TokenRate

Gemini 3.1 Pro Pricing

Flagship

Google · 1M tokens context

Gemini 3.1 Pro from Google costs $2.00 per 1 million input tokens and $12.00 per 1 million output tokens as of July 2026 (live OpenRouter data). The model supports a 1,048,576-token context window (approximately 786,432 words) with a 66K-token maximum output. A typical 1,000-token request costs $0.0020 in input charges; a 10,000-token request costs $0.0200.

Gemini 3.1 Pro pricing and capability summary
Input price$2.00 / 1M tokens
Output price$12.00 / 1M tokens
Output / input ratio6.0×
Context window1,048,576 tokens (~786,432 words)
Maximum output65,536 tokens
Cost per 1K tokens (input)$0.0020
TierFlagship
Last verified

Gemini 3.1 Pro is Google's generally-available flagship (released February 19, 2026) for complex reasoning, long-context work, and native multimodality across text, images, video, audio, and PDFs. It posts 80.6% on SWE-bench Verified, 94.3% on GPQA Diamond, and 77.1% on ARC-AGI-2, with a 1M-token context window at $2/$12 per million tokens — materially cheaper than the Claude and GPT flagships. Despite persistent speculation, there is no Gemini 3.5 Pro: Google shipped only Flash-class models in July 2026, leaving 3.1 Pro as its top Pro tier.

Live pricing from OpenRouter

Input Price

$2.00

per 1 million tokens

Output Price

$12.00

per 1 million tokens

Context Window

1M tokens

max 66K output

Cost Examples

Request TypeTokensInput CostOutput Cost
1,000 word article1,333$0.00267$0.0048
10-page document (2,500 words)3,333$0.00667$0.012
1,000 lines of code5,000$0.01$0.018
100K token document100,000$0.20$0.36

Output cost estimated at 30% of input token count. Use the calculator for exact figures.

Strengths

  • Frontier reasoning at well under flagship pricing ($2/$12 per 1M)
  • 1M-token context with native video, audio, image and PDF input
  • 94.3% GPQA Diamond and 77.1% ARC-AGI-2
  • 80.6% SWE-bench Verified — competitive with far pricier models

Limitations

  • Pricing doubles above 200K context ($4/$18 per 1M)
  • Trails the top Claude models on the hardest coding benchmarks
  • SWE-bench Pro (~54.2%) falls well short of its Verified score
  • Can be confidently wrong — factual output needs verification

Best Use Cases

Long-context analysis over entire codebases or document sets
Video, audio and multimodal understanding
Complex multi-step reasoning on a budget
High-volume workloads where flagship pricing is prohibitive

Calculate Gemini 3.1 Pro Costs

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Gemini 3.1 Pro — FAQ

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