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x402engine Llama LLM Inference (Pay-per-call)
x402
x402engine Llama LLM Inference (Pay-per-call) is a paid API for AI agents from x402engine.app, paid per call via x402, $0.002115/call, status unknown (last checked 2026-10-12).
Runs inference on Meta's Llama 3.3 70B Instruct model via a pay-per-call HTTP 402 micropayment API, returning OpenAI-compatible chat completions
Price / call$0.002115
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
Returns an OpenAI-compatible JSON object containing the model name, an array of choices each with a message (role=assistant, content string or null), tool_calls if applicable, and a finish_reason (e.g. 'stop'). When streaming is enabled, returns SSE events with delta tokens in real time after payment settlement.
Example use cases
Agent reasoning with tool calling
“Use Llama 3.3 70B to process this conversation — system: 'You are a travel planner', user: 'What flights are available from NYC to Paris next week?' — and call the search_flights function I've defined if it decides to use it.”
Low-cost open-source LLM for content drafting
“Have Llama 3.3 70B draft a three-paragraph product description for my new ergonomic standing desk — focus on health benefits and modern design, keep it professional.”
Streaming chat completion for real-time UI
“Send this chat thread to Llama 3.3 70B with streaming enabled so I can show tokens as they arrive: system 'You are a coding tutor', user 'Walk me through how Python decorators work with a simple example.'”
Technical details
Endpoint
POSThttps://x402engine.app/api/llm/llama?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a capable open-source LLM (Llama 3.3 70B) without committing to a subscription or managing API keys — ideal for agents that pay per inference in USDC. Prefer it over proprietary LLM APIs when cost transparency per call matters, when you want OpenAI-compatible request/response format with a Llama backbone, or when your agent operates on-chain and needs micropayment-native LLM access. Use over other x402engine LLMs when Llama 3.3 70B's instruction-following and tool-calling capabilities are sufficient for the task.
Side effects
- Payment not settled — HTTP 402 returned if USDC/USDm payment is not provided or insufficient
- Invalid messages array — missing required 'role' or 'content'/'tool_calls' fields returns a validation error
- Unsupported parameter for Llama model — parameters like seed or logprobs may be silently ignored or rejected depending on model capability
- Streaming timeout — SSE stream may drop if network latency exceeds settlement window
- Tool call schema mismatch — malformed function definitions cause inference errors or ignored tool calls
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"model": "meta-llama/llama-3.3-70b-instruct",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello!"
},
"finish_reason": "stop"
}
],
"content": "Hello!"
}
}Tags
x402
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