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Run LLM Locally

Qwen2.5 72B Instruct on the RTX PRO 6000 Blackwell

With 96 GB of VRAM, the RTX PRO 6000 Blackwell runs Qwen2.5 72B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 46.6 GB needed). At Q8_0 it fits entirely.

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Qwen2.5 72B Instruct

Q4_K_M · 8K context

Excellent

The model needs about 46.6 GB and fits in the 93.1 GB available, with 46.5 GB to spare.

Your hardware
RTX PRO 6000 Blackwell 96 GB · 64 GB RAM
Estimated memory
~46.6 GB estimate
VRAM (usable memory)
93.1 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
27–37 tok/s estimate
Largest context in fast memory
128K tokens
Confidence: low

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

Memory breakdown

~46.6 GB (45.3 GB–47.9 GB) needed · estimate

Fits entirely in VRAM · 46.5 GB left

  • Model weights41 GB
  • KV cache2.5 GB
  • Runtime overhead0.9 GB
  • Safety margin2.2 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

Other quantizations on the RTX PRO 6000 Blackwell

Qwen2.5 72B Instruct on RTX PRO 6000 Blackwell + 64 GB RAM · 8K context
Qwen2.5 72B Instruct Q8_08K~79.3 GB · 16–22 tok/s estimateCompatible
Qwen2.5 72B Instruct Q6_K8K~62.1 GB · 20–28 tok/s estimateExcellent
Qwen2.5 72B Instruct Q5_K_M8K~54.1 GB · 23–32 tok/s estimateExcellent
Qwen2.5 72B Instruct Q4_K_M8K~46.6 GB · 27–37 tok/s estimateExcellent
Qwen2.5 72B Instruct IQ4_XS8K~42.4 GB · 29–40 tok/s estimateExcellent
Qwen2.5 72B Instruct Q3_K_M8K~38.2 GB · 32–45 tok/s estimateExcellent

Alternatives

GPUs that run Qwen2.5 72B Instruct Q4_K_M entirely in VRAM

    Other models that fit the RTX PRO 6000 Blackwell

    Where to buy a RTX PRO 6000 Blackwell

    Prices and links follow the market you choose.

    RTX PRO 6000 Blackwell Workstation Edition

    96 GB GDDR7 ECC · 1,792 GB/s · 600 W

    ExcellentRuns Qwen2.5 72B Instruct Q4_K_M entirely in memory

    Price not available

    Availability unknown

    View on amazon.com

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    Frequently asked questions

    Can the RTX PRO 6000 Blackwell run Qwen2.5 72B Instruct?
    The model needs about 46.6 GB and fits in the 93.1 GB available, with 46.5 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. ~79.3 GB / 93.1 GB.
    What is the largest context on the RTX PRO 6000 Blackwell?
    At Q4_K_M, about 128K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
    How fast is Qwen2.5 72B Instruct (RTX PRO 6000 Blackwell)?
    We estimate 27–37 tok/s (estimate, confidence low). Based on: memory bandwidth (1,792 GB/s) and model size.