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Run LLM Locally

Gemma 2 9B IT on the Radeon PRO W7900

With 48 GB of VRAM, the Radeon PRO W7900 runs Gemma 2 9B IT at Q4_K_M entirely on the GPU with an 8K context (about 8.8 GB needed). At Q8_0 it fits entirely.

Gemma 2 9B IT

Q4_K_M · 8K context

Excellent

The model needs about 8.8 GB and fits in the 46.6 GB available, with 37.8 GB to spare.

Your hardware
Radeon PRO W7900 48 GB · 64 GB RAM
Estimated memory
~8.8 GB estimate
VRAM (usable memory)
46.6 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
65–100 tok/s estimate
Largest context in fast memory
8K tokens
Confidence: low

Based on: memory bandwidth (864 GB/s) and model size

Memory breakdown

~8.8 GB (8.2 GB–9.4 GB) needed · estimate

Fits entirely in VRAM · 37.8 GB left

  • Model weights5.4 GB
  • KV cache2 GB
  • Runtime overhead1 GB
  • Safety margin0.4 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (ROCm) · flash attention on · weights = real file size · sliding-window layers keep 4,096 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 Radeon PRO W7900

Gemma 2 9B IT on Radeon PRO W7900 + 64 GB RAM · 8K context
Gemma 2 9B IT Q8_08K~12.8 GB · 46–67 tok/s estimateExcellent
Gemma 2 9B IT Q6_K8K~10.6 GB · 55–81 tok/s estimateExcellent
Gemma 2 9B IT Q5_K_M8K~9.7 GB · 60–90 tok/s estimateExcellent
Gemma 2 9B IT Q4_K_M8K~8.8 GB · 65–100 tok/s estimateExcellent
Gemma 2 9B IT IQ4_XS8K~8.2 GB · 69–107 tok/s estimateExcellent
Gemma 2 9B IT Q3_K_M8K~7.8 GB · 73–114 tok/s estimateExcellent

Alternatives

Where to buy a Radeon PRO W7900

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Radeon PRO W7900

48 GB GDDR6 ECC · 864 GB/s · 295 W

ExcellentRuns Gemma 2 9B IT Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the Radeon PRO W7900 run Gemma 2 9B IT?
The model needs about 8.8 GB and fits in the 46.6 GB available, with 37.8 GB to spare.
Which quantization should I use on the Radeon PRO W7900?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~12.8 GB / 46.6 GB.
What is the largest context on the Radeon PRO W7900?
At Q4_K_M, about 8K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Gemma 2 9B IT (Radeon PRO W7900)?
We estimate 65–100 tok/s (estimate, confidence low). Based on: memory bandwidth (864 GB/s) and model size.