import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "perceptron/perceptron-mk1", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "perceptron/perceptron-mk1", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"perceptron/perceptron-mk1","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Mk1 This page | Reasoning + agents | |||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Mk1 has a 32,768 tokens context window and can return up to 8,192 tokens.
Mk1 takes image, text as input and returns text.
Use perceptron/perceptron-mk1 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Mk1 is priced at input $0.20631 / 1M tokens, output $2.0631 / 1M tokens.
Yes, Mk1 can stream responses as they are generated.
Yes, Mk1 accepts image input alongside text.
Mk1 is a chat model that accepts text and image input, supports reasoning, tool calls, structured outputs, and web search.
Yes, reasoning is listed as one of Mk1's supported features and capabilities.