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Run LLM Locally

Gemma 3 12B IT on the RTX PRO 6000 Blackwell

With 96 GB of VRAM, the RTX PRO 6000 Blackwell runs Gemma 3 12B IT at Q4_K_M entirely on the GPU with an 8K context (about 9.1 GB needed). At Q8_0 it fits entirely.

Gemma 3 12B IT

Q4_K_M · 8K context

Excellent

The model needs about 9.1 GB and fits in the 93.1 GB available, with 84.1 GB to spare.

Your hardware
RTX PRO 6000 Blackwell 96 GB · 64 GB RAM
Estimated memory
~9.1 GB estimate
VRAM (usable memory)
93.1 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
118–188 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

~9.1 GB (8.5 GB–9.6 GB) needed · estimate

Fits entirely in VRAM · 84.1 GB left

  • Model weights6.8 GB
  • KV cache0.8 GB
  • Runtime overhead1 GB
  • Safety margin0.4 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · flash attention on · weights = real file size · sliding-window layers keep 1,024 tokens

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

Gemma 3 12B IT on RTX PRO 6000 Blackwell + 64 GB RAM · 8K context
Gemma 3 12B IT Q8_08K~14.1 GB · 82–121 tok/s estimateExcellent
Gemma 3 12B IT Q6_K8K~11.4 GB · 98–150 tok/s estimateExcellent
Gemma 3 12B IT Q5_K_M8K~10.2 GB · 108–167 tok/s estimateExcellent
Gemma 3 12B IT Q4_K_M8K~9.1 GB · 118–188 tok/s estimateExcellent
Gemma 3 12B IT IQ4_XS8K~8.3 GB · 126–204 tok/s estimateExcellent
Gemma 3 12B IT Q3_K_M8K~7.8 GB · 133–217 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 Gemma 3 12B IT 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 Gemma 3 12B IT?
The model needs about 9.1 GB and fits in the 93.1 GB available, with 84.1 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. ~14.1 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 Gemma 3 12B IT (RTX PRO 6000 Blackwell)?
We estimate 118–188 tok/s (estimate, confidence low). Based on: memory bandwidth (1,792 GB/s) and model size.