Self-hosted LLM (Llama, Mistral) EC2/VPS pe deploy karein — data privacy aur zero API costs.
شروع از
PKR 120,000
We deploy open-weight LLMs on your AWS or VPS infrastructure with GPU sizing, quantization, and network exposure matched to your workload and privacy requirements. Inference runs inside your VPC or private server with TLS-terminated access, not on shared public API endpoints. We document when self-hosting is economical versus managed APIs so you do not over-provision hardware for sporadic traffic.
1. Workload & economics assessment
We model token throughput needs, compare GPU hourly cost against projected API spend, and flag when managed APIs remain cheaper.
2. Infrastructure provisioning
GPU instance launched in private subnet, base image hardened, NVIDIA drivers and container runtime verified.
3. Model serving setup
Weights pulled from approved registry, quantization applied to fit VRAM, server configured with concurrency and context limits.
4. Security hardening & benchmarking
Firewall rules, authentication, and load tests run. Results compared to acceptance targets before DNS or internal routing cutover.
| فیصلہ عنصر | یہ طریقہ | متبادل | نوٹس |
|---|---|---|---|
| GPU sizing accuracy | Throughput modeling from your real prompts before instance purchase | Largest GPU available without workload math | Oversized GPUs waste budget; undersized ones fail at peak concurrency. |
| Network exposure | Private subnet, TLS proxy, and authenticated inference API | Public IP on raw model port 8000 | Open model ports get scraped within hours and leak compute. |
| Quantization tuning | Quality benchmarks at multiple bit depths on your content types | Default quant preset from tutorial blog | Legal and medical summaries degrade sharply at aggressive quants without testing. |
| Operational readiness | Runbooks for patch, reboot, backup, and OOM recovery included | Install script only with no maintenance guide | Models run for weeks then fail on disk full or driver drift without ops docs. |
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