LLM inference proxy
LLM inference proxy - send an OpenAI-format chat/completions request and get a response from GPT-4o-mini. Supports vision (up to 2 image URLs, low detail) and structured output (response_format: json_object or json_schema). No API key needed; pay per call via x402. Input capped at 16k chars, output at 4096 tokens.
Not tested: has real-world effectsour last check, 2026-09-24
0 of 0checks answered this week
n/amedian answer time
$0.01listed price per call
n/aprice it asked us
Paid test badge: not yet. The checks above are free: we call the tool without paying and read the payment request it sends back. The Verified badge needs paid calls whose answers match the promised output, and nobody can buy a badge.
Endpoint
POST https://agent402.tools/api/llm
| Category | Image and media |
|---|---|
| Provider host | agent402.tools |
| Networks | algorand:wGHE2Pwdvd7S12BL5FaOP20EGYesN73ktiC1qzkkit8=, eip155:10, eip155:1329, eip155:137, eip155:143, eip155:42161, eip155:42220, eip155:43114, eip155:4663, eip155:8453, solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp, stellar:pubnet |
| Payment schemes | exact, upto |
| Self-reported calls, 30 days | 13 from 3 payers (the provider's figure, not ours) |
Our checks, last 30 days
We never call tools that send, buy, move money or file anything, not even without paying.
Example input (from the provider)
{
"body": {
"max_tokens": 64,
"messages": [
{
"content": "Say hello in one sentence.",
"role": "user"
}
],
"model": "gpt-4o-mini"
},
"bodyType": "json",
"method": "POST",
"type": "http"
}
Promised output schema (from the provider)
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"properties": {
"max_tokens": {
"description": "Max output tokens (default 1024, cap 4096)",
"type": "number"
},
"messages": {
"description": "Array of {role, content} objects. content can be a string or array of {type:'text',text} and {type:'image_url',image_url:{url,detail}} blocks",
"type": "array"
},
"model": {
"description": "Model ID - gpt-4o-mini",
"type": "string"
},
"response_format": {
"description": "Optional: {type:\"json_object\"} or {type:\"json_schema\",json_schema:{name,schema}}",
"type": "object"
},
"stop": {
"description": "Stop sequence(s)",
"type": "string"
},
"temperature": {
"description": "Sampling temperature (0-2)",
"type": "number"
},
"top_p": {
"description": "Nucleus sampling (0-1)",
"type": "number"
}
},
"required": [
"model",
"messages"
]
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"properties": {
"choices": {
"items": {
"properties": {
"finish_reason": {
"type": "string"
},
"message": {
"properties": {
"content": {
"type": "string"
},
"role": {
"type": "string"
}
},
"type": "object"
}
},
"type": "object"
},
"type": "array"
},
"model": {
"type": "string"
},
"provider": {
"type": "string"
},
"usage": {
"properties": {
"completion_tokens": {
"type": "integer"
},
"prompt_tokens": {
"type": "integer"
},
"total_tokens": {
"type": "integer"
}
},
"type": "object"
}
},
"required": [
"model",
"provider",
"usage",
"choices"
],
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}