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Gemini 3.5 Flash Lite API

Google

72% cheaper than OpenRouter

Gemini 3.5 Flash Lite is Google’s high-efficiency multimodal model for focused subagent tasks, multi-agent workflows, reasoning, tools, and structured outputs.

About Gemini 3.5 Flash Lite

Gemini 3.5 Flash Lite is a large language model developed by Google. It's particularly well-suited for analyzing images, screenshots, and visual content, tackling complex, multi-step reasoning problems, orchestrating tool-using agents that call APIs and external services, grounding responses in real-time web search results, producing structured outputs for reliable data extraction, and handling large contexts of up to 1M tokens. Its 1M-token context window means you can pass in entire documents, codebases, or conversation histories without losing context. Developers choose Gemini 3.5 Flash Lite when they need reliable, production-quality AI inference through a simple API — and on Qubax, it's available at a fraction of the cost of traditional providers.

In the broader AI landscape, Gemini 3.5 Flash Lite sits among the frontier-tier offerings from Google With advanced reasoning and multimodal vision and agentic tool use, it competes with the most frontier-tier models on the market. What sets it apart on Qubax isn't just the model itself — it's the accessibility. Rather than dealing with enterprise contracts or traditional payment rails, you get instant access via an OpenAI-compatible endpoint. That means you can drop Gemini 3.5 Flash Lite into Cursor, Cline, LangChain, or any framework that speaks the OpenAI protocol and start building immediately.

Qubax offers Gemini 3.5 Flash Lite at 72% below OpenRouter's price — just $0.086 per million input tokens and $0.713 per million output tokens. That pricing advantage compounds quickly at scale: a high-volume application sending millions of tokens per day can save significantly compared to using OpenRouter or the provider directly. And because Qubax runs on crypto-native infrastructure, you can pay with USDC, USDT, ETH, BTC, or 200+ other cryptocurrencies — no credit card or bank account required.

Pricing

Token TypeQubaxOpenRouterYou Save
Input (per 1M tokens)$0.086$0.30072%
Output (per 1M tokens)$0.713$2.5072%

Prices per 1 million tokens. Pay with 200+ cryptocurrencies.

Price History (60 Days)

Sep 1 Sep 13 24.00% cheaper than last week

This model's price over the last 60 days. Compare against all top AI models →

Estimated Monthly Cost

AI Chatbot
$15.82/mo
$55.50 on OpenRouter
Coding Copilot
$31.63/mo
$111.00 on OpenRouter
AI Agent
$23.51/mo
$82.50 on OpenRouter

Specifications

Context Window
1M
Max Output
66K
Provider
Google
Modality
MULTIMODAL

Use Cases

Visual Analysis
Analyze images, screenshots, diagrams, and visual content
Complex Reasoning
Multi-step problem solving, math, and logical analysis
Function Calling
Build agents and tool-using applications
Long Documents
Process entire codebases, books, or lengthy conversations
Chat & Conversation
Build AI chatbots and conversational assistants
Content Generation
Write articles, code, emails, and more

Capabilities

Vision Reasoning reasoning Configurable Tool Use File Upload pdf Streaming Structured Output json Schema Web Search Seed Control

Quick Start

Python
from openai import OpenAI

client = OpenAI(
    base_url="https://api.qubax.ai/v1",
    api_key="qbx_live_YOUR_API_KEY",
)

response = client.chat.completions.create(
    model="gemini-3-5-flash-lite",
    messages=[
        {"role": "user", "content": "Hello!"}
    ],
)

print(response.choices[0].message.content)
JavaScript
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.qubax.ai/v1",
  apiKey: "qbx_live_YOUR_API_KEY",
});

const response = await client.chat.completions.create({
  model: "gemini-3-5-flash-lite",
  messages: [{ role: "user", content: "Hello!" }],
});

console.log(response.choices[0].message.content);
cURL
curl https://api.qubax.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer qbx_live_YOUR_API_KEY" \
  -d '{
    "model": "gemini-3-5-flash-lite",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Get your API key from the dashboard.

Why use Gemini 3.5 Flash Lite on Qubax?

