Google

GGemini 2.5 Flash LiteAPI

Gemini 2.5 Flash Lite (Google): live API pricing, context window and the best open-source alternatives, tracked daily by OpenSourceAI.tech.

Context window
1M
tokens
Input price
$0.1
per M tokens
Output price
$0.4
per M tokens
Provider
Google

Prices update automatically — checked hourly against provider list prices.

See open-source alternatives → Compare all model prices

Benchmarks & performance

Independent benchmark scores for Gemini 2.5 Flash Lite, measured by Artificial Analysis. Higher is better. Measurement mode: Non-reasoning.

Intelligence index6.9
Math index35.3
GPQA47.4%
MMLU-Pro72.4%
Humanity's Last Exam3.7%
Long Context Reasoning31.3%
LiveCodeBench40%
SciCode17.7%
MATH-50092.6%
AIME50%
AIME 202535.3%
IFBench31.5%
τ²-Bench19%
Terminal-Bench Hard2.3%
💰 Blended price$0.175 / 1M tokens
📈 Value39.4 intelligence points per $
Benchmark data by Artificial Analysis

About this model

Gemini 2.5 Flash Lite is a commercial AI model by Google. The specifications below are tracked automatically: pricing is refreshed hourly from public list prices, so the numbers on this page reflect the current cost of using the model through its API.

Frequently asked questions

What is Gemini 2.5 Flash Lite?

Gemini 2.5 Flash Lite is an AI language model from Google. It is a proprietary model, available through an API. It scores 6.9 on the Artificial Analysis intelligence index.

Is Gemini 2.5 Flash Lite free?

Gemini 2.5 Flash Lite is not free: it costs $0.1 per million input tokens and $0.4 per million output tokens. Open-weight alternatives can be self-hosted at no per-token cost.

What is Gemini 2.5 Flash Lite good at?

Independent benchmarks from Artificial Analysis give it GPQA 47.4%, MMLU-Pro 72.4%, Humanity's Last Exam 3.7%, Long Context Reasoning 31.3%, LiveCodeBench 40%, SciCode 17.7%, MATH-500 92.6%, AIME 50%, AIME 2025 35.3%, IFBench 31.5%, τ²-Bench 19%, Terminal-Bench Hard 2.3%. It is particularly used for mathematical reasoning.

Open-source alternatives

Depending on your workload, an open-weight model that you can self-host may cut costs dramatically or remove per-token pricing entirely. Our comparison pages put this model side by side with the strongest open-source contenders.

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