DeepSeekDeepSeek Coder V2 Lite 16B on AMD Radeon RX 7900 XTX
Yes — AMD Radeon RX 7900 XTX handles DeepSeek Coder V2 Lite 16B well at Q5_K_M — 47 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
15.7B
Device VRAM
24 GB
Bandwidth
960 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for DeepSeek Coder V2 Lite 16B on AMD Radeon RX 7900 XTX 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 | 47 tok/s | 116ms | ✓ Yes | Good | estimated |
Notes
Q5_K_M
ROCm can run large models well on RDNA 3, though CUDA equivalents still have broader tooling support. Q5_K_M fits in VRAM on this card.
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 AMD Radeon RX 7900 XTX
AMD Radeon RX 7900 XTX has 24 GB at 960 GB/s. Street price: $849.
See all models AMD Radeon RX 7900 XTX can run →Builds with AMD Radeon RX 7900 XTX
Estimate method: Estimated from rtx-4090 compatibility patterns plus ROCm/Vulkan adjustments. Reference hardware source: github.com (2026-03-26)
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.