FarOut GLM-5.2 Chat Completions (Pay-Per-Call via x402)

x402

FarOut GLM-5.2 Chat Completions (Pay-Per-Call via x402) is a paid API for AI agents from farouter.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).

Runs a chat completion request against the GLM-5.2 model via a keyless, pay-per-call API using USDC on Base through the x402 protocol

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

Fixed-price chat completions for glm-5.2 on FarOut: flat $0.002 per call (includes up to 4,000 input + 1,000 output tokens). Rate: $0.011/1M input tokens, $0.035/1M output tokens. Pay with USDC on Base using x402. No API key, no account, no prepaid balance.

Output

Returns an OpenAI-compatible JSON response containing an array of choices, each with an assistant message (role + content), a finish_reason (e.g. 'stop'), and a usage object with prompt_tokens and completion_tokens counts.

Example use cases

Autonomous agent self-funded LLM calls

“I'm building an autonomous agent that needs to call an LLM on the fly without any pre-registered API keys or subscription. Use FarOut to send this system prompt 'You are a helpful assistant' and user message 'Summarize the pros and cons of microservices' to GLM-5.2, paying per call with USDC, and give me back the answer with up to 500 tokens.”

Crypto-native coding assistant query

“Ask GLM-5.2 via FarOut to write a Python function that validates an Ethereum address — pay per use with USDC on Base, no account required, and stream the response back to me.”

On-demand reasoning without subscription

“I don't want to maintain API keys or prepaid balances. Use FarOut's pay-per-call gateway to send GLM-5.2 this question: 'What are the key trade-offs between proof-of-work and proof-of-stake consensus mechanisms?' — limit it to 400 output tokens and return the full reply.”

Technical details

Endpoint

POSThttps://farouter.tech/v1/models/glm-5.2/chat/completions

When to prefer

Choose this endpoint when you need keyless, accountless LLM inference paid per-call in USDC via x402, especially for autonomous agents or workflows that cannot pre-register API keys or maintain prepaid balances. Prefer it over traditional LLM APIs (OpenAI, Anthropic direct) when you want crypto-native micropayments, zero onboarding friction, and OpenAI-compatible message formatting. Prefer GLM-5.2 specifically for Chinese-language tasks or when routing away from GPT/Gemini family models for cost or diversity reasons.

Side effects

Payment rejected or insufficient USDC balance — x402 payment handshake fails before inference runs
Invalid model ID — returns an error if the specified model is not available on the gateway
Message array is empty (minItems:1 violated) — request rejected with a validation error
max_tokens or temperature out of allowed range — schema validation error
Streaming connection drops mid-response — partial SSE stream with no final message
Model temporarily unavailable on the upstream provider — gateway returns a 503 or similar error

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

Example use cases

Autonomous agent self-funded LLM calls

Crypto-native coding assistant query

“Ask GLM-5.2 via FarOut to write a Python function that validates an Ethereum address — pay per use with USDC on Base, no account required, and stream the response back to me.”

On-demand reasoning without subscription

Technical details

Endpoint

POSThttps://farouter.tech/v1/models/glm-5.2/chat/completions

When to prefer

Side effects

Payment rejected or insufficient USDC balance — x402 payment handshake fails before inference runs
Invalid model ID — returns an error if the specified model is not available on the gateway
Message array is empty (minItems:1 violated) — request rejected with a validation error
max_tokens or temperature out of allowed range — schema validation error
Streaming connection drops mid-response — partial SSE stream with no final message
Model temporarily unavailable on the upstream provider — gateway returns a 503 or similar error

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"
      }
    ]
  }
}