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LFM3-1.7B API

model: lfm-3-1.7b

A compact 1.7B-parameter text model with a 256K-token context, post-trained for agents, tool calling, and structured outputs. It reasons before it answers. Prompts and outputs may be retained and used...

CallAI pricing

Crypto OK

Input / 1M:$0.088

Output / 1M:$0.220

Specs & upstream

Upstream (in/out):$0.080 / $0.200

Context:262K

SDK quickstart

OpenAI-compatible

Python

from openai import OpenAI

client = OpenAI(
    api_key="sk-live-your-callai-key",
    base_url="https://api.callaiapi.com/v1"
)

response = client.chat.completions.create(
    model="lfm-3-1.7b",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant."},
        {"role": "user", "content": "Hello, explain quicksort with Python"}
    ],
    stream=True
)

for chunk in response:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="", flush=True)

Node.js / TypeScript

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: process.env.CALLAI_API_KEY,
  baseURL: 'https://api.callaiapi.com/v1',
});

const response = await openai.chat.completions.create({
  model: 'lfm-3-1.7b',
  messages: [{ role: 'user', content: 'Hello!' }],
  stream: true,
});

for await (const chunk of response) {
  process.stdout.write(chunk.choices[0]?.delta?.content || '');
}