Sovereign AI Compute
for inference
Dedicated RTX 4090/5090 GPUs with easy hourly pricing.
Choose your region and use built-in privacy settings that are simple to explain to compliance.
Why teams switch from proprietary APIs
Proprietary AI APIs are convenient at first. Over time, token billing makes costs unpredictable, and infrastructure choices limit how much control you have over data residency and deployment.
Hivenet lets you run open-source models for inference on dedicated GPUs, with clear pricing and a region you can choose.
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Lower cost: Up to 70% cheaper than your current provider. Hourly GPU pricing (no token billing) and no separate charges for storage or data egress.
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Same quality: Smaller OSS models (Llama, Mistral, etc.) often match GPT-3.5/mini-tier performance.
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Sovereignty: Choose where your inference runs (France or UAE today). Keep prompts and outputs on your own infrastructure and out of US jurisdiction.
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Freedom: No contracts, no usage caps, no model lock-in.
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Partnership: We help you benchmark models on your real prompts, size GPUs correctly, and move your workloads when you’re ready.
A team spending €10,000/month on API calls can often cut that by half without sacrificing accuracy or latency.
Why open source is enough
For many production tasks—classification, chat, RAG, summarization—smaller OSS models match the reasoning power of mid-tier proprietary models.
You stop paying for capacity you don’t use. You keep every benefit of inference while gaining privacy and predictability.
What you get on day one
OpenAI-compatible endpoints
Point your client to a new URL. Minimal code changes. vLLM templates included.
Dedicated RTX 4090/5090
Modern GPUs sized for inference. No queueing behind strangers.
Transparent pricing
4090 at €0.20/hour. 5090 at €0.40/hour. No hidden fees.
Model right-sizing
We analyze your workload and latency targets, then recommend a model size and GPU setup to test first.
Bring-your-own-model
or pick from popular open-source families
How it works
Map your workload
We review your use case, prompt size, and latency targets.
Choose models
Start with proven open-source options sized to your needs.
Spin up Compute
Deploy on 4090 or 5090 GPUs with OpenAI-compatible endpoints.
Validate results
Measure quality, latency, and cost on your actual traffic.
Switch when ready
Run in parallel with your current API until you’re confident.
Who it’s for
Teams paying over €2k/month on OpenAI, Gemini, or Claude APIs
Companies with repetitive workloads or predictable demand
Developers running chat, extraction, or RAG pipelines
Organizations with strict data residency, privacy, or sovereign requirements
If you rely on exclusive proprietary features, start small. We’ll help you test open-source parity before you commit.
Pricing
RTX 5090
RTX 4090
Flat hourly rates. Clear invoices. Stop paying for mystery multipliers.
Welcome bonus: up to €250 on first purchase
Data sovereignty and control
Your prompts and outputs are not used for training
Ephemeral by default unless you opt in to retention
Region on request for teams with EU needs
We start small. If the proof hits your targets, we scale with you.
Common questions
Will open-source match the quality I have now?
Often, yes, for tasks that don’t need frontier reasoning. We test on your prompts so you can see it yourself.
How much code changes?
Usually a new endpoint URL and minor auth changes. The route is OpenAI-compatible via vLLM.
What about latency?
Latency depends on model size, context length, and batching. We size the setup to meet your target for your workload.
Do you support embeddings and RAG?
Yes. We provide templates and guidance for embeddings, retrieval steps, and context control.
Can I burst for spiky traffic?
We use instance-based scaling today. We’ll help you plan autoscaling with clear rules and warm capacity where needed.
Start with a proof of concept
Show us one costly workload. We’ll stand up an endpoint, benchmark open-source models, and give you side-by-side results—cost, latency, and accuracy. If it fits, expand. If it doesn’t, no harm done.
Compute with Hivenet is a distributed cloud built on everyday devices, not data centers. You keep control of cost, data, and pace.
