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Google · Low-cost processing of large amounts of data

Gemini 3.5 Flash-Lite

A model for quick classification, data retrieval and conversion into the required format. It is insufficient for complex decisions; its advantages are speed and low cost.

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Costs
Low · $0.30 per million input tokens and $2.50 per million output tokens; a token is a small piece of text
Speed
Very fast · generated 350 tokens per second in the measurement
Availability
Online service from Google and Gemini products
Input length
Very long input · up to 1 million tokens (small pieces of text)
Inputs
Text, images, video and audio as input

Data checked . Release date unverified.

Indicative capability profile

Where the model is strong

The five levels are our clear summary of the results below. They are not a ranking that applies to every task.

Analysis Sufficient for simple decisions based on clear rules.
Coding Better suited to editing and classification than designing an entire solution.
Autonomous work across multiple steps Classifies tasks well; it should pass complex cases to a stronger model.
Writing and content It quickly summarizes and reformats, but cannot replace a final expert text.
Speed Very short task completion time and high output speed.

Ideal use

When to choose it

  • Classifying requests and routing them to the appropriate workflow
  • Finding data and then checking it
  • Bulk rewrites and format conversions

Usage boundaries

When to choose another model

  • Autonomous solving of complex analytical tasks
  • Final check of important claims

Traceable supporting sources

Data and measurement sources

Distinguish between the manufacturer's documentation and the results of a specific test. Measurements also depend on the settings and the task set used.

Artificial Analysis

Time and cost per task

0.6 min · $0.09

Suitable for a low-cost first step in a process that passes complex cases on.

Open original source ↗
Artificial Analysis

Intelligence Index v4.1

36 points

It also shows its limitation: speed cannot replace the ability to solve complex problems.

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Next step

Compare the model using your actual task.

A benchmark narrows the selection. A short trial on your data determines the choice.

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