DeepSeekDeepSeek Coder V2 Lite 16B on NVIDIA GeForce RTX 4060 Ti 16GB
Yes — RTX 4060 Ti 16GB runs DeepSeek Coder V2 Lite 16B excellently at Q5_K_M — 50 tok/s. 16 GB VRAM with plenty of headroom.
Model Size
15.7B
Device VRAM
16 GB
Bandwidth
288 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for DeepSeek Coder V2 Lite 16B on NVIDIA GeForce RTX 4060 Ti 16GB at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 50 tok/s | 150ms | ✓ Yes | Excellent | estimated |
Notes
Q5_K_M
Fits well. Q5 quality at 10.9GB on 16GB. Fast inference thanks to MoE sparsity.
About DeepSeek Coder V2 Lite 16B
DeepSeek Coder V2 Lite 16B (15.7B) is a coding, ai coding, ai building model. Mixture-of-Experts architecture: 15.7B total, ~2.4B active per token. Fast and capable code generation and completion. Inference speed belies the total param count. One of the best coding models for its effective size.
View all DeepSeek Coder V2 Lite 16B 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.
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Estimate method: MoE model performance reports. Reference hardware source: github.com (2026-01-15)
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.