
HLE-Verified
Claude Fable 5.2—
Gemini 3.7 Flash53.6%
Source
Not directly comparable
LABBench2
Claude Fable 5.2—
Gemini 3.7 Flash82.1%
Source
Not directly comparable
BioMysteryBench (human-solvable)
Claude Fable 5.2—
Gemini 3.7 Flash87.1%
Source
Not directly comparable
BioMysteryBench (human-difficult)
Claude Fable 5.2—
Gemini 3.7 Flash43.5%
Source
Not directly comparable
GPQA Diamond (Vals)
Claude Fable 5.2—
Gemini 3.7 Flash93.9%
Source
Not directly comparable
MMLU-Pro (Vals)
Claude Fable 5.2—
Gemini 3.7 Flash90.1%
Source
Not directly comparable

Multilingual

GMMLU
Claude Fable 5.296.0%
Source
Gemini 3.7 Flash—
Not directly comparable
MILU
Claude Fable 5.294.1%
Source
Gemini 3.7 Flash—
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Claude Fable 5.2—
Gemini 3.7 Flash71.579%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Claude Fable 5.2—
Gemini 3.7 Flash36.585%
Source
Not directly comparable

57 public results · 3 shared

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Last updated November 9, 2026

Claude Fable 5.2 vs Gemini 3.7 Flash

Decision reading

Which one for your work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Coding work

Agentic work

Long documents

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Reasoning

Knowledge

Agentic

Coding

Multimodal

Multilingual

Instruction following

Math

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

If you already use one of these models

Questions

Which is better, Claude Fable 5.2 or Gemini 3.7 Flash?

Which is better for coding, Claude Fable 5.2 or Gemini 3.7 Flash?

Which is better for agentic tasks, Claude Fable 5.2 or Gemini 3.7 Flash?

Which costs less, Claude Fable 5.2 or Gemini 3.7 Flash?

Which has the larger context window, Claude Fable 5.2 or Gemini 3.7 Flash?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Math

Related comparisons

Watch Claude Fable 5.2 vs Gemini 3.7 Flash