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Run LLM Locally

Mixtral 8x7B Instruct on the RTX PRO 6000 Blackwell

With 96 GB of VRAM, the RTX PRO 6000 Blackwell runs Mixtral 8x7B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 27.5 GB needed). At Q8_0 it fits entirely.

Mixtral 8x7B Instruct

Q4_K_M · 8K context

Excellent

The model needs about 27.5 GB and fits in the 93.1 GB available, with 65.6 GB to spare.

Your hardware
RTX PRO 6000 Blackwell 96 GB · 64 GB RAM
Estimated memory
~27.5 GB estimate
VRAM (usable memory)
93.1 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
103–154 tok/s estimate
Largest context in fast memory
32K tokens
Confidence: low

Based on: memory bandwidth (1,792 GB/s) and model size

Memory breakdown

~27.5 GB (26.8 GB–28.3 GB) needed · estimate

Fits entirely in VRAM · 65.6 GB left

  • Model weights24.6 GB
  • KV cache1 GB
  • Runtime overhead0.6 GB
  • Safety margin1.3 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · flash attention on · weights = real file size

EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card

What makes this estimate less reliable

  • no benchmark for this hardware and model yet
  • mixture-of-experts: speed depends on expert routing

Other quantizations on the RTX PRO 6000 Blackwell

Mixtral 8x7B Instruct on RTX PRO 6000 Blackwell + 64 GB RAM · 8K context
Mixtral 8x7B Instruct Q8_08K~50.2 GB · 66–93 tok/s estimateExcellent
Mixtral 8x7B Instruct Q6_K8K~39.2 GB · 80–115 tok/s estimateExcellent
Mixtral 8x7B Instruct Q5_K_M8K~33.2 GB · 90–132 tok/s estimateExcellent
Mixtral 8x7B Instruct Q4_K_M8K~27.5 GB · 103–154 tok/s estimateExcellent
Mixtral 8x7B Instruct IQ4_XS8K~27.1 GB · 104–156 tok/s estimateExcellent
Mixtral 8x7B Instruct Q3_K_M8K~21.6 GB · 122–186 tok/s estimateExcellent

Alternatives

Where to buy a RTX PRO 6000 Blackwell

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RTX PRO 6000 Blackwell Workstation Edition

96 GB GDDR7 ECC · 1,792 GB/s · 600 W

ExcellentRuns Mixtral 8x7B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RTX PRO 6000 Blackwell run Mixtral 8x7B Instruct?
The model needs about 27.5 GB and fits in the 93.1 GB available, with 65.6 GB to spare.
Which quantization should I use on the RTX PRO 6000 Blackwell?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~50.2 GB / 93.1 GB.
What is the largest context on the RTX PRO 6000 Blackwell?
At Q4_K_M, about 32K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Mixtral 8x7B Instruct (RTX PRO 6000 Blackwell)?
We estimate 103–154 tok/s (estimate, confidence low). Based on: memory bandwidth (1,792 GB/s) and model size.