Model Cost Profile

Google: Gemini 3.1 Flash Lite Preview

Developer: google

Pricing updated Mar 11, 2026

Input rank: #153Output rank: #199

Live Pricing

Input: $0.2500

Output: $1.50

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Google's Gemini 3.1 Flash Lite Preview offers a substantial context window of 1,048,576 tokens, making it suitable for complex applications such as conversational agents and large-scale document processing. With an input price of $0.25 per million tokens and an output price of $1.50 per million tokens, teams can effectively manage costs while leveraging its advanced capabilities for data-intensive tasks. This model is particularly beneficial for organizations that require high throughput and extensive context handling in their AI-driven solutions.

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Context Window

1,048,576

Tokens

Input Price / 1M

$0.2500

Prompt tokens

Output Price / 1M

$1.50

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Google: Gemini 3.1 Flash Lite Preview Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$0.2500$0.8750$1.50Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$0.2500

Current Output / 1M

$1.50

Cheaper Alternatives to Compare

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FAQ

Common pricing and benchmark questions for Google: Gemini 3.1 Flash Lite Preview.

How much does Google: Gemini 3.1 Flash Lite Preview cost per 1M input tokens?

Google: Gemini 3.1 Flash Lite Preview input pricing is $0.2500 per 1M tokens based on the latest synced provider data.

How much does Google: Gemini 3.1 Flash Lite Preview cost per 1M output tokens?

Google: Gemini 3.1 Flash Lite Preview output pricing is $1.50 per 1M tokens based on the latest synced provider data.

What context window does Google: Gemini 3.1 Flash Lite Preview support?

Google: Gemini 3.1 Flash Lite Preview supports a context window of 1,048,576 tokens.

How can I compare Google: Gemini 3.1 Flash Lite Preview with cheaper alternatives?

Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.