Google

GGemini 3.5 Flash (batch)API

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed.

Context window
1M
tokens
Input price
$0.75
per M tokens
Output price
$4.5
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 3.5 Flash (batch), measured by Artificial Analysis. Higher is better. Measurement mode: high.

Intelligence index50.2
Coding index70.1
GPQA92.2%
Humanity's Last Exam41%
Long Context Reasoning69.3%
SciCode53.1%
IFBench76.3%
τ²-Bench95.3%
τ-Bench Banking25.4%
Terminal-Bench78.7%
Terminal-Bench Hard40.9%
⚡ Speed243 tokens/sec
⏱ Latency13.71s to first token
💰 Blended price$3.375 / 1M tokens
📈 Value14.9 intelligence points per $
Benchmark data by Artificial Analysis

About this model

Gemini 3.5 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 3.5 Flash (batch)?

Gemini 3.5 Flash (batch) is an AI language model from Google. It is a proprietary model, available through an API. It scores 50.2 on the Artificial Analysis intelligence index.

Is Gemini 3.5 Flash (batch) free?

Gemini 3.5 Flash (batch) is not free: it costs $0.75 per million input tokens and $4.5 per million output tokens. Open-weight alternatives can be self-hosted at no per-token cost.

What is Gemini 3.5 Flash (batch) good at?

Independent benchmarks from Artificial Analysis give it GPQA 92.2%, Humanity's Last Exam 41%, Long Context Reasoning 69.3%, SciCode 53.1%, IFBench 76.3%, τ²-Bench 95.3%, τ-Bench Banking 25.4%, Terminal-Bench 78.7%, Terminal-Bench Hard 40.9%. It is particularly used for code generation.

How fast is Gemini 3.5 Flash (batch)?

It generates about 243 tokens per second, with a median 13.71s delay before the first token. Measured independently by Artificial Analysis.

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