72% Cheaper

Up to 72% off OpenRouter prices

Pay with Crypto

200+ coins (BTC, ETH, SOL, USDT, USDC & more). No credit card needed.

OpenAI Compatible

Drop-in replacement. Works with Cline, Cursor, any tool.

Get started →

More from Google

Compare Gemini 3.5 Flash Lite with alternatives

ModelProviderInput / 1MOutput / 1Mvs Gemini 3.5 Flash Lite
Gemini 3.5 Flash LiteGoogle$0.086$0.713
DeepSeek V4 Flash (Morpheus Web)DeepSeek$0.171$0.352More expensive
GPT-5.4 Image 2OpenAI$0.120$0.225More expensive
Qwen 3.6 35B A3B (E2EE)Alibaba$0.134$0.867More expensive
Meta: Muse Spark 1.2 ContributorMeta$0.068$0.135 Cheaper

Frequently Asked Questions

How much does the Gemini 3.5 Flash Lite API cost?

On Qubax, Gemini 3.5 Flash Lite costs $0.086 per 1M input tokens and $0.713 per 1M output tokens. This is 72% cheaper than OpenRouter's price of $0.300 per 1M input tokens.

Is the Gemini 3.5 Flash Lite API compatible with OpenAI?

Yes. Qubax provides an OpenAI-compatible API. You can use Gemini 3.5 Flash Lite as a drop-in replacement by changing your base URL to https://api.qubax.ai/v1 and using your Qubax API key. It works with Cline, Cursor, OpenCode, Hermes Agent, and any tool that supports OpenAI APIs.

Why is Gemini 3.5 Flash Lite cheaper on Qubax than OpenRouter?

Qubax sources AI inference from an open compute marketplace on the Base blockchain where GPU providers compete on price. We pass the savings to you — 72% cheaper than OpenRouter's price for Gemini 3.5 Flash Lite.

How do I pay for Gemini 3.5 Flash Lite API usage?

Qubax uses prepaid crypto credits. Deposit USDC on the Base chain and your balance is automatically deducted as you use the API. No credit card required. Top up from $3.

What is the context window of Gemini 3.5 Flash Lite?

Gemini 3.5 Flash Lite supports a context window of 1M tokens, allowing you to process large documents, codebases, or long conversations in a single request.

What can I build with Gemini 3.5 Flash Lite?

Gemini 3.5 Flash Lite is versatile enough for a wide range of applications. You can use it to analyze images and visual content, tackle complex multi-step reasoning tasks, build autonomous agents that call external tools and APIs, answer questions with real-time web search, generate structured JSON output for data pipelines, process long documents and entire codebases, and more. Because it's served through Qubax's OpenAI-compatible API, integration into existing apps, agents, or workflows takes just a few lines of code.

How fast is Gemini 3.5 Flash Lite on Qubax?

Gemini 3.5 Flash Lite on Qubax supports streaming responses, so tokens begin arriving in real time as they're generated. Latency depends on the provider and prompt complexity, but most requests start streaming within 200–800 milliseconds. Qubax routes requests through an intelligent routing layer, which selects the fastest available compute provider for each request — so you get competitive latency at a lower price.

Gemini 3.5 Flash Lite vs DeepSeek V4 Flash (Morpheus Web): which should I choose?

Gemini 3.5 Flash Lite by Google and DeepSeek V4 Flash (Morpheus Web) by DeepSeek are both strong models in a similar price tier. Gemini 3.5 Flash Lite excels at complex reasoning and supports vision/image inputs. DeepSeek V4 Flash (Morpheus Web) comes from a different lab and may have different strengths depending on your workload. On Qubax, Gemini 3.5 Flash Lite starts at $0.086/1M input tokens versus DeepSeek V4 Flash (Morpheus Web)'s $0.171/1M — making Gemini 3.5 Flash Lite the more cost-effective option for high-volume workloads. Both are available on Qubax with crypto payments and OpenAI-compatible APIs, so you can try each and switch freely.

Can I use Gemini 3.5 Flash Lite for commercial projects?

Yes. Gemini 3.5 Flash Lite on Qubax can be used for commercial purposes. You own the outputs you generate. Qubax provides the API infrastructure — you bring your use case.

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