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AI123AI ModelsgoogleGemini 3.1 Flash Lite Preview
Gemini 3.1 Flash Lite Preview

Gemini 3.1 Flash Lite Preview

google

Gemini 3.1 Flash Lite Preview is Google's high-efficiency model optimized for high-volume use cases. It outperforms Gemini 2.5 Flash Lite on overall quality and approaches Gemini 2.5 Flash performance across key capabilities. Improvements span audio input/ASR, RAG snippet ranking, translation, data extraction, and code completion. Supports full thinking levels (minimal, low, medium, high) for fine-grained cost/performance trade-offs. Priced at half the cost of Gemini 3 Flash.

Modalities
TT
Input / output price
$0.25/$1.5per 1M tokens
Context
1.0M
Released
2026-03-03
PricingArtificial AnalysisDesign ArenaRelated Models

Pricing

Usage prices in USD. Token rates are per one million tokens; other billing units are shown with each charge.
InputOutputCache readCache writeWeb search
$0.25/ 1M tokens$1.50/ 1M tokens$0.02/ 1M tokens$0.08/ 1M tokens$0.014/ request

Artificial Analysis

Explore rankings
15.6

Intelligence index

Outperforms 47% of compared models

34.7

Coding index

Outperforms 34% of compared models

1.6

Agentic index

Outperforms 26% of compared models

Design Arena

Elo scores and win rates across design and agent tasks.

Category performance

1,000-1,500 Elo
3D: 1045; Asciiart: 1164; Code Categories: 1070; Data Visualization: 1045; Game Development: 1029; SVG: 1049; UI Component: 1066; Website: 10813D1045 EloAsciiart1164 EloCode Categories1070 EloData Visualization1045 EloGame Development1029 EloSVG1049 EloUI Component1066 EloWebsite1081 Elo

Model Arena

Asciiart

1164Elo

Win rate 50.8%

SVG

1049Elo

Win rate 42.5%

UI Component

1066Elo

Win rate 37.7%

3D

1045Elo

Win rate 38.8%

Data Visualization

1045Elo

Win rate 33.3%

Code Categories

1070Elo

Win rate 36.5%

Website

1081Elo

Win rate 36.6%

Game Development

1029Elo

Win rate 33.7%

How Design Arena works

Related Models

Gemini 4 Argon

Gemini 4 Argon

google

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Context
1.0M
Max output
943.7K
Released
2026-10-13
Input
$2/M
Output
$10/M
Cache read
$0.1/M
Gemini 3.8 Flash

Gemini 3.8 Flash

google

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Context
1.0M
Max output
65.5K
Released
2026-09-02
Input
$0.825/M
Output
$4.13/M
Cache read
$0.083/M
Gemini 3.7 Flash

Gemini 3.7 Flash

google

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step problem solving.

Context
1.0M
Max output
65.5K
Released
2026-08-13
Input
$0.75/M
Output
$3.75/M
Cache read
$0.075/M
Home > Models > Gemini 3.1 Flash Lite Preview