Can the RTX 6000D run Qwen3.8 27B?
Yes. Qwen3.8 27B fits the RTX 6000D's 84 GB at Q4_K_M (about 17.8 GB needed), running at an estimated 56 tok/s. There's room for up to FP16 if you want higher quality.
Every quantization
Qwen3.8 27B (27.8B) on 84 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 16 GB | 17.8 GB | Fits easily | ~56 tok/s |
| Q5_K_M | 20 GB | 21.8 GB | Fits easily | ~45 tok/s |
| Q8_0 | 30 GB | 31.8 GB | Fits easily | ~30 tok/s |
| FP16 | 56 GB | 57.8 GB | Fits | ~16 tok/s |
Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 6000D's 1570 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.
Compare
Same model, other hardware - and other models on this card
Qwen3.8 27B on other hardware
- RTX 5090~64 tok/s
- RTX 5090 D~64 tok/s
- RTX 4090~39 tok/s
- RTX 3090~34 tok/s
- Radeon RX 7900 XTX~34 tok/s
- MacBook Pro 16" M4 Max~20 tok/s
- Arc Pro B60~16 tok/s
- DGX Spark (GB10)~9.8 tok/s
Also runs on the RTX 6000D
- Qwen2.5 72B~23 tok/s
- Llama 3.3 70B~23 tok/s
- Qwen3.6 35B A3B~343 tok/s
- Qwen3.5 35B A3B~343 tok/s
- dolphin-2.9.1-yi-1.5-34b~45 tok/s
- Gemma 4 31B~47 tok/s
- Qwen3 32B~47 tok/s
- GLM-4.7-Flash~347 tok/s
Frequently asked
Quick answers
Can the RTX 6000D run Qwen3.8 27B?
Yes. Qwen3.8 27B fits the RTX 6000D's 84 GB at Q4_K_M (about 17.8 GB needed), running at an estimated 56 tok/s. There's room for up to FP16 if you want higher quality.
How much VRAM does Qwen3.8 27B need?
About 16 GB of weights at Q4_K_M, 30 GB at Q8_0 and 56 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is Qwen3.8 27B on the RTX 6000D?
Roughly 56 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 6000D's 1570 GB/s memory bandwidth.