Can the RTX 6000D run Gemma 4 31B?
Yes. Gemma 4 31B fits the RTX 6000D's 84 GB at Q4_K_M (about 20.8 GB needed), running at an estimated 47 tok/s. There's room for up to FP16 if you want higher quality.
Every quantization
Gemma 4 31B (32.7B) on 84 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 19 GB | 20.8 GB | Fits easily | ~47 tok/s |
| Q5_K_M | 23 GB | 24.8 GB | Fits easily | ~39 tok/s |
| Q8_0 | 35 GB | 36.8 GB | Fits easily | ~26 tok/s |
| FP16 | 65 GB | 66.8 GB | Fits | ~14 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.
Run it
Copy, paste, go
llama-server -hf google/gemma-4-31B-it-qat-q4_0-gguf -ngl 99Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Gemma 4 31B details →
Compare
Same model, other hardware - and other models on this card
Gemma 4 31B on other hardware
- RTX 5090~54 tok/s
- RTX 5090 D~54 tok/s
- RTX 4090~33 tok/s
- RTX 3090~29 tok/s
- Radeon RX 7900 XTX~29 tok/s
- MacBook Pro 16" M4 Max~16 tok/s
- Arc Pro B60~14 tok/s
- DGX Spark (GB10)~8.3 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
- Qwen3 32B~47 tok/s
- GLM-4.7-Flash~347 tok/s
- Qwen3-30B-A3B-Instruct-2507~339 tok/s
Frequently asked
Quick answers
Can the RTX 6000D run Gemma 4 31B?
Yes. Gemma 4 31B fits the RTX 6000D's 84 GB at Q4_K_M (about 20.8 GB needed), running at an estimated 47 tok/s. There's room for up to FP16 if you want higher quality.
How much VRAM does Gemma 4 31B need?
About 19 GB of weights at Q4_K_M, 35 GB at Q8_0 and 65 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is Gemma 4 31B on the RTX 6000D?
Roughly 47 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.