🖥️ Need a PC built for Local AI? Affordable Laptop Services builds high-VRAM AI workstations for running LLaMA, Mistral, Stable Diffusion, and other models offline in Singapore.
📋 Table of Contents
Why Running AI Locally Is So Hardware-Intensive
Running large language models like LLaMA 3, Mistral, or Mixtral locally — or image generation models like Stable Diffusion — is one of the most demanding tasks a consumer PC can face. Every token generated and every image rendered happens on your machine, in real time.
⚠️ Key Insight: Local AI performance is almost entirely determined by GPU VRAM. If the model is too large, it spills into system RAM — which is 10–50× slower for inference.
PC Requirements by Model Size
🔴 ENTRY (7B models)
- Windows 11 64-bit
- Any modern CPU
- 32 GB RAM
- 8 GB VRAM (RTX 3060/4060)
- 500 GB NVMe SSD
Runs LLaMA 3 8B, Mistral 7B smoothly
🟡 MID (13B–34B)
- Windows 11 64-bit
- AMD Ryzen 7 / Intel i7
- 64 GB RAM
- 16–24 GB VRAM (RTX 4080/4090)
- 1 TB NVMe SSD
Runs LLaMA 3 70B quantised, CodeLlama 34B
🟢 HIGH-END (70B+)
- Windows 11 64-bit
- AMD Ryzen 9 / Threadripper
- 128 GB RAM
- 24–48 GB VRAM (dual GPU)
- 2 TB NVMe SSD
Runs 70B unquantised, multi-user inference
VRAM: The Single Most Important Spec
| Model | Quantisation | VRAM Needed | GPU |
|---|---|---|---|
| LLaMA 3 8B | Q4 | 6 GB | RTX 3060 12GB |
| Mistral 7B | Q4 | 5 GB | RTX 3060 12GB |
| LLaMA 3 70B | Q4 | 40 GB | Dual RTX 4090 or RTX 6000 |
| Stable Diffusion XL | FP16 | 8–10 GB | RTX 3070 / 4070 |
| FLUX.1 | FP8 | 12–16 GB | RTX 4080 / 4090 |
🚫 Critical Warning: If your model doesn’t fit in VRAM, inference speed drops from 30–50 tokens/sec to 1–3 tokens/sec. Always buy more VRAM than the minimum.
System RAM: When VRAM Isn’t Enough
| Use Case | RAM Needed |
|---|---|
| 7B model, fits in VRAM fully | 32 GB |
| 13B–34B model with partial CPU offload | 64 GB |
| 70B model, heavy CPU offload | 128 GB |
| Multi-user / API server | 128 GB+ |
CPU: Loading, Tokenising, and Offloading
🏆 BEST VALUE
AMD Ryzen 9 7900X
Fast model loading, handles CPU offload layers well
⚡ HEAVY OFFLOAD
AMD Ryzen 9 7950X
16 cores — best for heavy CPU offload on large models
🏭 ENTERPRISE
AMD Threadripper Pro
For multi-user inference servers and 128 GB+ RAM configs
Storage: Model Files Are Huge
- Minimum: 1 TB NVMe SSD
- Recommended: 2 TB NVMe SSD (model library + working space)
- Heavy users: 4 TB NVMe or secondary SSD for model archives
Build Your Local AI Workstation
🤖 Custom Local AI PC — Built in Singapore
High-VRAM RTX 40 series, 64–128 GB RAM, fast NVMe. Built to run LLaMA, Stable Diffusion, and custom models offline — no cloud subscription, full privacy.
📍 Bugis, Singapore | Free consultation, no obligation
Also read: Stable Diffusion PC Requirements | Blender GPU Rendering Guide | Premiere Pro PC Requirements
Glossary: What is Local AI / LLM? | Professional Software Glossary
