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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.

1MContext window · tokens
$0.15Input price · per M tokens
$1.25Output 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 (batch), measured by Artificial Analysis. Higher is better. Measurement mode: Non-reasoning.

Intelligence index9.9
Math index60.3
GPQA68.3%
MMLU-Pro80.9%
Humanity's Last Exam4.7%
Long Context Reasoning49.9%
LiveCodeBench49.5%
MATH-50093.2%
AIME50%
AIME 202560.3%
IFBench39%
τ²-Bench14.9%
Terminal-Bench Hard12.1%
💰 Blended price$0.85 / 1M tokens
📈 Value11.6 intelligence points per $
vs. models measured heretop 76%
Scores higher than 24% of the 292 models measured by Artificial Analysis and tracked here.
Models at this level cost $0.39 per 1M tokens (median of 37) — this one costs $0.43.
Cheaper and better on this index: DeepSeek V4.1 Flash 1017 · GLM 5.3 · Claude Haiku 5.5 and 49 more
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 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 (batch)?

Gemini 2.5 Flash (batch) is an AI language model from Google. It is a proprietary model, available through an API. It scores 9.9 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 68.3%, MMLU-Pro 80.9%, Humanity's Last Exam 4.7%, Long Context Reasoning 49.9%, LiveCodeBench 49.5%, MATH-500 93.2%, AIME 50%, AIME 2025 60.3%, IFBench 39%, τ²-Bench 14.9%, Terminal-Bench Hard 12.1%. It is particularly used for mathematical reasoning.

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