Gemini 3.5 Flash Lite, the Google DeepMind model in numbers

What you need to know

Released on July 21, 2026, Gemini 3.5 Flash Lite is one of the 14 Google DeepMind models tracked on this site. It is a closed model: you access it through an API, from Google DeepMind or one of the 30 providers listed on models.dev. It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money. That makes it 3 months old as of October 22, 2026.

We file it under mid-range models (34 models in this category on the site).

What do independent benchmarks say?

According to results published by Epoch AI (checked on October 22, 2026), Gemini 3.5 Flash Lite has a capability index of 53.9 out of 100, computed on 4 benchmarks from our basket.

It is not among the top 30 of the weekly ranking.

• GPQA Diamond (PhD-level science questions): 83.3% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 71.1% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 26% — the best tracked model, GPT-6 Astra, reaches 93.7%
• APEX-Agents (professional tasks carried out by an agent): 29.3% — the best tracked model, Gemini 4 Argon, reaches 82.4%

Pricing and budget

Gemini 3.5 Flash Lite costs $0.30 per million input tokens and $2.5 per million output tokens (developer's price, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.011; a thousand of those tasks, $11.

That is 1.8 times cheaper than the median output price of mid-range models ($4.38).

Tokens read back from cache cost $0.03 per million, which helps an agent that keeps resending the same context.

To estimate your own budget, use the agent cost calculator.

What it can do

Its context window reaches 1,048,576 tokens, roughly 1,573 pages of text at 500 words per page: enough to load a whole book or a mid-sized codebase. A single answer can run to 65,536 tokens.

It accepts as input: text, image, video, audio and PDF. Its knowledge stops at March 2026: beyond that, it needs web search or your documents.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

When to choose it

Given its category, Gemini 3.5 Flash Lite is mainly aimed at a balance between quality and cost, for everyday uses that do not justify a frontier model.

Its very large context window makes it worth considering for analysing large sets of documents in a single request.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

What could replace it?

In the same category, the models closest to Gemini 3.5 Flash Lite are:

• Qwen3 Max (Alibaba Cloud (Qwen), index 55.4)
• Gemini 2.5 Pro (Google DeepMind, index 57)
• Claude Sonnet 4.6 (Anthropic, index 67.6)
• GPT-5.4 mini (OpenAI, index 68.4)