DeepSeekDeepSeek Coder V2 Lite 16B on NVIDIA RTX PRO 6000 Blackwell
Yes — RTX PRO 6000 Blackwell handles DeepSeek Coder V2 Lite 16B well at Q8_0 — 63 tok/s. Solid daily-driver performance on 96 GB VRAM.
Model Size
15.7B
Device VRAM
96 GB
Bandwidth
1800 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for DeepSeek Coder V2 Lite 16B on NVIDIA RTX PRO 6000 Blackwell at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 63 tok/s | 120ms | ✓ Yes | Good | estimated |
Notes
Q8_0
96 GB GDDR7 fits Q8_0 (16.9 GB) with 79 GB headroom. 1.8 TB/s bandwidth. Near-FP16 quality — minimal quantization loss.
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 RTX PRO 6000 Blackwell
NVIDIA RTX PRO 6000 Blackwell has 96 GB at 1800 GB/s. Street price: $7,500.
See all models NVIDIA RTX PRO 6000 Blackwell can run →Estimate method: Estimated from bandwidth ratio vs RTX 4090 (1800/1008 = 1.78x) with conservative margin. Reference hardware source: nvidia.com (2026-03-29)
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.