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Run LLM Locally

Qwen3.8 27B on the RX 7900 XTX

With 24 GB of VRAM, the RX 7900 XTX runs Qwen3.8 27B at Q4_K_M entirely on the GPU with an 8K context (about 18.2 GB needed). At Q8_0 it does not fit in VRAM.

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Qwen3.8 27B

Q4_K_M · 8K context

Excellent

The model needs about 18.2 GB and fits in the 23.3 GB available, with 5.1 GB to spare.

Your hardware
RX 7900 XTX 24 GB · 64 GB RAM
Estimated memory
~18.2 GB estimate
VRAM (usable memory)
23.3 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
32–47 tok/s estimate
Largest context in fast memory
85K tokens
Confidence: low

Based on: memory bandwidth (960 GB/s) and model size

Memory breakdown

~18.2 GB (17.5 GB–19 GB) needed · estimate

Fits entirely in VRAM · 5.1 GB left

  • Model weights15.7 GB
  • KV cache0.6 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

EstimateData updated 40 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 XTX

Qwen3.8 27B on RX 7900 XTX + 64 GB RAM · 8K context
Qwen3.8 27B Q8_08K~30.2 GB · 2.5–5 tok/s estimateCPU/GPU offload
Qwen3.8 27B Q6_K8K~23.7 GB · 14–26 tok/s estimateCPU/GPU offload
Qwen3.8 27B Q5_K_M8K~21.2 GB · 28–40 tok/s estimateCompatible
Qwen3.8 27B Q4_K_M8K~18.2 GB · 32–47 tok/s estimateExcellent
Qwen3.8 27B IQ4_XS8K~16.9 GB · 34–50 tok/s estimateExcellent
Qwen3.8 27B Q3_K_M8K~15.4 GB · 37–55 tok/s estimateExcellent

Alternatives

GPUs that run Qwen3.8 27B Q4_K_M entirely in VRAM

Other models that fit the RX 7900 XTX

Where to buy a RX 7900 XTX

Prices and links follow the market you choose.

Radeon RX 7900 XTX

24 GB GDDR6 · 960 GB/s · 355 W

ExcellentRuns Qwen3.8 27B Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RX 7900 XTX run Qwen3.8 27B?
The model needs about 18.2 GB and fits in the 23.3 GB available, with 5.1 GB to spare.
Which quantization should I use on the RX 7900 XTX?
Q5_K_M is the highest-precision quantization that fits entirely in VRAM at 8K context. ~21.2 GB / 23.3 GB.
What is the largest context on the RX 7900 XTX?
At Q4_K_M, about 85K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Qwen3.8 27B (RX 7900 XTX)?
We estimate 32–47 tok/s (estimate, confidence low). Based on: memory bandwidth (960 GB/s) and model size.