📍 Part of the Local LLMs in 2026 guide
❌ No — not enough VRAM without CPU offloading
DeepSeek Coder V2 33B needs 19.5 GB VRAM at Q4. The RTX 4060 Ti 16GB has 16 GB.
DeepSeek Coder V2 33B needs 19.5 GB VRAM at Q4. The RTX 4060 Ti 16GB has 16 GB.
● DeepSeek Coder V2 33B (DeepSeek) is a 33B parameter model used for Code generation and analysis. Top-tier code model, competitive with GPT-4 for programming.
VRAM Requirements
| Quantization | VRAM Needed | RTX 4060 Ti 16GB |
|---|---|---|
| Q4_K_M (recommended) | 19.5 GB | ❌ |
| Q8_0 (high quality) | 34 GB | ❌ |
Why It Won’t Fit
DeepSeek Coder V2 33B needs 19.5 GB VRAM at Q4 quantization, but the RTX 4060 Ti 16GB only has 16 GB. You’re 3.5 GB short.
Options: You can run it with CPU offloading (expect ~16 tok/s — very slow), or upgrade to a GPU with 19.5+ GB VRAM.
About the RTX 4060 Ti 16GB
Pros: 16GB unlocks 14B models, efficient power draw, DLSS 3
Cons: Limited to 128-bit bus, not ideal for batch inference
Price: ~$450 — Check current price on Amazon →