
Compute with Hivenet
Self-serve GPU compute. Sovereign by architecture. Available in France, UAE, and USA.


Researchers, startups, studios, and enterprise teams run production workloads on this infrastructure. Not a sandbox.
Used by independent builders, researchers, students, creators, and teams testing ideas before they become larger deployments.

Train on 4090 and 5090 instances. Reusable environments. Per-second billing. Your training data stays on your infrastructure.

Blender, video encoding, upscaling. Dedicated GPU instances. Not queued. Not shared.

Simulations and notebooks. On-demand. No minimum commitment.

Run local models at 737 tokens/s (RTX 4090) or 45.4ms TTFT (RTX 5090). Private. No third-party API calls.

Deploy an OpenAI-compatible inference endpoint without building the serving layer yourself.
Ubuntu, PyTorch, and Jupyter Notebook. Pre-configured. Start in under 60 seconds.
Save your setup. Reuse it.
Bring your setup. Same tools. European infrastructure. Lower cost.
1 × - 8 ×
VRAM 32 - 256 GB
RAM 73 - 584 GB
CPU 8 - 64
Disk space 250 - 2000 GB
Bandwidth 1000 Mb/s
1 × - 8 ×
VRAM 24 - 192 GB
RAM 48 - 384 GB
CPU 8 - 64
Disk space 250 - 2000 GB
Bandwidth 125 - 1000 Mb/s
2 × - 32 ×
RAM 4 - 64 GB
Disk space 50 - 800 GB
Bandwidth 250 - 1000 Mb/s
No sales call required. Credit card is all you need.
No legal pathway for foreign government data requests.
77% greener than centralized cloud.
No offsets.

If you need regional deployment, private AI, procurement support, or a larger rollout, explore Compute for business.