Startup MVPs need the cheapest realistic AI backend that survives the first 100-500 users. The RTX 5060 Ti 16GB on our dedicated GPU hosting is the sweet spot.
Contents
Why This Card
- Fits Llama 3 8B, Mistral 7B, Qwen 2.5 14B (AWQ) – the 3 models most MVPs use
- 180 W, cheap UK dedicated hosting
- Full root, no per-token billing surprises
- Native FP8 – no performance penalty for modern quantised models
Recommended Stack
Backend: vLLM (Llama 3 8B FP8) on port 8000
Embedding: TEI (BGE-base) on port 8080
RAG DB: Qdrant or Postgres + pgvector
App: FastAPI or Next.js on your own containerAll on the same box – no network hops, no per-request cost. See full RAG install guide.
Capacity on One Card
| Metric | Capacity |
|---|---|
| Active chat users (p95 SLA) | ~16 |
| MAU at 10% active | ~160 |
| Document chunks embedded/day | ~800M |
| SDXL images/day | ~22k |
| Whisper transcription hours/day | ~1,320 audio-hours |
Cost vs API
- OpenAI API: GPT-4o-mini at ~$0.15 / M input, $0.60 / M output. For 200 users doing 1M tokens each per month: ~$150/month minimum
- Dedicated GPU: flat monthly fee, unlimited tokens, same card handles image gen and embedding on top
- Break-even is usually around 100-200 MAU depending on usage intensity – see break-even calculator
When to Scale Up
- > 160 MAU: add a second 5060 Ti or move to RTX 5090
- Need 30B+ models: RTX 6000 Pro 96GB
- Heavy image+LLM mix: split onto two cards
- Need 128k context regularly: upgrade for more VRAM
For most MVPs, one 5060 Ti takes you from zero to product-market-fit without infrastructure work.
Startup MVP Hosting
One Blackwell 16GB card, all your AI needs. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: first AI server, SaaS RAG, break-even vs API, concurrent users, vs OpenAI.
