Gemini 3.1 Flash Lite, the Google DeepMind model in numbers

Gemini 3.1 Flash Lite at a glance

Gemini 3.1 Flash Lite is a language model from Google DeepMind, released on May 7, 2026. That makes it 5 months old as of October 22, 2026. It is a closed model: you access it through an API, from Google DeepMind or one of the 26 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.

We file it under budget models (24 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 3.1 Flash Lite has a capability index of 64.3 out of 100, computed on 3 benchmarks from our basket.

With only 3 benchmarks reported, it does not enter the public ranking, which requires at least 4 results, so its index should be read as partial.

• GPQA Diamond (PhD-level science questions): 81.8% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 80% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 27.7% — the best tracked model, GPT-6 Astra, reaches 93.7%
• Humanity's Last Exam (multidisciplinary expert questions): 8.6% — the best tracked model, GPT-6 Astra, reaches 54.8%

What it costs

Gemini 3.1 Flash Lite costs $0.25 per million input tokens and $1.5 per million output tokens (median of 26 providers, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.008; a thousand of those tasks, $8.

That is 1.3 times the median output price of budget models ($1.13).

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

Context and capabilities

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 January 2025: 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 3.1 Flash Lite is mainly aimed at high volumes where every cent counts: sorting, information extraction, summaries, simple assistants.

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 3.1 Flash Lite are:

• Qwen3.6 Flash (Alibaba Cloud (Qwen), index 64.5) — see the comparison
• Qwen3.7 Flash (Alibaba Cloud (Qwen), index 63.7) — see the comparison
• GPT-5 Mini (OpenAI, index 62.9) — see the comparison
• GPT-5.4 nano (OpenAI, index 71.7) — see the comparison