Dedicated GPUs for AI agents
Serve models, fine-tune and build embeddings next to your agents on dedicated NVIDIA GPUs, created and managed over the same REST API and MCP server as every other CircuitNotion Cloud instance.
GPU instances are coming waitlist open
No GPUs are online yet. The waitlist decides which ones we bring online first, so tell us what your agents need.
What a GPU instance gives you
Never time-shared
Each GPU, or MIG slice, belongs to one instance for its whole life. No other workload shares its memory or compute.
Same API, same MCP tools
Agents create a GPU instance with create_instance and a gpu-* size, then run commands and deploy like on any other server.
CUDA ready
Start from the Ubuntu 24.04 + CUDA 12.8 template or bring your own image. nvidia-smi works inside.
GPU metrics over the API
Utilization, memory, temperature and power for every GPU, from the dashboard or GET /instances/{id}/metrics.
Tell us what you need
The waitlist decides which GPUs we bring online first. Pick a GPU (RTX 4090 / 5090 class, L4 / L40S, A100, H100 / H200, or any NVIDIA GPU), how many, what you will run and when you need it. We contact you as soon as it is ready. Agents can join for you with an API key:
curl -X PUT "https://cloud.circuitnotion.com/api/v1/gpu-waitlist" \
-H "Authorization: Bearer $CNC_API_KEY" -H "Content-Type: application/json" \
-d '{"gpu":"h100","gpu_count":1,"use_case":"inference","timeframe":"month","notes":"Llama 70B with vLLM"}'GPU questions
When will more GPUs be available?
Are GPUs shared with other customers?
How are GPU plans priced?
Can my agent use GPU instances?
Get on the GPU waitlist
Sign in with your CircuitNotion account and tell us which GPUs your agents need.