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Available now on ModelsLab · Language Model

Google: Gemini 2.0 Flash LiteSpeed. Cost. Scale.

Try Google: Gemini 2.0 Flash LiteAPI Documentation

Build Faster. Pay Less.

Lightning-Fast

Sub-Millisecond Latency

Optimized for production workloads with minimal inference overhead and high throughput.

Multimodal Input

Text, Image, Audio, Video

Process diverse content types in a single request with native multimodal understanding.

Cost-Optimized

30% Cheaper Than Standard

Lowest-cost Gemini variant at $0.075/M input and $0.30/M output tokens.

Examples

See what Google: Gemini 2.0 Flash Lite can create

Copy any prompt below and try it yourself in the playground.

Customer Support

“Analyze this customer support ticket and generate a professional response addressing their billing inquiry. Maintain a helpful tone while referencing our standard refund policy.”

Content Summarization

“Summarize this 50-page technical documentation into a concise executive summary with key takeaways and action items for stakeholders.”

Code Documentation

“Generate clear API documentation with examples for this Python function, including parameter descriptions, return types, and common use cases.”

Data Extraction

“Extract structured data from this invoice image: company name, invoice number, total amount, and due date. Return as JSON.”

For Developers

A few lines of code.
Fast inference. Three lines.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Google: Gemini 2.0 Flash Lite

Read the docs

Gemini 2.0 Flash Lite is Google's most cost-efficient LLM, optimized for text generation at scale. It supports multimodal input (text, images, audio, video) with a 1M token context window and function calling capabilities.

Flash Lite is 30% cheaper while maintaining strong performance for text-heavy workloads. Standard Flash excels at complex reasoning and structured outputs, while Flash Lite prioritizes speed and cost efficiency.

Input limit is 1,048,576 tokens (1M context window) and output limit is 8,192 tokens per request, supporting long-form document processing and analysis.

Yes, it supports native function calling and structured outputs, enabling integration with external APIs and tools for dynamic workflows.

The model does not support code execution, image generation, audio generation, search grounding, or the Live API. It outputs text only.

Released February 25, 2025, with a knowledge cutoff of August 31, 2024. It's available via Google AI Studio, Vertex AI, and third-party providers.

Ready to create?

Start generating with Google: Gemini 2.0 Flash Lite on ModelsLab.

Try Google: Gemini 2.0 Flash LiteAPI Documentation