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  4. Gemini 3.5 Flash-Lite
Google
Released July 21, 2026

Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is the fastest 3.5-class model, optimized for high-volume agentic workflows, subagent tasks, and document parsing with 1M context.

Visit GoogleAnnouncement
Inputs
Text
Image
File
Audio
Video
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

Gemini 3.5 Flash-Lite - fastest, most cost-effective 3.5-class model

Gemini 3.5 Flash-Lite is a low-latency, natively multimodal reasoning model built on Gemini 3.1 Flash-Lite and positioned as the speed and cost leader within the Gemini 3.5 class. It is optimized for high-volume agentic workflows, subagent tasks, and document parsing where latency and API cost are the primary constraints.

TraitDetail
Throughput350 output tokens per second (Artificial Analysis Index), making it the fastest 3.5-class model
Subagent and document focusOptimized for high-throughput, low-cost execution of subagent tasks and document parsing
Agentic workflow gainsSignificantly outperforms prior Flash-Lite generations in agentic workflows
Multimodal inputsText, image, video, audio, and PDF with a 1M token context window; 64K token text output
Agentic capabilitiesSupports function calling, file search, computer use (preview), thinking, URL context, and structured outputs
Not supportedAudio generation, image generation, and Live API are not available
FoundationBased on Gemini 3.1 Flash-Lite architecture

Positioned for scale

The model is distributed across Gemini App, Google AI Studio, Gemini Enterprise Agent Platform, and the Gemini API. It supports caching, batch API, flex inference, and priority inference to manage cost and throughput at production scale.

Benchmark Performance

Independent evaluations · Artificial Analysis

37.4%
Intelligence
49.3%
Coding Index
27.2%
Agentic Index

Accuracy & Capability Details

GPQA - Graduate Science83.8%
Humanity's Last Exam18.8%
SciCode - Scientific Coding40.9%
Long Context Reasoning74.7%
Specs
Context window
1.0Mtokens
Input pricing
$0.30per 1M tokens
Output pricing
$2.50per 1M tokens
Cached input
$0.03per 1M tokens

Prices in USD.

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderGoogleAnthropicAnthropic
Release DateJuly 21, 2026July 24, 2026June 9, 2026
Knowledge Cutoff-May 2026-
Context & Limits
Context Window
1.0M
Best Context Window
1M1M
Pricing (per 1M tokens)
Input Pricing
$0.30
Best Input Pricing
$5$10
Output Pricing
$2.50
Best Output Pricing
$25$50
Modalities
Inputs
textimagefileaudiovideo
textimage
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index37.4
63.1
Best Intelligence Index
62.1
Coding Index49.3
78.0
Best Coding Index
76.5
Agentic Index27.2
59.2
Best Agentic Index
56.6
Gemini 3.5 Flash-Lite
Claude Opus 5
Claude Fable 5

GPQA Benchmark

Graduate-level reasoning and expert Q&A evaluation.

84%
Gemini 3.5 Flash-Lite
GPQA Benchmark
Score: 84%
Gemini 3.5 Flash-Lite
93%
Claude Opus 5
GPQA Benchmark
Score: 93%
Claude Opus 5
93%
Claude Fable 5
GPQA Benchmark
Score: 93%
Claude Fable 5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

19%
Gemini 3.5 Flash-Lite
Humanity's Last Exam
Score: 19%
Gemini 3.5 Flash-Lite
55%
Claude Opus 5
Humanity's Last Exam
Score: 55%
Claude Opus 5
56%
Claude Fable 5
Humanity's Last Exam
Score: 56%
Claude Fable 5

Long Context Reasoning

Logical reasoning over long context windows.

75%
Gemini 3.5 Flash-Lite
Long Context Reasoning
Score: 75%
Gemini 3.5 Flash-Lite
76%
Claude Opus 5
Long Context Reasoning
Score: 76%
Claude Opus 5
77%
Claude Fable 5
Long Context Reasoning
Score: 77%
Claude Fable 5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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