I will self host your llm privately on your own server or cloud


About this gig
I will self-host your LLM privately on your own server or cloud
Running your LLM through a third-party API means your prompts and data pass through someone else's servers. If you need data privacy, predictable costs, or an offline/air gapped model, self-hosting is the answer. I set it up end-to-end.
I deploy open-weight models (Llama, Mistral, Qwen, DeepSeek, or your fine-tuned model) on your own VPS, dedicated server, or cloud GPU instance (AWS, Vultr, RunPod, Lambda Labs), and expose them through a clean OpenAI-compatible API endpoint you can plug straight into your app.
What you get:
- Model serving via vLLM or Ollama (whichever fits your GPU/traffic)
- Dockerized, reproducible deployment not a fragile manual setup
- OpenAI-compatible API endpoint (drop-in replacement, minimal code changes)
- Basic auth / API key protection so it's not wide open
- Resource sizing guidance so you're not overpaying for GPU you don't
I've set up production infrastructure on AWS (ECS, EC2, IAM) and run GPU-mounted Kubernetes workloads before this isn't my first server.
Get to know Ammar Haider
AI Engineer and Automation Specialist I LangChain, RAG I React, Node, DevOps
- FromPakistan
- Member sinceMar 2020
- Avg. response time2 hours
- Last delivery6 months
Languages
English
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FAQ
Do I need my own GPU?
No — I can help you provision a cloud GPU instance if you don't have one (cost is separate from the gig price).
Can you fine-tunning the model?
That's a separate service — this gig covers deployment/hosting of an existing or open-weight model.
Is my data really private?
Yes — once deployed, all inference runs on your infrastructure; nothing is sent to a third-party API.
