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LLM API Chat Completions (agents.llmapi.ai)
LLM API Chat Completions (agents.llmapi.ai) is a paid API for AI agents from agents.llmapi.ai, paid per call via MPP, price unknown, status unknown (last checked 2026-10-17).
Generates a chat completion response from a curated set of frontier LLMs (GPT, Claude, Gemini, DeepSeek, Grok, Kimi, GLM) via an OpenAI-compatible interface, billed per call.
Price / call—
Success—
StatusUnknown
How this service works
Proxies chat completion requests to upstream providers.
Output
Returns an OpenAI-style chat completion object containing the assistant's generated message, the model used, finish reason, and token usage counts (prompt tokens, completion tokens, total tokens). The response is synchronous (non-streaming).
Example use cases
Frontier model response routing
“Send the user's question to claude-opus-5 and return the answer — the question is: 'What are the main differences between supervised and unsupervised learning?' Cap the response at 300 tokens.”
Rapid prototyping with gpt-5-mini
“I need a quick answer from gpt-5-mini: ask it to write a three-sentence product description for a reusable water bottle, and keep it under 100 tokens.”
Multi-model comparison pipeline
“Run this prompt through both deepseek-v4-pro and gemini-3.7-flash: 'List five creative names for a jazz café.' Return both responses so I can compare them.”
Technical details
Endpoint
POSThttps://agents.llmapi.ai/zc/v1/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need pay-per-call access to a curated set of frontier models (GPT-5, Claude, Gemini, DeepSeek, Grok, Kimi, GLM) through a single OpenAI-compatible interface without managing per-provider subscriptions. It is especially useful for agents that need to dynamically select among multiple frontier models, want transparent per-call billing, or operate in environments where committing to a single provider subscription is impractical.
Side effects
- Invalid or unsupported model ID returns a validation error
- Exceeding max_tokens limit for the chosen model causes a truncation or error
- stream:true is rejected — must be false or omitted
- Missing required fields (model or messages) returns a 400 bad request
- Payment/authentication failure returns a 401 or 402 error
- Model-specific context length exceeded returns an error
- Network timeout if the upstream LLM is slow to respond
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| modelrequired | string | One of the storefront model ids. |
| stream | boolean | Must be false or omitted on this storefront. |
| messagesrequired | array | OpenAI style message list. |
| max_tokens | integer | Output token ceiling for this call. |
Reviews
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Zero review prompt (fires after every successful call)
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