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Run LLM Locally

Qwen3 30B-A3B on the RTX PRO 6000 Blackwell

With 96 GB of VRAM, the RTX PRO 6000 Blackwell runs Qwen3 30B-A3B at Q4_K_M entirely on the GPU with an 8K context (about 19.7 GB needed). At Q8_0 it fits entirely.

Qwen3 30B-A3B

Q4_K_M · 8K context

Excellent

The model needs about 19.7 GB and fits in the 93.1 GB available, with 73.4 GB to spare.

Your hardware
RTX PRO 6000 Blackwell 96 GB · 64 GB RAM
Estimated memory
~19.7 GB estimate
VRAM (usable memory)
93.1 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
156–284 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

~19.7 GB (19.1 GB–20.5 GB) needed · estimate

Fits entirely in VRAM · 73.4 GB left

  • Model weights17.3 GB
  • KV cache0.8 GB
  • Runtime overhead0.8 GB
  • Safety margin0.9 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

Qwen3 30B-A3B on RTX PRO 6000 Blackwell + 64 GB RAM · 8K context
Qwen3 30B-A3B Q8_08K~33.4 GB · 130–221 tok/s estimateExcellent
Qwen3 30B-A3B Q6_K8K~26.1 GB · 142–250 tok/s estimateExcellent
Qwen3 30B-A3B Q5_K_M8K~22.8 GB · 149–266 tok/s estimateExcellent
Qwen3 30B-A3B Q4_K_M8K~19.7 GB · 156–284 tok/s estimateExcellent
Qwen3 30B-A3B IQ4_XS8K~17.7 GB · 161–296 tok/s estimateExcellent
Qwen3 30B-A3B Q3_K_M8K~15.4 GB · 167–312 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 Qwen3 30B-A3B 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 Qwen3 30B-A3B?
The model needs about 19.7 GB and fits in the 93.1 GB available, with 73.4 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. ~33.4 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 Qwen3 30B-A3B (RTX PRO 6000 Blackwell)?
We estimate 156–284 tok/s (estimate, confidence low). Based on: memory bandwidth (1,792 GB/s) and model size.