DeepSeekDeepSeek Coder V2 Lite 16B on NVIDIA GeForce RTX 4070 Ti 12GB
Yes — RTX 4070 Ti 12GB runs DeepSeek Coder V2 Lite 16B excellently at Q4_K_M — 55 tok/s. 12 GB VRAM with plenty of headroom.
Model Size
15.7B
Device VRAM
12 GB
Bandwidth
504 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for DeepSeek Coder V2 Lite 16B on NVIDIA GeForce RTX 4070 Ti 12GB at Q4_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | 55 tok/s | 140ms | ✓ Yes | Excellent | estimated |
Notes
Q4_K_M
Best coding model for 12GB. MoE efficiency + good quantization = fast experience.
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 4070 Ti 12GB
NVIDIA GeForce RTX 4070 Ti 12GB has 12 GB at 504 GB/s. Street price: $749.
See all models NVIDIA GeForce RTX 4070 Ti 12GB can run →Estimate method: MoE model. Q4_K_M 9.1GB fits with headroom. 504 GB/s bandwidth ideal. 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.