Your own AI — on your GPU, with your data
Deploy an LLM or a ready AI platform on a cloud GPU within an hour: a corporate chatbot, RAG over internal documents, AI features in your product. Data doesn't leave your server, and the bill is hourly and predictable.
Why your own AI when there's ChatGPT
Two motives no one argues with: data privacy and economics at scale.
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Privacy
Internal documents, client data, code, contracts — things you can't send to external APIs. A self-hosted LLM runs in an isolated perimeter: your GPU, your network, your Firewall. No "data may be used for training".
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Economics at scale
API billing grows with every request; your own GPU costs a fixed amount: from ≈$80.96/mo in workday mode (8×5) to ≈$331.20/mo round-the-clock (GPU from $0.46/hr). On a steady request flow this is many times cheaper than an API, and for uneven load — hourly billing: on for the day, off at night.
Ready images — AI in one click
Marketplace images bring up a working AI stack in minutes, with no fighting drivers.
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Dify Premium
A low-code platform for AI apps: visual workflows, RAG pipelines over your documents, an API for integrations, connecting any models. Effectively — a builder for a corporate AI assistant.
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Qwen3-VL-32B
A powerful open multimodal model: text + images, OCR, reasoning. Document recognition, image analysis, chatbot — with no per-model licensing fees.
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Ollama + open models
The simplest way to run Llama, DeepSeek or any open model: Ollama, DeepSeek and Llama images are already in the Marketplace — a GPU instance with ready inference in minutes.
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Planning something else?
vLLM (production inference), ComfyUI (image generation), Whisper (speech recognition) — deploy on a clean GPU instance; CUDA and drivers are pre-installed.
Which GPU for which model
A practical cheat sheet — the answer to the top query "what GPU do I need for an LLM".
| Task | Model (examples) | Recommended GPU | Price |
|---|---|---|---|
| Start: chatbot / RAG for a team | 7–8B (Llama 3.1 8B, Qwen 8B) | RTX PRO 4500 Blackwell (32 GB) | $0.69/hr · 8×5 ≈$121.44/mo |
| Assistant, document analysis | 30–70B quantized | A100 80 GB / RTX PRO 6000 Blackwell (96 GB) | from $1.30/hr |
| Multimodality (text + images) | Qwen3-VL-32B | A100 80 GB | $1.30/hr |
| Fine-tuning | LoRA / QLoRA on 7–70B | H100 | $2.40/hr |
| Large models without quantization | 70B+ fp16 (Llama 3.1 70B) | Multi-GPU: 2–4× A100 / H100 | custom |
| Image generation | SDXL, Flux | RTX PRO 4500 Blackwell / L40S | from $0.69/hr |
Not sure — start with a smaller GPU by the hour (from $0.46) and measure speed on your own task. That's cheaper than any consultation. Full price list of all cards — Cloud GPU
A typical corporate AI architecture
Everything in one private network (VPC), with only the interface exposed. The Firewall is free.
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Staff / your application
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Dify on a Cloud Instance — orchestration, RAG, access rights
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LLM on a GPU instance — Qwen / Llama, vLLM
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Object Storage (S3) — documents for RAG, model weights, datasets
Requests don't leave your infrastructure — this is the key difference from OpenAI, Google or Anthropic APIs.
Frequently asked questions
Get advice on the configurationYour AI assistant can work today
A Marketplace image + a GPU by the hour = a working prototype in an hour. Like it — scale up; no — switch it off, having paid for the hours of the test.
Latest publications
Everything you need to create a stable, secure and scalable environment
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