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x402engine Gemini 3.5 Flash Lite LLM
x402
x402engine Gemini 3.5 Flash Lite LLM is a paid API for AI agents from x402engine.app, paid per call via x402, $0.00349/call, status unknown (last checked 2026-10-11).
Sends a chat message to Google's Gemini 3.5 Flash Lite model and returns an OpenAI-compatible response, billed per call via USDC micropayment over HTTP 402
Price / call$0.00349
Success—
StatusUnknown
How this service works
125 production APIs behind HTTP 402 micropayments. 87 LLMs, Kling V3 and Hailuo video generation, image generation, code execution, travel search, web scraping, TTS, and transaction simulation. Pay with USDC on Base, USDm on MegaETH, or USDC on Solana.
Output
An OpenAI-compatible JSON object containing the model name ('google/gemini-3.5-flash-lite'), a choices array with the assistant message (role, content), finish_reason, and a top-level content field. When streaming is enabled, returns SSE chunks in OpenAI streaming format after HTTP 402 payment settlement.
Example use cases
Rapid content drafting with Gemini
“Use the Gemini 3.5 Flash Lite model to write a short product description for a wireless ergonomic keyboard — keep it under 100 words, professional tone.”
Tool-calling agent with function definitions
“Call Gemini 3.5 Flash Lite with my messages array and this function definition for get_weather(location: string) — I want the model to decide whether to call it based on the user's question 'What's the weather in Tokyo right now?'”
Multimodal image analysis chat
“Send this image URL to Gemini 3.5 Flash Lite along with the user message 'Describe what you see in this photo and identify any text visible' and return the assistant's response.”
Technical details
Endpoint
POSThttps://x402engine.app/api/llm/gemini-3.5-flash-lite?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, low-cost Google Gemini model with OpenAI-compatible API format and want to pay per call in USDC without a monthly subscription. Ideal for AI agents running intermittent inference tasks, budget-sensitive pipelines, or situations where you need Google's multimodal capabilities (image, video, audio, PDF) without managing API keys. Prefer this over OpenAI GPT models when Gemini's reasoning style or pricing ($0.00349/call) fits better, and over direct Google API access when you want HTTP 402 micropayment billing on Base, MegaETH, or Solana.
Side effects
- Payment not settled — HTTP 402 returned if USDC/USDm payment header is missing or insufficient
- Model does not support requested parameter (seed, stop, top_p) — check /docs/llm-capabilities.md
- Invalid messages array — missing required 'role' field or malformed content
- Tool call schema mismatch — function definition does not conform to required schema
- Streaming not supported in certain client environments — SSE connection drops
- Rate limit or capacity error from underlying Google Gemini API
- Unsupported content type in multimodal messages — image/video/audio URL unreachable
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"model": "google/gemini-3.5-flash-lite",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello!"
},
"finish_reason": "stop"
}
],
"content": "Hello!"
}
}Tags
x402
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