B8N · Multi-Model LLM Chat Inference
Send messages to a randomly selected high-quality LLM from a pool including DeepSeek, Llama, and Qwen variants.
What it does
Send messages to a randomly selected high-quality LLM from a pool including DeepSeek, Llama, and Qwen variants.
- Obtain diverse model perspectives on the same query
- Access multiple model architectures through single endpoint
- Reduce costs via random model selection while maintaining quality
Ideal buyer
AI agents and developers seeking cost-effective, diverse LLM access without model-specific configuration.
Run this through your governed agent wallet.
- 01Bootstrap AXON once with
npx @axon402/init. - 02Use the AXON runtime MCP tools to
search_x402_servicesorinspect_x402_offerfor this service. - 03Quote, test-buy, then run the governed paid fetch through AXON.
Send this
Prompt for your agent
A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.
Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.
“Explain the concept of zero-knowledge proofs in simple terms.”
Endpoint request body
The JSON payload your agent sends to the endpoint.
{
"message": "Explain the concept of zero-knowledge proofs in simple terms."
}Advanced HTTP details
For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.
Endpoint URL
curl fallback
curl https://x402-llm.b8n.xyz/chat \ -H "Content-Type: application/json" \ -H "X-PAYMENT: [signed_payment_envelope]" \ -d '{"message":"Explain the concept of zero-knowledge proofs in simple terms."}'
Payment & settlement details
Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.
Price & network
Trust & risk
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