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Model A
Claude Sonnet 5

Anthropic

64.6/100

Estimated · Public rank #35

90% interval 50.3–78.9

Claude Sonnet 5 vs Gemini 3.7 Flash

Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Gemini 3.7 Flash

Google

Evidence status unavailable

90% interval unavailable

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 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.

  • 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

    Claude Sonnet 5

    Claude Sonnet 5 has the lower estimated token cost for this stated workload. Gemini 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

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

    No shared weighted benchmark basis supports a winner.

    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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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 Sonnet 5 only
15
Gemini 3.7 Flash only
11
Like-for-like categories
1 / 8

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.

Multimodal

Like-for-like
Claude Sonnet 5
88.3
Gemini 3.7 Flash
88.7
Weighted basis
1 vs 1 rows
Reading
Gemini 3.7 Flash leads

Agentic

Not comparable
Claude Sonnet 5
81.9
Gemini 3.7 Flash
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude Sonnet 5
76.7
Gemini 3.7 Flash
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Sonnet 5
Not measured
Gemini 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Sonnet 5
57.4
Gemini 3.7 Flash
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 5
Not measured
Gemini 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 5
Not measured
Gemini 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 5
Not measured
Gemini 3.7 Flash
Not measured
Weighted basis
0 vs 0 rows
Reading
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.

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 Sonnet 5
$0.007
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 Sonnet 5
$0.13
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 Sonnet 5
$0.18
Fits in one request
Gemini 3.7 Flash
$0.2025
Fits in one request
Cached input priced at the published list-input rate

Claude Sonnet 5 has the lower modeled cost

Gemini 3.7 Flash 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.

Provider availability

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

Gemini 3.7 Flash

Generally Available · Gemini API, Google AI Studio, Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise, Gemini app via Spark

Google Gemini 3.7 Flash launch

Reasoning profile

Claude Sonnet 5

Reasoning

Gemini 3.7 Flash

Reasoning

Weight access

Claude Sonnet 5

Proprietary

Gemini 3.7 Flash

Proprietary

License

Claude Sonnet 5

Proprietary

Gemini 3.7 Flash

Proprietary

Release date

Claude Sonnet 5

2026-06-30

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
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
Repository review: $0.13 vs $0.04875. Cache-heavy agent loop: $0.18 vs $0.2025.
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 evidence30 rows

Agentic

  • Terminal-Bench 3.0

    Claude Sonnet 514.6%
    Source
    Gemini 3.7 Flash14.9%
    Source

    Gemini 3.7 Flash leads this result

  • Terminal-Bench 2.0

    Claude Sonnet 580.4%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • BrowseComp

    Claude Sonnet 584.7%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 557.4%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • OSWorld-Verified

    Claude Sonnet 581.2%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 5
    Gemini 3.7 Flash85.8%
    Source

    Not directly comparable

  • AutomationBench

    Claude Sonnet 5
    Gemini 3.7 Flash30.4%
    Source

    Not directly comparable

  • OSWorld 2.0

    Claude Sonnet 5
    Gemini 3.7 Flash47.9%
    Source

    Not directly comparable

  • Agents' Last Exam

    Claude Sonnet 5
    Gemini 3.7 Flash26.3%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Sonnet 585.2%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • SWE-bench Pro

    Claude Sonnet 563.2%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • SWE Multilingual

    Claude Sonnet 578.3%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • SWE Multimodal

    Claude Sonnet 528.1%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Sonnet 580.4%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Sonnet 542.7%
    Source
    Gemini 3.7 Flash43.6%
    Source

    Gemini 3.7 Flash leads this result

  • cursorBench32

    Claude Sonnet 561.5%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • APEX-SWE

    Claude Sonnet 546.4%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • EEBench

    Claude Sonnet 540.3%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • 3DCodeBench

    Claude Sonnet 539.2%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • deepSwe

    Claude Sonnet 5
    Gemini 3.7 Flash65.3%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 5
    Gemini 3.7 Flash85.8%
    Source

    Not directly comparable

Reasoning

  • GDM-MRCR v2 128K average

    Claude Sonnet 5
    Gemini 3.7 Flash97%
    Source

    Not directly comparable

Knowledge

  • HLE

    Claude Sonnet 557.4%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 543.2%
    Source
    Gemini 3.7 Flash

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Sonnet 5
    Gemini 3.7 Flash87.1%
    Source

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Sonnet 5
    Gemini 3.7 Flash43.5%
    Source

    Not directly comparable

Multimodal

  • CharXiv

    Claude Sonnet 588.3%
    Source
    Gemini 3.7 Flash88.7%
    Source

    Gemini 3.7 Flash leads this result

  • CharXiv w/o tools

    Claude Sonnet 577%
    Source
    Gemini 3.7 Flash84.5%
    Source

    Gemini 3.7 Flash leads this result

  • GDP.pdf (no tools)

    Claude Sonnet 5
    Gemini 3.7 Flash34.0%
    Source

    Not directly comparable

  • LVBench

    Claude Sonnet 5
    Gemini 3.7 Flash85.4%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Sonnet 5 or Gemini 3.7 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 Sonnet 5 or Gemini 3.7 Flash?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Sonnet 5 or Gemini 3.7 Flash?

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 Sonnet 5 or Gemini 3.7 Flash?

For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.00263 on Gemini 3.7 Flash; repository review costs $0.13 and $0.04875; the cache-heavy agent loop costs $0.18 and $0.2025. Gemini 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Sonnet 5 or Gemini 3.7 Flash?

Both models list the same context window, 1M.

Related comparisons

Last updated August 13, 2026

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