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FarOut Pay-Per-Call LLM Inference (GPT-5.3-Codex)
x402
FarOut Pay-Per-Call LLM Inference (GPT-5.3-Codex) is a paid API for AI agents from farouter.tech, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-14).
Runs chat completions against GPT-5.3-Codex via a pay-per-call gateway using x402/USDC micropayments — no API key or account required.
Price / call$0.001
Success—
StatusUnknown
How this service works
Fixed-price chat completions for gpt-5.3-codex on FarOut: flat $0.001 per call (includes up to 4,000 input + 1,000 output tokens). Rate: $0.063/1M input tokens, $0.504/1M output tokens. Pay with USDC on Base using x402. No API key, no account, no prepaid balance.
Output
Returns an OpenAI-compatible JSON object with a choices array containing the assistant's reply message and finish_reason, plus a usage object showing prompt_tokens and completion_tokens consumed.
Example use cases
Agentic coding assistant on demand
“Have GPT-5.3-Codex write a TypeScript function that debounces async calls and include inline JSDoc comments — limit the response to 800 tokens and pay per call with USDC so I don't need to set up an account.”
Autonomous agent reasoning step
“I need my agent to think through a multi-step plan for scheduling a data pipeline — send the reasoning prompt to GPT-5.3-Codex with temperature 0.2 and a 1024-token budget, paying per call over x402.”
Zero-setup chat for a prototype app
“Route this user message to GPT-5.3-Codex and stream the reply back: 'Explain the difference between supervised and reinforcement learning in plain English' — use 300 tokens max and pay with USDC on Base.”
Technical details
Endpoint
POSThttps://farouter.tech/v1/models/gpt-5.3-codex/chat/completionsWhen to prefer
Choose this endpoint when an autonomous agent needs LLM inference without pre-registering API keys or maintaining a prepaid balance — ideal for agent-to-agent workflows, prototyping, or ephemeral tasks where pay-per-call USDC micropayments via x402 are preferable to subscription billing. Best for coding and reasoning workloads where GPT-5.3-Codex specifically is desired.
Side effects
- Payment rejected if USDC balance on Base is insufficient or x402 handshake fails
- Invalid model ID returns 400 or empty model list
- messages array missing or empty triggers schema validation error
- max_tokens set too low causes truncated or empty responses
- Streaming (SSE) misconfiguration can cause client-side parsing errors
- Rate limits or upstream model unavailability return 429 or 503
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. Drives the quote directly. |
| 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"
}
]
}
}Tags
x402
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