Gemini 2.5 Flash-Lite
Our smallest and most cost effective model, built for at scale usage.
You always get the exact model you pick — we never silently route you to another.
About Gemini 2.5 Flash-Lite
At 262 tokens per second with a 0.37-second time-to-first-token, Gemini 2.5 Flash-Lite is built for one thing above all else: going fast without draining your budget. It delivers roughly 75% of Gemini 2.5 Flash's capability at 30% of the cost — $0.10 per million input tokens and $0.40 per million output tokens — making it the go-to choice for high-volume production workloads where per-call economics matter. Users consistently highlight the million-token context window as a practical win, letting entire codebases or lengthy documents land in a single request. The multimodal support (text, image, audio, video) is a bonus for pipelines that mix content types. The honest trade-off: reasoning is limited by design. Thinking mode is off by default, and the model isn't suited for complex multi-step logic without external scaffolding. For real-time, scale-first applications where you need speed and cost discipline, it hits the mark.
Best for
- High-volume content classification, moderation, and document processing where per-call cost control is critical
- Real-time chatbots and customer support assistants that need sub-half-second response times
- Multimodal pipelines processing mixed text, image, audio, or video inputs at scale
- Multilingual applications requiring broad language coverage (84.5% on Multilingual MMLU)
- Agentic automation workflows with tool calling and Google Search grounding where latency compounds across steps
Specifications
| Provider | |
|---|---|
| Released | 2025-07 |
| Intelligence | Low |
| Speed | Fast |
| Context window | 1,048,576 tokens |
| Max output | 65,535 tokens |
| Knowledge cutoff | January 2025 |
| Input price | $0.10 / 1M tokens |
| Output price | $0.40 / 1M tokens |
| Request cost | 1 base request |
| Plan tier | Base |
| Model ID | gemini-2.5-flash-lite |
Frequently asked questions
Input is $0.10 per million tokens for text, image, and video, and $0.30 per million for audio. Output is $0.40 per million tokens. Prompt caching drops cached input cost to $0.01 per million tokens — a 90% discount for repeated context.
One million tokens (1,048,576). This lets you pass entire books, long codebases, or large document sets in a single request without chunking.
Not by default. Thinking mode is disabled to prioritize speed and cost. For straightforward classification, extraction, or generation tasks it performs well, but complex multi-step reasoning requires enabling optional thinking budgets or using a more capable model like Gemini 2.5 Flash.
Flash-Lite delivers approximately 75% of Gemini 2.5 Flash's capability at 30% of the price. It's faster in raw throughput but trades away deeper reasoning depth. If your workload is latency- or cost-sensitive and doesn't demand heavy logic, Flash-Lite is the better pick.
Output is capped at 65,535 tokens despite the million-token input window, which limits long-form generation. The knowledge cutoff is January 2025. There is no fine-tuning support. Some users have reported occasional mid-sentence response cutoffs, tracked as a known issue.
Teams running high-volume inference pipelines, real-time assistants, or cost-constrained applications where throughput and price per call are the primary constraints — and where tasks are well-defined enough that deep reasoning isn't required.