1M Token Massive Context
Ingest entire technical manuals or legal archives at once. The signature 1M context window allows for large-scale RAG and deep document analysis at a fraction of the price of larger models.
gemini-3.5-flash-lite / web-search
Gemini 3.5 Flash Lite API offers sub-second latency and a massive 1M token context window. Optimized for high-frequency tasks, this Google model provides multimodal support and elite JSON extraction at a fraction of the cost of standard models.
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Key Gemini 3.5 Flash Lite API Capabilities
Explore the core technical strengths of the Gemini 3.5 Flash Lite API, from its massive memory to its industry-leading speed, designed specifically for high-efficiency enterprise deployments.
Native Multimodal Support
Process images, video up to one hour, audio, and PDFs natively. Gemini 3.5 Flash-Lite achieves a 68.2% score on MMMU benchmarks, outperforming many text-only lite competitors significantly.
Structured JSON Reliability
Features an optimized internal head for schema adherence, resulting in a 98% success rate on complex nested extraction. Perfect for converting unstructured data into actionable insights.
Sub-100ms Response Speed
Optimized for an instant-feel, the model delivers a Time To First Token approximately 30-40% faster than standard versions, ensuring smooth user experiences in chat and real-time tools.
How to Get a gemini-3.5-flash-lite API Key
Getting a gemini-3.5-flash-lite API key takes four steps and a few minutes. Create a free GPTProto account, add credits, generate your key, and make your first call — at $0.18 / $1.5 it's a cheaper gemini-3.5-flash-lite API key than going direct, and one key works across every model on the platform. Full gemini-3.5-flash-lite Documentation is in the docs.
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Create your free GPT Proto account to begin. You can set up an organization for your team at any time.
Top up
Your balance can be used across all models on the platform, including gemini-3.5-flash-lite, giving you the flexibility to experiment and scale as needed.
Generate your API key
In your dashboard, create an API key — you'll need it to authenticate when making requests to gemini-3.5-flash-lite.
Make your first API call
Use your API key with our sample code to send a request to gemini-3.5-flash-lite via GPT Proto and see instant AI-powered results.
Gemini 3.5 Flash Lite API: Common Questions
Get details on the Gemini 3.5 Flash Lite API. Learn about latency, the 1M context window, pricing, and how this model compares to others in the 3.5 family for building responsive AI applications.
What is the typical latency of the Flash Lite model?
Gemini 3.5 Flash-Lite is optimized for instant-feel applications. It delivers a Time To First Token (TTFT) that is roughly 30-40% faster than the standard Flash model on text-only prompts. For most short queries, you can expect a response within 100-200ms, making it ideal for interactive chatbots and real-time translation where latency is the most critical factor for ensuring a smooth and responsive user experience.
How large is the Gemini 3.5 Flash Lite context window?
This model features a massive 1,048,576 token context window. This allows you to process enormous amounts of data—such as hour-long videos, large codebases, or hundreds of documents—in a single request. This high efficiency enables large-scale Retrieval-Augmented Generation (RAG) at a significantly lower price point than larger models, without needing to constantly truncate or summarize your input data before processing.
What is the pricing for the Gemini 3.5 Flash Lite API?
The pricing is highly competitive at $0.075 per 1M input tokens and $0.30 per 1M output tokens. It is approximately 50% cheaper than the standard Gemini 3.5 Flash. Additionally, we offer a 50% discount on cached input tokens. This makes it the most cost-effective model per token in the entire Gemini 3.5 family, perfect for high-volume data labeling, classification, or massive document summarization pipelines.
Does this lite model support multimodal inputs?
Yes. Unlike many competitors that offer text-only lite versions, this model natively supports multimodal inputs including images, video (up to 1 hour), audio, and PDF files. It achieves an impressive 68.2% on the MMMU benchmark. This capability allows you to build sophisticated applications that can search video archives, index image libraries, or analyze complex technical documents containing charts and graphs effortlessly.
How does it compare to GPT-4o-mini?
While GPT-4o-mini is strong in reasoning, Gemini 3.5 Flash-Lite offers a much larger context window (1M vs 128k) and lower latency (120ms vs 180ms). It is also roughly 50% cheaper on input tokens. For tasks like large-scale document summarization, high-volume classification, or multimodal processing, Gemini 3.5 Flash-Lite provides a superior balance of speed, capacity, and cost-efficiency for modern developers.
Is my data used to train the Gemini models?
No. We take data privacy seriously. Any data you send via the GPTProto.com platform to the Gemini 3.5 Flash-Lite API is not used to train the underlying foundation models. We provide a unified OpenAI-compatible endpoint with consolidated billing and automatic failover across multiple Google Cloud regions to ensure higher uptime, allowing you to build enterprise-grade applications with full confidence in your data security.