Comparison page

Claude Sonnet 4.6 vs Gemini 3.1 Pro Preview

Compare a strong Anthropic production model against Google’s current Gemini Pro preview.

Side-by-side pricing

The table uses the same example request on both models so you can compare balanced reasoning and multimodal work without changing the prompt shape.

Input 1,000 / Output 250

ModelInput / 1MCached input / 1MOutput / 1MExample requestSource
Claude Sonnet 4.6

Anthropic's current balanced production model for everyday writing, analysis, and automation.

$3.00No public rate$15.0$0.0067Anthropic pricing
Gemini 3.1 Pro Preview

Google's latest Gemini Pro preview for complex multimodal reasoning workloads.

$2.00No public rate$12.0$0.0050Google Gemini pricing

When to choose each model

Claude Sonnet 4.6

Choose Claude Sonnet 4.6 when you want the economics or capability profile of Anthropic and you can justify the published rate.

Gemini 3.1 Pro Preview

Choose Gemini 3.1 Pro Preview when you need the second option in this comparison and want to test whether it lowers spend without hurting the workflow.

Use the calculator to confirm the exact request cost for your own input and output mix before you ship the change.

Use cases

  • • Choosing between Anthropic writing quality and Google multimodal reach.
  • • Planning enterprise assistants with richer documents.
  • • Comparing vendor economics for production deployments.

If the prompt is noisy or repetitive, run it through the prompt optimizer first.

If the brief is too loose, use the context engineer to tighten the instructions before you compare models again.

For the broader pricing strategy, read the LLM cost optimization pillar and the cost-per-million-tokens cheat sheet.

FAQ

Which model is cheaper?

Claude Sonnet 4.6 is cheaper on the current public input rate than Gemini 3.1 Pro Preview.

When might Gemini win?

When the workflow leans on the Google ecosystem or you need a specific Gemini preview capability.

Can I pair this with the pillar guide?

Yes. Use it alongside the LLM cost optimization pillar to understand the bigger spend pattern.