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GGemini 2.5 FlashAPI

Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks.

1MContext window · tokens
$0.3Input price · per M tokens
$2.5Output price · per M tokens
GoogleProvider

Prices update automatically — checked daily against provider list prices.

See open-source alternatives → Compare all model prices

Benchmarks & performance

Independent benchmark scores for Gemini 2.5 Flash, measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.

Intelligence index20.3
Math index73.3
GPQA79%
MMLU-Pro83.2%
Humanity's Last Exam12.1%
Long Context Reasoning65.7%
LiveCodeBench69.5%
SciCode39.4%
MATH-50098.1%
AIME82.3%
AIME 202573.3%
IFBench50.3%
τ²-Bench31.6%
Terminal-Bench Hard13.6%
💰 Blended price$0.85 / 1M tokens
📈 Value23.9 intelligence points per $
vs. models measured heretop 63%
Scores higher than 37% of the 273 models measured by Artificial Analysis and tracked here.
Models at this level cost $0.88 per 1M tokens (median of 23) — this one costs $0.85.
Cheaper and better on this index: GLM 5.3 Flash · Gemini 3.7 Flash · Gemini 3.7 Flash (batch) and 55 more
Benchmark data by Artificial Analysis

About this model

Gemini 2.5 Flash is a commercial AI model by Google. The specifications below are tracked automatically: pricing is refreshed daily 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?

Gemini 2.5 Flash is an AI language model from Google. It is a proprietary model, available through an API. It scores 20.3 on the Artificial Analysis intelligence index.

Is Gemini 2.5 Flash free?

Gemini 2.5 Flash is not free: it costs $0.3 per million input tokens and $2.5 per million output tokens. Open-weight alternatives can be self-hosted at no per-token cost.

What is Gemini 2.5 Flash good at?

Independent benchmarks from Artificial Analysis give it GPQA 79%, MMLU-Pro 83.2%, Humanity's Last Exam 12.1%, Long Context Reasoning 65.7%, LiveCodeBench 69.5%, SciCode 39.4%, MATH-500 98.1%, AIME 82.3%, AIME 2025 73.3%, IFBench 50.3%, τ²-Bench 31.6%, Terminal-Bench Hard 13.6%. It is particularly used for mathematical reasoning.

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