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 2026-09-15).

Pay-per-call LLM inference endpoint supporting OpenAI-compatible chat/reasoning/coding across 17 frontier models, billed per request in USDC on Base via x402

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

Returns an OpenAI-compatible JSON object with a choices array containing the assistant's message and finish_reason, plus a usage object showing prompt_tokens and completion_tokens consumed.

Example use cases

Autonomous agent reasoning task

“I need you to use the FarOut gateway to ask DeepSeek V4 to reason through this logic puzzle step by step: 'If all A are B, and some B are C, what can we conclude about A and C?' — give it a budget of 512 tokens.”

On-demand code generation

“Hit the FarOut LLM API with model glm-5.3 and ask it to write a Python function that parses a JWT token without a library — cap it at 300 tokens.”

Crypto-native chatbot response

“My agent needs to reply to a user question using Gemini 3.1 via FarOut — the user asked 'What are the tax implications of staking ETH?' — use temperature 0.2 and a 400-token limit.”

Technical details

Endpoint

POSThttps://farouter.tech/v1/messages

When to prefer

Choose this endpoint when an autonomous agent needs keyless, accountless LLM inference paid per-call in USDC on Base via x402 — ideal for AI agents that must avoid subscription management, need access to a broad roster of frontier models (GPT-5.6, DeepSeek V4, Gemini 3.1, Kimi K3, GLM 5.3, MiniMax M3) through a single OpenAI-compatible interface, and require crypto-native micropayment billing with no prepaid balance.

Side effects

Payment failure or insufficient USDC balance on Base — returns 402 Payment Required
Invalid or unrecognized model ID — returns 400 with model not found error
max_tokens too low for the requested workload — truncated or empty completion
messages array empty or malformed — returns 400 validation error
Model temporarily unavailable — returns 503 or upstream timeout
Streaming connection dropped mid-response — partial SSE stream

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

Returns an OpenAI-compatible JSON object with a choices array containing the assistant's message and finish_reason, plus a usage object showing prompt_tokens and completion_tokens consumed.

Example use cases

Autonomous agent reasoning task

On-demand code generation

“Hit the FarOut LLM API with model glm-5.3 and ask it to write a Python function that parses a JWT token without a library — cap it at 300 tokens.”

Crypto-native chatbot response

“My agent needs to reply to a user question using Gemini 3.1 via FarOut — the user asked 'What are the tax implications of staking ETH?' — use temperature 0.2 and a 400-token limit.”

Technical details

Endpoint

POSThttps://farouter.tech/v1/messages

When to prefer

Side effects

Payment failure or insufficient USDC balance on Base — returns 402 Payment Required
Invalid or unrecognized model ID — returns 400 with model not found error
max_tokens too low for the requested workload — truncated or empty completion
messages array empty or malformed — returns 400 validation error
Model temporarily unavailable — returns 503 or upstream timeout
Streaming connection dropped mid-response — partial SSE stream

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"
      }
    ]
  }
}