Google

GGemini 2.5 Flash (batch)API

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

Context window
1M
tokens
Input price
$0.15
per M tokens
Output price
$1.25
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 (batch), measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.

Intelligence index20.1
Math index73.3
GPQA79%
MMLU-Pro83.2%
Humanity's Last Exam11.1%
Long Context Reasoning61.7%
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
📈 Value23.6 intelligence points per $
Benchmark data by Artificial Analysis

About this model

Gemini 2.5 Flash (batch) 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 (batch)?

Gemini 2.5 Flash (batch) is an AI language model from Google. It is a proprietary model, available through an API. It scores 20.1 on the Artificial Analysis intelligence index.

Is Gemini 2.5 Flash (batch) free?

Gemini 2.5 Flash (batch) is not free: it costs $0.15 per million input tokens and $1.25 per million output tokens. Open-weight alternatives can be self-hosted at no per-token cost.

What is Gemini 2.5 Flash (batch) good at?

Independent benchmarks from Artificial Analysis give it GPQA 79%, MMLU-Pro 83.2%, Humanity's Last Exam 11.1%, Long Context Reasoning 61.7%, 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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