The World's First Composite Intelligence.
Our intelligence system outperforms every AI model that has EVER existed at coding, mathematics, and agentic work.
Ask Anything.
One Intelligence. A Whole System Inside It.
Quancis comes from quán, the Chinese word for the whole. Not a fragment. Not a committee of parts pretending to be one thing. The whole. The entire system, working as a single intelligence. It's how a company works: hundreds of people, hundreds of tools, and the world only sees one name on the door. That's Quancis. You see one. Behind it, everything.
That principle is why Kael, the model inside Quancis, is the best in the world. A great company isn't one genius doing everything alone. It's many specialists pointed at the same goal. Kael works the same way. Not a bigger model, but a smarter system: many intelligences working as one. Using Kael, we built Quan Harness, a full coding agent, and Quan Chat, an agentic assistant, in a single month. Both rival, and in places surpass, what the top AI companies spent years building. Quancis is the system. Kael is the model. Together, they are the best intelligence in the world.
One System. The Best The World Has Ever Built.
No contact-sales tier. No compromises. Just the most capable intelligence system in the world, at a price that makes the decision obvious.
The world's most advanced intelligence, behind an API surface you already know.
- Input
- $3.00 per 1M tokens
- Cached input
- $0.60 per 1M tokens · up to 80% off
- Output
- $10.00 per 1M tokens
For the hardest problems, Kael Pro Beta goes further. It costs $8.00 in and $25.00 out per 1M tokens.
- Input
- Text + images
- Output
- Text
- Context
- 1M tokens
- Max response
- 128k tokens
Swap The Base URL.
No custom SDK. No migration. If you already speak OpenAI, you already speak Quancis.
https://api.quancis.space/v1import openai
# Quancis is 100% drop-in compatible with the OpenAI SDK.
client = openai.OpenAI(
api_key="sk-quan-...",
base_url="https://api.quancis.space/v1",
)
response = client.chat.completions.create(
model="kael-beta",
messages=[
{"role": "system", "content": "You are a helpful coding assistant."},
{"role": "user", "content": "Refactor our distributed cache..."},
],
)
print(response.choices[0].message.content)