Can the RTX 6000D run Mistral-7B-Instruct-v0.2?
Yes. Mistral-7B-Instruct-v0.2 fits the RTX 6000D's 84 GB at Q4_K_M (about 5.8 GB needed), running at an estimated 225 tok/s. There's room for up to FP16 if you want higher quality.
Every quantization
Mistral-7B-Instruct-v0.2 (7.2B) on 84 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 4 GB | 5.8 GB | Fits easily | ~225 tok/s |
| Q5_K_M | 5 GB | 6.8 GB | Fits easily | ~180 tok/s |
| Q8_0 | 8 GB | 9.8 GB | Fits easily | ~113 tok/s |
| FP16 | 14 GB | 15.8 GB | Fits easily | ~64 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 TheBloke/Mistral-7B-Instruct-v0.2-GGUF -ngl 99Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Mistral-7B-Instruct-v0.2 details →
Compare
Same model, other hardware - and other models on this card
Mistral-7B-Instruct-v0.2 on other hardware
- RTX 5090~257 tok/s
- RTX 5090 D~257 tok/s
- RTX 4090~156 tok/s
- Radeon RX 7900 XTX~138 tok/s
- RTX 5080~138 tok/s
- RTX 3090~137 tok/s
- RTX 3080 Ti~131 tok/s
- RTX 5080 Mobile~129 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 Mistral-7B-Instruct-v0.2?
Yes. Mistral-7B-Instruct-v0.2 fits the RTX 6000D's 84 GB at Q4_K_M (about 5.8 GB needed), running at an estimated 225 tok/s. There's room for up to FP16 if you want higher quality.
How much VRAM does Mistral-7B-Instruct-v0.2 need?
About 4 GB of weights at Q4_K_M, 8 GB at Q8_0 and 14 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is Mistral-7B-Instruct-v0.2 on the RTX 6000D?
Roughly 225 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.