01
Pick a model
Choose any Hugging Face model. The control plane validates VRAM requirements and prepares the runtime. No manual GPU configuration.
Run any model without per-token billing.
The Compute engine abstracts GPU selection, provider routing, and runtime configuration behind one API. Pick a model, deploy, and start serving at predictable hourly rates.
From model to API in three steps.
02
Compute deploys it
The scheduler selects the optimal capacity across available providers. Runtime, networking, and scaling are provisioned automatically.
03
Call the endpoint
Your model is exposed as an OpenAI-compatible endpoint. Use the Python SDK or any HTTP client. Same API, any model.
Capacity pricing. No token meters.
Pay a fixed hourly rate for each model. Scale up when you need more capacity. Stop when you don't. Your invoice is the sum of active compute hours.
Example workload
Qwen 3.6 35B A3B MTP
8 h/day · 20 days/month
Similar capacity to GPT-5.4-mini for general and agentic tasks.
Estimated monthly40 €/month
Calculated at 8 hours/day, 20 working days/month. Actual costs depend on your usage pattern and can be lower with scheduled start/stop rules.
Example workload
Qwen3-VL-Embedding-2B
8 h/day · 20 days/month
Multimodal embedding model. Generate embeddings from text and images at predictable cost.
Estimated monthly16 €/month
Calculated at 8 hours/day, 20 working days/month. Actual costs depend on your usage pattern and can be lower with scheduled start/stop rules.
Example workload
DeepSeek V4 Flash
8 h/day · 20 days/month
Similar capacity to Grok 4.3 High for reasoning and instruction-following workloads.
Estimated monthly178 €/month
Calculated at 8 hours/day, 20 working days/month. Actual costs depend on your usage pattern and can be lower with scheduled start/stop rules.
Example workload
Kimi K2.6
8 h/day · 20 days/month
Similar capacity to Opus 4.7 for complex, long-context enterprise workloads.
Estimated monthly2.080 €/month
Calculated at 8 hours/day, 20 working days/month. Actual costs depend on your usage pattern and can be lower with scheduled start/stop rules.
External provider estimates
Token-priced equivalents.
Estimated per user at 15M input + 10M output tokens/month. Output is usually the expensive side.
Claude 3.7 Sonnet
200k context
$195.00
USD / user / month
GPT-5.4 mini
OpenAI fast tier
$56.25
USD / user / month
GPT-5.5
OpenAI standard tier
$375.00
USD / user / month
Opus 4.7
Anthropic reasoning tier
$975.00
USD / user / month
QDivZero stays the same price as you add users; only compute capacity is limited.
Performance comparisons sourced from Artificial Analysis. Prices are indicative and depend on actual resource allocation.
Security? First, please.
Regional controls, verified capacity, and private-by-default operations for production AI workloads. Add Firewall when policy must sit in the request path.
Regions
Trusted regions
European deployments for GDPR-sensitive workloads, with the option to disable unverified servers.
Runtime
Verified runtime
QDivZero Agent, mTLS-authenticated traffic, and GPU security module checks before capacity is accepted.
Privacy
Private by default
We do not store conversation logs.
Start when work starts. Stop when it doesn't.
Create cron rules to turn instances on before traffic and off after hours. Lower the invoice, cut idle energy use, and keep operations predictable.
Lower the invoice
Pay only while compute is actually running.
Reduce idle energy use
Avoid overnight and weekend GPUs consuming power without work.
Keep capacity ready
Bring instances up before users, jobs, or office hours begin.
Time-based start and stop rules for this instance.
Action
Start
Timezone
UTC
Cron expression
0 9 * * 1-5
Action
Stop
Timezone
UTC
Cron expression
0 19 * * 1-5
What Compute already includes.
Deployment, routing, pricing, security, scheduling, and API compatibility in one runtime.
Model deployment
Pick a model and let Compute validate runtime requirements and prepare capacity for serving.
Multi-provider routing
The scheduler selects capacity across available providers for cost, availability, and latency.
OpenAI-compatible API
Expose deployed models behind the standard OpenAI contract so existing clients keep working.
Scheduled operations
Use cron-based start and stop rules so workloads run when needed and stay off when they do not.
Capacity pricing
Pay for compute hours instead of tokens, with pricing that stays predictable as usage grows.
Security controls
Apply regional controls, verified runtime checks, and private-by-default operations for production workloads.
OpenAI SDK. Your models. Our infrastructure.
Point existing OpenAI-compatible code at QDivZero and run production AI workloads on capacity-priced infrastructure.
View docsquickstart.py
from 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"}
],
)Deploy your first model in minutes.
Compute abstracts infrastructure decisions so you can focus on your product. Start with a model, add products as your workload grows.