LLMAnonymized

Gemini 3.5 Flash-Lite

Google's fastest, most cost-efficient 3.5-class model — optimized for high-throughput agentic tasks, document parsing, and low-latency reasoning.

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What is Gemini 3.5 Flash-Lite?

Gemini 3.5 Flash-Lite is Google DeepMind's fastest and most cost-effective multimodal reasoning model, released in July 2026. It supports text, images, audio, and video inputs, with a 1M-token context window and 65K-token output, optimized for high-throughput agentic workflows and low-latency tasks.

Use Gemini 3.5 Flash-Lite privately on Venice

On Venice, Gemini 3.5 Flash-Lite runs with anonymized privacy — your prompts are never stored or used for training. You get full access to its vision, function calling, and web search capabilities without surveillance, ideal for scalable, private agentic applications. The model’s low latency and cost efficiency are preserved in Venice’s zero-retention environment.

Anonymized
No prompt training
TEE · hardware enclave
End-to-end encrypted

What can Gemini 3.5 Flash-Lite do?

Strengths
  • Extremely fast — delivers up to 376 output tokens per second, ideal for latency-sensitive workflows.
  • Cost-efficient for high-volume tasks like classification, translation, and JSON extraction.
  • Supports multimodal inputs (text, image, audio, video) and structured outputs via JSON schema.
  • Enables tool use, web search, and function calling for agentic automation.
  • 1M-token context window allows deep document analysis and long-form reasoning.
Limitations
  • Custom inference parameters (temperature, top-k, top-p) are not supported — limits fine control over output randomness.
  • No computer use or code execution in sandbox — restricts autonomous tool operation.
  • Less suitable for complex multi-step agentic reasoning compared to higher-tier models like Gemini 3.5 Flash or Opus-class models.

Gemini 3.5 Flash-Lite capabilities

How to use Gemini 3.5 Flash-Lite via API

Venice exposes an OpenAI-compatible API. Swap your base URL and call gemini-3-5-flash-lite.

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3-5-flash-lite",
    "messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
  }'

Specifications

MakerGoogle DeepMind
ReleasedJuly 2026
ArchitectureBased on Gemini 3.1 Flash-Lite
ParametersNot publicly disclosed
Open weightsNo — proprietary
Context window1,000K tokens
Max output65.536K tokens
CapabilitiesVision, Function calling, Reasoning, Web search
Privacy on VeniceAnonymized — prompts not stored
Available on Venice sinceJul 2026
LicenseProprietary

Pricing

Billed per token on Venice: $0.38 per 1M input tokens and $3.13 per 1M output tokens.

Input / 1M tokens
$0.38
Output / 1M tokens
$3.13
Cached input / 1M
$0.04

New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.

Gemini 3.5 Flash-Lite vs alternatives

ModelMax outputSpeed (tok/s)Open weightsPrice (Venice)
Gemini 3.5 Flash-Lite65.5K376No$0.38 in · $3.13 out / 1M
DeepSeek V4 Flash 073164K412No$0.17 in · $0.35 out / 1M
Google Gemma 4 31B Instruct32K289Yes$0.12 in · $0.36 out / 1M
Claude Sonnet 4.616K183No$3.60 in · $18 out / 1M

Google's fastest low-cost model for agentic throughput.

What is Gemini 3.5 Flash-Lite good for?

  • High-throughput document parsing and data extraction at scale.
  • Low-latency translation and content classification pipelines.
  • Lightweight agentic subtasks with vision and function calling.
  • Receipt or invoice analysis with multimodal input and structured output.
  • Rapid prototyping of UI or game concepts via API automation.

Prompting tips

  • Use minimal thinking level for fast, low-cost classification or extraction tasks.
  • Set thinking level to medium or high when using as a subagent for code or API workflows.
  • Include images or PDFs directly in prompts — the model handles multimodal input natively.
  • Leverage web search grounding for real-time information retrieval within prompts.

Version history

Gemini 2.5 Flash
2025

Predecessor model

Gemini 3.1 Flash-Lite
2026-03

Base model

Gemini 3.5 Flash-Lite
2026-07

CurrentCurrent — faster, more efficient

Frequently asked questions

Gemini 3.5 Flash-Lite is Google DeepMind's fastest and most cost-efficient multimodal reasoning model, released in July 2026. It supports text, image, audio, and video inputs, with a 1M-token context window, optimized for high-throughput agentic workflows and low-latency tasks.

On Venice, Gemini 3.5 Flash-Lite is billed at $0.38 per 1M input tokens and $3.13 per 1M output tokens. Cached input is even cheaper at $0.04 per 1M tokens, making repeated queries highly efficient.

No. Gemini 3.5 Flash-Lite is a proprietary Google model with no open weights. It is not free to use — pricing is based on token consumption, though Venice offers no upfront subscription.

Yes. Gemini 3.5 Flash-Lite supports image, video, and PDF inputs natively, enabling multimodal understanding for tasks like receipt analysis, document parsing, and visual content interpretation.

Yes. The model supports function calling, web search, and structured output, making it suitable for lightweight agentic workflows. However, it does not support full computer use or sandboxed code execution.

Gemini 3.5 Flash-Lite has a 1M-token context window, allowing it to process extremely long documents or complex multimodal inputs in a single pass.

Gemini 3.5 Flash-Lite offers stronger integration with Google's ecosystem and better multimodal support, while DeepSeek V4 Flash is faster and significantly cheaper. Choose Gemini for Google-grounded workflows, DeepSeek for pure cost-performance.

Related models

Run Gemini 3.5 Flash-Lite privately.

No prompt logging. No data used for training. Free to start — no credit card.

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