DeepSeekDeepSeek V3 on NVIDIA GeForce RTX 4060 Ti 16GB
RTX 4060 Ti 16GB cannot run DeepSeek V3. 16 GB VRAM is insufficient at any quantization level.
Model Size
671B
Device VRAM
16 GB
Bandwidth
288 GB/s
Quantization
Q2_K
Performance by Quantization
OwnRig currently has one published compatibility entry for DeepSeek V3 on NVIDIA GeForce RTX 4060 Ti 16GB at Q2_K. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q2_K | – | – | ✗ Offload | Not viable | estimated |
Notes
Q2_K
671B MoE model requires 115GB+ at Q2_K. 16GB insufficient. Would need 128GB+ unified memory.
About DeepSeek V3
DeepSeek V3 (671B) is a chat, coding, ai coding, reasoning, multi-purpose model. Massive MoE model rivaling GPT-4 class. Only ~37B parameters active per token despite 671B total. Requires multi-GPU or very large unified memory (128GB+ Apple Silicon at Q2/Q3). Not for casual home use. Included for completeness and to show what the high end looks like.
View all DeepSeek V3 hardware options →About NVIDIA GeForce RTX 4060 Ti 16GB
NVIDIA GeForce RTX 4060 Ti 16GB has 16 GB at 288 GB/s. Street price: $449.
See all models NVIDIA GeForce RTX 4060 Ti 16GB can run →Builds with NVIDIA GeForce RTX 4060 Ti 16GB
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Estimate method: Performance estimates based on model size and device bandwidth. Reference hardware source: github.com (2026-03-15)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.