Google's cheapest Gemini 3 model, with a 1,048,576-token context window and $0.25/$1.50 per million token pricing for high-volume, cost-sensitive work.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
The gemini 3.1 flash lite model is the entry point into Google's Gemini 3 line — the cheapest model in this comparison, and the one built for workloads where cost per call matters more than squeezing out every last point of reasoning depth: content moderation, lightweight classification, chat widgets fielding thousands of short conversations, and background agents that fire off frequent tool calls.
A 1,048,576-token context window is large enough to hold a full customer support history, a mid-size codebase, or a stack of PDFs without truncation — even on the cheapest model in the lineup. Output tops out at 65,536 tokens per response, which covers structured data extraction, summaries, and multi-turn tool plans comfortably.
Gemini 3.1 Flash Lite costs $0.25 per million input tokens and $1.50 per million output tokens — the lowest rate of any model in this comparison. Cached input drops further, to $0.025 per million tokens, a real saving for apps that reuse a large system prompt or reference document across many requests. Its knowledge cutoff is listed as January 2025, so anything that happened after that needs to come in through retrieval or tool use rather than the model's training data.
Rough cost picture:
Compared to Gemini 3.5 Flash Lite ($0.30 input / $2.50 output), 3.1 Flash Lite is the older, cheaper generation — a reasonable default if your task doesn't need whatever incremental improvements came with the 3.5 line, and a good starting point before paying more for Gemini 3.6 Flash ($1.50 / $7.50) or Gemini 3.5 Flash ($1.50 / $9.00). It still supports function calling, reasoning, and vision, so the lower price isn't a case of stripped-out features — it's the same feature set at a smaller footprint.
Its capability score (89.0) sits just under the two newer models in this lineup (both 89.4), a small but real gap. For latency- and cost-sensitive workloads that lean on high call volume, that gap is usually worth trading for the lower price — but for anything where output quality directly affects the product, it's worth running your own comparison rather than assuming the newer, pricier sibling automatically wins.
Use the recorded facts as a shortlist, then validate the model against representative inputs and production constraints.
Gemini 3.1 Flash Lite is categorized for Audio-text-to-text, Automatic speech recognition, Image-text-to-text, Image-to-text, Text generation, Text-to-text AI models, Video-text-to-text. Its current record accepts text, image, video, audio, pdf and produces text. Confirm file formats, preprocessing, and provider-specific request schemas before implementation.
The directory records 1.0M context and 65.5K maximum output. Listed token prices are $0.25 input and $1.50 output per 1M tokens. Treat missing values as unknown and recheck current commercial terms.
Recorded output speed is — and time to first token is —. Hosting route, region, prompt length, concurrency, and provider load can materially change both measurements.
This page separates sourced model facts from incomplete fields. Benchmark evidence is displayed only when its source is linked and verified. Before choosing Gemini 3.1 Flash Lite, test task quality, tool reliability, safety behavior, data controls, rate limits, and total cost on the exact route you intend to use.
Related approved models in Automatic speech recognition. Compare specifications and verify fit for your workload.
Google's low-cost Gemini 3 model with a 1,048,576-token context window, vision support, and $0.30/$2.50 per million token pricing for volume workloads.
Google's mid-tier Gemini 3 model: 1,048,576-token context, multimodal input, and $1.50/$7.50 per million token pricing for production agent workloads.
Google's full Gemini 3 Flash model, with a 1,048,576-token context window and $1.50/$9.00 per million token pricing for production-grade agent work.
Google's fast, rolling-updated Gemini model with a 1M-token context window, reasoning, and tool calling at $1.50/$9.00 per million tokens.
Google's low-cost, high-volume Gemini model at $0.25/$1.50 per million tokens, with a 1M-token context window and reasoning support.