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Model Comparison

Claude Sonnet 5 vs Gemini 3.7 FlashWhich Is Better in 2026?

Claude Sonnet 5 vs Gemini 3.7 Flash: which should you choose in 2026?

Claude Sonnet 5 (by Anthropic) and Gemini 3.7 Flash (by Google) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Gemini 3.7 Flash is about 5.3× cheaper on a blended 3:1 input/output basis ($0.75 vs $4.00 per 1M tokens).

Choose Claude Sonnet 5 if…

  • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage

Choose Gemini 3.7 Flash if…

  • lower blended API cost matters for your workload

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

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Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

Claude Sonnet 5 and Gemini 3.7 Flash benchmark results
BenchmarkClaude Sonnet 5Gemini 3.7 Flash
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

DeepSWE 1.1

A long-horizon software-engineering benchmark with 113 original tasks graded by hand-written tests.

Pass@1

54.0%±4.0
DataCurve
SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

74.6%±1.6
Terminal-Bench
AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

LiveBench

A contamination-resistant benchmark refreshed on a fixed release cadence. Scores from different LiveBench releases must never be compared as the same protocol.

Mean of category averages

Pricing, capabilities, and model facts

Claude Sonnet 5 and Gemini 3.7 Flash model facts
FeatureClaude Sonnet 5Gemini 3.7 Flash
Context & model facts
DeveloperAnthropicGoogle
API providerAnthropicGoogle
Input context1,000,000 tokens1,048,576 tokens
Maximum output128,000 tokens65,536 tokens
Released
Added to WritingmateJun 30, 2026Aug 13, 2026
LicenseNot availableNot available
Knowledge cutoff
Capabilities
InputsText, Image, FileText, Image, Video, File, Audio
OutputsTextText
Provider endpoint accepts tool parametersYesYes
ReasoningYesYes
VisionYesYes
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$2.00$0.375
Output (per 1M tokens)$10.00$1.88
Blended 3:1 input/output$4.00$0.75
API performance
p95 latencyNot measuredNot measured
Output throughputNot measuredNot measured
Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

Data sources

  • Writingmate model catalog (pricing, limits, and availability)

Catalog data last updated Aug 13, 2026.

Why Pay for Multiple Subscriptions?

Comparing Claude Sonnet 5 from Anthropic with Gemini 3.7 Flash from Google? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for Claude Sonnet 5 and Gemini 3.7 Flash
PlanPriceClaude Sonnet 5Gemini 3.7 FlashAI ImagesAI Video
Writingmate Pro
Most popular
$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
Writingmate Ultimate
Power users
$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1

Claude Sonnet 5 vs Gemini 3.7 Flash FAQ

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

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Gemini 3.7 Flash is about 5.3× cheaper on a blended 3:1 input/output basis ($0.75 vs $4.00 per 1M tokens).

Which model is cheaper to use through an API?

Gemini 3.7 Flash is about 5.3× cheaper on a blended 3:1 input/output basis ($0.75 vs $4.00 per 1M tokens).

Which model supports more context?

The published context windows are close enough that this page does not treat the difference as a material advantage.

Can I switch between Claude Sonnet 5 and Gemini 3.7 Flash?

Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.