Capacity-priced AI infrastructure
Your AI bill should not rise
with every token.
Moonshotai
Deepseek Ai
Qwen
Zai Org
HauhauCS
Unsloth
Google
Empero AiMoonshotaiDeepseek AiQwenZai OrgHauhauCSUnslothGoogleEmpero AiMoonshotaiDeepseek AiQwenZai OrgHauhauCSUnslothGoogleEmpero AiMoonshotaiDeepseek AiQwenZai OrgHauhauCSUnslothGoogleEmpero AiDedicated capacity, billed by the second. Lock the rate when you launch — keep your OpenAI-compatible code.
Choose the cost boundary
Fixed cost or open meter. Slide and compare.
A Compute instance runs 20 days × 8 hours at a locked rate. The price stays the same whether you process 10 million or 500 million tokens. Token-priced providers charge for every token.
See Compute pricingMonthly tokens
50 M tokens / month
QDivZero — Qwen 3.6 35B
20 days × 8 h × 0.40 €/h
64 €
/ mo
GPT-5.4 Mini
4.14 €/M tokens / month
207 €
/ mo
GPT-5.6 Luna
5.52 €/M tokens / month
276 €
/ mo
Claude Sonnet 5
9.2 €/M tokens / month
460 €
/ mo
Gemini 2.5 Pro
13.8 €/M tokens / month
690 €
/ mo
Compute uses active-capacity pricing. Public Models remain token-priced.
Approximate monthly usage
Keep your integration. Control what you spend.
Point existing OpenAI-compatible code at QDivZero. Compute capacity is billed by the second at the rate locked when an instance launches, so your team can plan around the capacity it needs instead of watching a token meter climb.
See capacity pricingfrom openai import OpenAI
client = OpenAI(
base_url="https://api.qdiv0.com/v1",
api_key="your-api-key",
)
response = client.chat.completions.create(
model="your-model",
messages=[
{"role": "user", "content": "Hello world"},
],
)
Compute
Run compatible models through one OpenAI-compatible endpoint.
Run compatible Hugging Face models through an OpenAI-compatible endpoint. Active capacity is billed by the second at a rate locked when the instance launches.
Explore Compute
Flexible Vector Database
Reuse Compute embeddings for semantic search, discovery, and recommendations.
Reuse a Compute embeddings instance for semantic search, discovery, and recommendations instead of adding a separate embedding service.
Explore Flexible Vector Database
Firewall
Keep blocked requests away from the target model.
Attach guardrails to supported chat-completion requests and keep blocked requests away from the target model.
Explore Firewall
Smart Balancers
Route requests by configured intent and priority.
Route by configured intent and priority, with ordered failover between healthy destinations. Compute-backed routes retain capacity pricing; Public Model routes remain token-priced.
Explore Smart Balancers
Next step / 05
Make AI spend a decision, not a surprise.
Deploy compatible models on active capacity billed by the second at the rate set when you launch. Keep your OpenAI-compatible application and scale on a budget you can plan.