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Gemini 3.5 Flash-Lite API pricing

Gemini 3.5 Flash-Lite costs $0.30 per million input tokens and $2.50 per million output tokens at the standard rate. Here are its cached and batch prices, and what it costs for your usage.

Google Prices last checked: how

Price per million tokens

Token typeStandardBatch (50% off)
Input$0.30$0.15
Cached input$0.03$0.02
Output$2.50$1.25
Standard rates in USD, before tax Gemini API pricing
Your usage
Gemini 3.5 Flash-Lite / month $32.40 $0.0011 per request
  • Input $9.00
  • Cached input $0.9
  • Output $22.50

Monthly cost for typical workloads

WorkloadStandardBatch
Support chatbot
2,000 in / 300 out tokens, 1,000 requests a day, 50% cached
$32.40$16.35
Document summaries
10,000 in / 800 out tokens, 200 requests a day
$30.00$15.00
Tagging / classifying
400 in / 20 out tokens, 20,000 requests a day
$102.00$51.00
USD, before tax. A month is 30 days. Compare every model in the calculator

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FAQ

Frequently asked questions

How much does Gemini 3.5 Flash-Lite cost per million tokens?

Gemini 3.5 Flash-Lite costs $0.30 per million input tokens and $2.50 per million output tokens at the standard rate. Prices are in USD, before tax, from Gemini API pricing, last checked on 30 Sept 2026.

Does Gemini 3.5 Flash-Lite have a Batch API discount?

Yes. Through the Batch API, Gemini 3.5 Flash-Lite costs $0.15 per million input tokens and $1.25 per million output tokens, 50% less than the standard rate. Batch requests are processed asynchronously rather than straight away.

How much does prompt caching save on Gemini 3.5 Flash-Lite?

Input read from the prompt cache costs $0.03 per million tokens instead of $0.30, 90% less. Writing to or storing the cache can cost extra; those charges aren’t included here.

Is Gemini 3.5 Flash-Lite one of the cheaper API models?

For a support chatbot sending 1,000 requests a day (2,000 input and 300 output tokens each, 50% of the input cached), Gemini 3.5 Flash-Lite is the 4th cheapest of the 18 OpenAI, Anthropic and Google models we track, at $32.40 a month. Price alone doesn’t tell you how well a model will handle your task, so test the candidates on your own prompts.

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