For Stable Diffusion and local AI at home, graphics memory (VRAM) matters more than anything else: 8GB runs basic image generation, 12–16GB is comfortable for SDXL-class models and small language models, and 24GB or more is needed for larger models. An NVIDIA card is still the easiest choice because most AI tools are built around CUDA.
By the TechCure India build team · Prices checked 27 September 2026 from our live in-stock catalogue, inclusive of GST. Prices change often — the product page always shows today's price.
VRAM guide
| VRAM | What runs comfortably |
|---|---|
| 8GB | Stable Diffusion 1.5, basic SDXL with memory-saving settings, 7–8B chat models in 4-bit |
| 12GB | SDXL, many LoRA workflows, 7–8B models with longer context |
| 16GB | SDXL and newer image models with fewer compromises, 13–14B models in 4-bit |
| 24GB+ | Larger image models, 30B-class models in 4-bit, fine-tuning small models |
These are practical rules of thumb; exact needs depend on the model, resolution and settings.
16GB graphics cards in stock
| Graphics card | VRAM | Price |
|---|---|---|
| Sapphire Pure RX 9060 XT OC 16GB GDDR6 | 16GB | ₹58,119 |
| Gigabyte RTX 5060 Ti Windforce Max OC 16GB GDDR7 | 16GB | ₹89,229 |
| GALAX GeForce RTX 5070 Ti 1-Click OC 16GB GDDR7 | 16GB | ₹1,41,769 |
NVIDIA or AMD for AI?
- NVIDIA: works with almost every AI tool out of the box — the safe choice for beginners.
- AMD: more VRAM per rupee (the RX 9060 XT 16GB is the cheapest 16GB card here), and support is improving, but some tools need extra setup.
The rest of the PC
- RAM: 32GB system RAM; 64GB for larger language models.
- Storage: 1–2TB NVMe — models take tens of gigabytes each.
- PSU: sized for the graphics card with headroom — see our PSU guide.
Our recommendation
For beginners, an RTX 5060 Ti 16GB is the easiest start; for serious local LLM work, plan 24GB or more. See the AI and Stable Diffusion PC guide, our AI PCs and deep learning workstations, such as the TechCure PC for eSports Gaming – Intel Core Ultra 5 245KF,.
Products in this guide
Sapphire Pure RX 9060 XT OC 16GB GDDR6View product →
Gigabyte RTX 5060 Ti Windforce Max OC 16GB GDDR7View product →
GALAX GeForce RTX 5070 Ti 1-Click OC 16GB GDDR7 PCIe 5.0View product →
TechCure PC for eSports Gaming – Intel Core Ultra 5 245KF,View product →
Frequently asked questions
How much VRAM do I need for Stable Diffusion?
8GB for basic use, 12–16GB for SDXL-class models without heavy compromises.
Can I run ChatGPT-like models at home?
Yes, smaller open models. A 7–8B model in 4-bit runs on 8GB VRAM; 13–14B models are comfortable on 16GB.
NVIDIA or AMD for AI?
NVIDIA is easier because most AI tools use CUDA. AMD offers more VRAM per rupee but can need extra setup.
Is 16GB VRAM enough in 2026?
For image generation and small-to-mid language models, yes. For larger models, choose 24GB or more.
Do I need a lot of system RAM?
32GB is a good start; 64GB helps with larger models and datasets.
Need a quote? Send your budget and use on WhatsApp +91 96907 96307 — the TechCure India build team replies with an itemised GST estimate, usually within minutes.