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AgentRXI Llama 3.2 1B Instruct Chat Completions
x402
AgentRXI Llama 3.2 1B Instruct Chat Completions is a paid API for AI agents from agentrxi.com, paid per call via x402, $0.00262/call, status unknown (last checked 2026-10-15).
Runs a prompt through Meta's Llama 3.2 1B Instruct model and returns a chat completion response, billed per token via USDC with no API key required.
Price / call$0.00262
Success—
StatusUnknown
How this service works
AgentRXI: the largest pay-per-call tool market for AI agents. Web research, 22 LLMs priced per token, rent-a-browser, code sandbox, file storage, agent databases, KYB and wallet trust checks, a prompt-injection firewall, economic data, maps and more. Pay per call in USDC with x402. No key, no signup.
Output
Returns an OpenAI-compatible JSON object containing the assistant's generated message text, finish reason (e.g. 'stop'), token usage breakdown (prompt tokens, completion tokens, total tokens), model name ('llama-3.2-1b-instruct'), and a unique completion ID.
Example use cases
Low-cost draft email generation
“Use the small Llama model to draft a short professional reply to this email: 'Hi, can you send me the Q3 report by Friday?' — keep it under 100 tokens and polite in tone.”
Quick language translation snippet
“Translate this sentence into French using the Llama 1B model: 'The meeting has been rescheduled to next Tuesday at 3pm.' Just give me the translation, nothing else.”
Lightweight classification with no signup
“Without any API key, use the pay-per-call Llama 1B model to classify this sentence as positive, negative, or neutral: 'The delivery was late but the product quality was excellent.' Return just the label.”
Technical details
Endpoint
GEThttps://agentrxi.com/v1/llama1b/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a very fast, low-cost LLM inference call with no API key or signup — ideal for simple classification, short translations, quick drafts, or agentic subtasks where a small 1B model suffices. Prefer this over larger models when latency and cost are top priorities and the task does not require deep reasoning or long context.
Side effects
- Missing required 'prompt' query parameter returns a validation error
- Exceeding max_tokens budget may truncate output prematurely
- Model may produce low-quality output for complex reasoning tasks given its 1B parameter size
- USDC payment failure or insufficient balance blocks the call
- High temperature values may produce incoherent or repetitive output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "chatcmpl-...",
"model": "llama-3.2-1b-instruct",
"usage": {
"total_tokens": 18,
"prompt_tokens": 14,
"completion_tokens": 4
},
"object": "chat.completion",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Bonjour !"
},
"finish_reason": "stop"
}
]
}
}Tags
x402
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