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Gemini 3.5 Flash-Lite

Multimodal modelTool useGemini 3.5

Gemini 3.5 Flash-Lite

Release date: 2026-07-21Updated: 2026-08-22Views: 287
Live demoGitHubHugging FaceCompare
Parameters
No data
Context length
1M
Multilingual
No data
Reasoning ability
3/5

Gemini 3.5 Flash-Lite is a multimodal model from Google Deep Mind, released on 2026-07-21. It accepts text, image, audio, and video input and returns text output. The recorded context window is 1M, and the recorded maximum output is 64K. Cataloged capabilities include Reasoning model, Coding model, Translation model, and Function calling. The model weights are proprietary and are not published for download. Use the linked references to confirm current access, licensing, and provider-specific limits.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

Gemini 3.5 Flash-Lite

Model basics

Reasoning traces
Supported
Thinking modes
Thinking Level · LowThinking Level · MediumThinking Level · High
Context length
1M tokens
Max output length
64K tokens
Model type
Multimodal model
Modality (in / out)
Text, Image, Audio, Video → Text
Release date
2026-07-21
Model file size
No data
MoE architecture
No
Total params / Active params
No data / Not applicable
Knowledge cutoff
No data
Gemini 3.5 Flash-Lite

Open source & experience

Code license
Proprietary
Weights license
Proprietary
GitHub repo
N/A
Hugging Face
N/A
Live demo
aistudio.google.com
Gemini 3.5 Flash-Lite

Official resources

Paper
Paper
DataLearnerAI blog
N/A
Gemini 3.5 Flash-Lite

API details

API speed
5/5
💡Default unit: $/1M tokens. If vendors use other units, follow their published pricing.
Learn about pricing modes
Standard
TypeConditionInputOutput
Text-$0.300/ 1M$2.50/ 1M
Batch
TypeConditionInputOutput
Text-$0.150/ 1M$1.25/ 1M
flex
TypeConditionInputOutput
Text-$0.150/ 1M$1.25/ 1M
priority
TypeConditionInputOutput
Text-$0.540/ 1M$4.50/ 1M
Cache PricingPrompt Cache
TypeTTLWriteRead
Text-—$0.020/ 1M

“—” means the modality is not billed in that direction, or the vendor has not published a price for it.

Gemini 3.5 Flash-Lite

Benchmark Results

Gemini 3.5 Flash-Lite currently shows benchmark results led by Creative Writing (41 / 99, score 1556), GPQA Diamond (114 / 270, score 83.33), Context Arena (57 / 126, score 72.57). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.

Thinking
Tool usage

General Evaluation

2 evaluations
Benchmark / mode
Score
Rank/total
GPQA Diamond
Low
75.76
166 / 270
GPQA Diamond
High
83.33
114 / 270

Writing and Creative Capabilities

1 evaluations
Benchmark / mode
Score
Rank/total
Creative Writing
Standard Mode
1556
41 / 99

Coding and Software Engineer

1 evaluations
Benchmark / mode
Score
Rank/total
SWE-Bench Pro - Public
Thinking ModeTools
54.20
36 / 60

Text Embedding

3 evaluations
Benchmark / mode
Score
Rank/total
Context Arena
Low
61.90
75 / 126
Context Arena
Medium
65.50
72 / 126
Context Arena
High
72.57
57 / 126

AI Agent - Tool Usage

2 evaluations
Benchmark / mode
Score
Rank/total
OSWorld-Verified
Thinking ModeTools
74
14 / 26
Terminal-Bench 2.1
Thinking ModeTools
54
47 / 49

Productivity Knowledge

1 evaluations
Benchmark / mode
Score
Rank/total
AA-Briefcase
Thinking ModeTools
636.95
17 / 19

Math and Reasoning

2 evaluations
Benchmark / mode
Score
Rank/total
FrontierMath v2
High
25.96
46 / 58
FrontierMath Tier 4 v2
High
0
39 / 40
View benchmark analysisCompare with other models

Compare with other models

Gemini 3.5 Flash-Lite

Publisher

Google Deep Mind
Google Deep Mind
View publisher details
Gemini 3.5 Flash-Lite

Model Overview

Gemini 3.5 Flash-Lite is a multimodal model from Google Deep Mind, released on 2026-07-21.

It accepts text, image, audio, and video input and produces text output. Its cataloged capabilities include Reasoning model, Coding model, Translation model, Function calling, and Tool use. The recorded context window is 1M, and the recorded maximum output is 64K.

The model weights are proprietary and are not published for download. The page records 12 API pricing rules from DeepMind; current provider pricing and conditions should be checked before deployment. The evaluation section contains 3 cataloged benchmark results with their recorded modes and scores. The page links 2 release, model-card, repository, or provider references for checking the underlying claims. Specifications, availability, and prices can change; undisclosed values are intentionally left unstated.

Gemini 3.5 Flash-Lite

FAQ

What is Gemini 3.5 Flash-Lite?

Gemini 3.5 Flash-Lite is a multimodal model from Google Deep Mind, released on 2026-07-21. It accepts text, image, audio, and video input and returns text output. The recorded context window is 1M, and the recorded maximum output is 64K. Cataloged capabilities include Reasoning model, Coding model, Translation model, and Function calling. The model weights are proprietary and are not published for download. Use the linked references to confirm current access, licensing, and provider-specific limits.

What input and output modalities does Gemini 3.5 Flash-Lite support?

The current model record lists text, image, audio, and video as input and text as output.

What are the main recorded specifications for Gemini 3.5 Flash-Lite?

The recorded context window is 1M, and the recorded maximum output is 64K. Fields without a source-backed value remain undisclosed.

Does Gemini 3.5 Flash-Lite have API pricing?

The page records 12 API pricing rules from DeepMind; current provider pricing and conditions should be checked before deployment.

Are benchmark results available for Gemini 3.5 Flash-Lite?

The evaluation section contains 3 cataloged benchmark results with their recorded modes and scores. Compare only results that use the same benchmark version and evaluation mode.

Is Gemini 3.5 Flash-Lite open source?

The model weights are proprietary and are not published for download. Review the linked license text before commercial or derivative use.

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