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x402engine Llama 4 Maverick LLM
x402
x402engine Llama 4 Maverick LLM is a paid API for AI agents from x402engine.app, paid per call via x402, $0.002801/call, status unknown (last checked 2026-10-12).
Run inference on Meta's Llama 4 Maverick model via a pay-per-call HTTP 402 micropayment API, returning OpenAI-compatible chat completions
Price / call$0.002801
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 response containing a choices array with the assistant's message (text content or tool_calls), the finish_reason (stop, tool_calls, length, etc.), and the model name. When streaming is enabled, returns OpenAI-compatible server-sent events (SSE) chunks in real time.
Example use cases
Agentic tool-calling pipeline
“Send this message thread to Llama 4 Maverick with my weather-lookup and calendar functions defined as tools, and have it decide which tool to call and with what arguments.”
Reproducible LLM evaluation run
“Run this benchmark prompt through Llama 4 Maverick with seed 42 and temperature 0 so I get a deterministic output I can compare across runs.”
Streaming chat response for a user-facing app
“Forward this user's question to Llama 4 Maverick and stream the response token-by-token back to the frontend so it appears as it's being generated.”
Technical details
Endpoint
POSThttps://x402engine.app/api/llm/llama-4-maverick?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need Meta Llama 4 Maverick specifically (strong multimodal and tool-calling capabilities) and want pay-per-call pricing with no subscription or API key — ideal for agents that need to control cost at the individual call level using crypto micropayments (USDC on Base, USDm on MegaETH, or USDC on Solana). Prefer over hosted inference APIs when you want OpenAI-compatible output format without vendor lock-in.
Side effects
- Payment not settled — HTTP 402 returned if USDC/USDm micropayment is not attached or insufficient
- Invalid messages format — missing required 'role' or both 'content' and 'tool_calls' fields causes a 422 validation error
- Unsupported parameter for model — some sampling params (seed, logprobs, min_p) may not be supported by Maverick; check /docs/llm-capabilities.md
- Context length exceeded — very long message arrays may exceed model context window and return an error
- Streaming timeout — SSE stream may drop if network latency is too high after payment settlement
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"model": "meta-llama/llama-4-maverick",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello!"
},
"finish_reason": "stop"
}
],
"content": "Hello!"
}
}Tags
x402
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Zero review prompt (fires after every successful call)
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