gemini-2.0-flash-lite-001
Neural Network
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 048 576 tokens
- Max answer length
- 32 000 tokens
- Capabilities
- function calling, Batch API
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
Image prompt
(per 1K tokens)
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: '<your bothub access token>',
baseURL: 'https://openai.bothub.chat/v1'
});
// Sync - Text generation
async function main() {
const chatCompletion = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gemini-2.0-flash-lite-001',
});
}
// Async - Text generation
async function main() {
const stream = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gemini-2.0-flash-lite-001',
stream: true
});
for await (const chunk of stream) {
const part: string | null = chunk.choices[0].delta?.content ?? null;
}
}
main();
How it works gemini-2.0-flash-lite-001?
Frequently asked questions about gemini-2.0-flash-lite-001
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a fast Google model for text tasks: summarization, data extraction, document Q&A, code assistance, and streaming processing of large volumes of text. It accepts images and documents as input and supports function calling. The context is 1,048,576 tokens, so an entire report or codebase fits into a single request.
In a single response, the model outputs up to 32,000 tokens — enough for a lengthy article, detailed instructions, a large JSON, or a significant code snippet. If you need more, ask it to continue: the huge input context allows it to keep the entire previous text in the dialogue without losing the thread.
A reasoning mode is not explicitly noted in our data, but that doesn't mean it's absent. The model answers quickly and to the point. If you need step-by-step reasoning, ask for it directly in the prompt — or switch to a reasoning model in the same window.
Yes. Function calling and structured JSON output are supported — the model can be embedded into agents, connected to external services, and provide predictable responses based on a schema. In BotHub, this works via a unified OpenAI-compatible API, so switching models won't require rewriting your integration.
According to our data, images and documents are accepted as input: upload a scan, photo, PDF, or spreadsheet and ask to analyze the content, extract specific fields, or create a summary. Support for audio and video is not noted in our data — it's worth testing with your own file.
We don't have data on specific language support, so we won't make promises — it's easier to check the quality with your own task. In BotHub, this takes a minute: pay-as-you-go for tokens, no subscription, no VPN, and no foreign card required. If it doesn't fit, switch to another model in the same window.