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AgentRXI Llama 3.1 8B Chat Completions
x402
AgentRXI Llama 3.1 8B Chat Completions is a paid API for AI agents from agentrxi.com, paid per call via x402, $0.003183/call, status unknown (last checked 2026-10-15).
Runs OpenAI-compatible chat completions on Meta Llama 3.1 8B Instruct, billed per token via x402 micropayments instead of an API key.
Price / call$0.003183
Success—
StatusUnknown
How this service works
OpenAI-compatible chat completions on Meta Llama 3.1 8B, fast general chat. Set your OpenAI SDK base URL to https://agentrxi.com/v1 and pay per token with x402 instead of an API key: $0.135 per million input and $1.152 per million output tokens, minimum $0.002 a call, at most $0.0053. The 402 quotes your request's maximum; "upto" payers are charged only the tokens used. Same request/response shape as OpenAI (streaming supported), up to 2048 output tokens. Pass model to use an
Output
Returns an OpenAI-format JSON object with a choices array containing the assistant message content, finish_reason, and an index; plus a usage object with prompt_tokens, completion_tokens, and total_tokens, and the model name.
Example use cases
Quick text summarization for agents
“Use Llama 3.1 8B to summarize this customer support transcript in 3 bullet points: 'Customer called about a billing error on their March invoice, agent confirmed the overcharge and issued a $12 refund, case closed.' Keep it concise.”
Lightweight coding assistant call
“Ask the Llama 3.1 8B model to write a Python function that takes a list of integers and returns only the even ones — I want a clean, well-commented answer.”
On-demand translation for a chatbot
“Have Llama 3.1 8B translate this English phrase into French: 'Your order has been shipped and will arrive in 3 business days.' Use a temperature of 0.2 so the result is consistent.”
Technical details
Endpoint
GEThttps://agentrxi.com/v1/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, low-cost general-purpose chat completions with a small open-source model (Llama 3.1 8B) and want to pay per token via x402 micropayments rather than maintaining an API key subscription. It is ideal for high-volume, latency-sensitive agent workloads where cost control matters and the task does not require frontier-model reasoning. Prefer the DeepSeek or QwQ siblings on this platform for math, logic, or chain-of-thought tasks.
Side effects
- Insufficient x402 payment balance causes 402 error before completion
- Prompt too long for 2048 output token limit causes truncation or error
- Malformed prompt or missing required field returns 400 bad request
- Model occasionally produces low-quality output on complex reasoning tasks beyond 8B capability
- Temporary service unavailability returns 503
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "chatcmpl-...",
"model": "llama-3.1-8b-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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