Apertis for Research.
One API, Every Model.

from openai import OpenAI

client = OpenAI(
    api_key="your-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

# Compare 3 models in one script
for model in ["gpt-5-codex", "claude-sonnet-4-6", "gemini-3-pro"]:
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Explain quantum entanglement"}]
    )
    print(f"{model}: {response.choices[0].message.content[:100]}...")

import anthropic

client = anthropic.Anthropic(
    api_key="your-apertis-key",
    base_url="https://api.apertis.ai"
)

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain quantum entanglement"}
    ]
)

print(message.content[0].text)

import { createApertis } from '@apertis/ai-sdk-provider';
import { generateText } from 'ai';

const apertis = createApertis({
  apiKey: process.env.APERTIS_API_KEY,
});

const { text } = await generateText({
  model: apertis('claude-sonnet-4-6'),
  prompt: 'Explain quantum entanglement',
});

console.log(text);

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "your-apertis-key",
  baseURL: "https://api.apertis.ai/v1",
});

const models = ["gpt-5-codex", "claude-sonnet-4-6", "gemini-3-pro"];

for (const model of models) {
  const response = await client.chat.completions.create({
    model,
    messages: [{ role: "user", content: "Explain quantum entanglement" }],
  });
  console.log(`${model}: ${response.choices[0].message.content?.slice(0, 100)}...`);
}

curl https://api.apertis.ai/v1/chat/completions \
  -H "Authorization: Bearer your-apertis-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5-codex",
    "messages": [
      {"role": "user", "content": "Explain quantum entanglement"}
    ]
  }'