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Gemma 3 27B IT on the RX 7900 XT

With 20 GB of VRAM, the RX 7900 XT runs Gemma 3 27B IT at Q4_K_M entirely on the GPU with an 8K context (about 18.4 GB needed). At Q8_0 it does not fit in VRAM.

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Gemma 3 27B IT

Q4_K_M · 8K context

Compatible

The model needs about 18.4 GB and fits in the 19.4 GB available (1 GB left).

Your hardware
RX 7900 XT 20 GB · 64 GB RAM
Estimated memory
~18.4 GB estimate
VRAM (usable memory)
19.4 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
28–40 tok/s estimate
Largest context in fast memory
20K tokens
Confidence: low

Based on: memory bandwidth (800 GB/s) and model size

Memory breakdown

~18.4 GB (17.6 GB–19.2 GB) needed · estimate

Fits entirely in VRAM · 1 GB left

  • Model weights15.4 GB
  • KV cache1 GB
  • Runtime overhead1.1 GB
  • Safety margin0.9 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (ROCm) · 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 RX 7900 XT

Gemma 3 27B IT on RX 7900 XT + 64 GB RAM · 8K context
Gemma 3 27B IT Q8_08K~30.3 GB · 1.7–3.5 tok/s estimatePossible but slow
Gemma 3 27B IT Q6_K8K~23.9 GB · 4–7 tok/s estimateCPU/GPU offload
Gemma 3 27B IT Q5_K_M8K~21.1 GB · 8–15 tok/s estimateCPU/GPU offload
Gemma 3 27B IT Q4_K_M8K~18.4 GB · 28–40 tok/s estimateCompatible
Gemma 3 27B IT IQ4_XS8K~16.7 GB · 30–44 tok/s estimateCompatible
Gemma 3 27B IT Q3_K_M8K~15.4 GB · 32–48 tok/s estimateExcellent

Alternatives

GPUs that run Gemma 3 27B IT Q4_K_M entirely in VRAM

Other models that fit the RX 7900 XT

Where to buy a RX 7900 XT

Prices and links follow the market you choose.

Radeon RX 7900 XT

20 GB GDDR6 · 800 GB/s · 315 W

CompatibleRuns Gemma 3 27B IT Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RX 7900 XT run Gemma 3 27B IT?
The model needs about 18.4 GB and fits in the 19.4 GB available (1 GB left).
Which quantization should I use on the RX 7900 XT?
Q4_K_M is the highest-precision quantization that fits entirely in VRAM at 8K context. ~18.4 GB / 19.4 GB.
What is the largest context on the RX 7900 XT?
At Q4_K_M, about 20K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Gemma 3 27B IT (RX 7900 XT)?
We estimate 28–40 tok/s (estimate, confidence low). Based on: memory bandwidth (800 GB/s) and model size.