FarOut LLM Gateway

x402

FarOut LLM Gateway is a paid API for AI agents from farouter.tech, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-13).

Pay-per-call LLM chat completion inference over x402 micropayments, supporting 17 frontier models with no API key or account required

Price / call$0.001

Seller volume →—

Success—

StatusUnknown

How this service works

[OI]-compatible LLM inference API for autonomous agents. Supports reasoning, coding and chat workloads. Pay with USDC on Base using x402 (upto scheme, true-up billing): the 402 quotes a spending CAP (estimated input tokens + your max_tokens at the model's per-1M price), and after the model answers you are settled for the ACTUAL usage — always <= the cap, never more. Minimum $0.001, cap $3.0 per call. Cached input bills at 10%. Failed calls are never charged. Any model from GET /v1/models.

Output

An OpenAI-compatible JSON response containing one or more choices with the assistant's message content, finish reason (e.g. 'stop'), and token usage counts (prompt_tokens, completion_tokens).

Example use cases

Autonomous agent reasoning task

“Have FarOut call Kimi K3 with up to 1024 output tokens and ask it: 'Given this user's transaction history, identify any anomalous spending patterns and explain your reasoning.'”

Code generation without API subscription

“Use FarOut to ask GPT-5.6 with temperature 0.2 and 800 max tokens to write a Python function that parses ISO 8601 timestamps and converts them to Unix epoch — no API key, just pay per call.”

Multi-model comparison for chat response

“Send the same user message — 'What are the key differences between transformer and mamba architectures?' — to both Gemini 3.1 and GLM 5.3 via FarOut, each with 600 max tokens, and compare their responses.”

Technical details

Endpoint

POSThttps://farouter.tech/v1/chat/completions

When to prefer

Choose FarOut when your agent needs on-demand LLM inference with no prior account setup, no prepaid credits, and no API key management — paying per call in USDC on Base via x402. Ideal for autonomous agents that need to call multiple frontier models (GPT-5.6, Gemini 3.1, DeepSeek V4, Kimi K3, GLM 5.3, MiniMax M3) without vendor lock-in, or when operating in trustless environments where holding API credentials is undesirable. Prefer alternatives when you need guaranteed rate limits, SLA-backed uptime, or persistent fine-tuned model access.

Side effects

Insufficient USDC balance on Base — payment rejected before inference runs
Invalid or unsupported model ID — returns error listing available models
messages array is empty or malformed — validation error before model call
max_tokens set too high for selected model's context window — truncation or error
Network timeout or model provider outage — gateway returns 5xx
Streaming requested but client does not handle SSE — partial response consumption failure

Input

Schema · Request body

Field	Type	Description
model	string	Model id from GET /v1/models, e.g. glm-5.3. No provider prefix.
stream	boolean	SSE streaming.
messages	array	Chat messages, [OI]-compatible {role, content}.
max_tokens	integer	Output token budget. Sets your spending cap; actual usage is what gets settled (true-up).
temperature	number	Sampling temperature.
max_completion_tokens	integer	Alias of max_tokens (gpt-5.x models).

Output

Schema · Response

{
  "type": "json",
  "example": {
    "usage": {
      "prompt_tokens": 6,
      "completion_tokens": 8
    },
    "choices": [
      {
        "message": {
          "role": "assistant",
          "content": "Hello! How can I help?"
        },
        "finish_reason": "stop"
      }
    ]
  }
}

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How this service works

Output

An OpenAI-compatible JSON response containing one or more choices with the assistant's message content, finish reason (e.g. 'stop'), and token usage counts (prompt_tokens, completion_tokens).

Example use cases

Autonomous agent reasoning task

“Have FarOut call Kimi K3 with up to 1024 output tokens and ask it: 'Given this user's transaction history, identify any anomalous spending patterns and explain your reasoning.'”

Code generation without API subscription

“Use FarOut to ask GPT-5.6 with temperature 0.2 and 800 max tokens to write a Python function that parses ISO 8601 timestamps and converts them to Unix epoch — no API key, just pay per call.”

Multi-model comparison for chat response

Technical details

Endpoint

POSThttps://farouter.tech/v1/chat/completions

When to prefer

Side effects

Insufficient USDC balance on Base — payment rejected before inference runs
Invalid or unsupported model ID — returns error listing available models
messages array is empty or malformed — validation error before model call
max_tokens set too high for selected model's context window — truncation or error
Network timeout or model provider outage — gateway returns 5xx
Streaming requested but client does not handle SSE — partial response consumption failure

Input

Schema · Request body

Field	Type	Description
model	string	Model id from GET /v1/models, e.g. glm-5.3. No provider prefix.
stream	boolean	SSE streaming.
messages	array	Chat messages, [OI]-compatible {role, content}.
max_tokens	integer	Output token budget. Sets your spending cap; actual usage is what gets settled (true-up).
temperature	number	Sampling temperature.
max_completion_tokens	integer	Alias of max_tokens (gpt-5.x models).

Output

Schema · Response

{
  "type": "json",
  "example": {
    "usage": {
      "prompt_tokens": 6,
      "completion_tokens": 8
    },
    "choices": [
      {
        "message": {
          "role": "assistant",
          "content": "Hello! How can I help?"
        },
        "finish_reason": "stop"
      }
    ]
  }
}