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Qwen2.5 72B Instruct on the RX 7900 XTX

Qwen2.5 72B Instruct at Q4_K_M needs about 46.6 GB, more than the 24 GB of the RX 7900 XTX: part of the model runs from system RAM, which slows generation. At Q3_K_M it does not fit in VRAM.

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Qwen2.5 72B Instruct

Q4_K_M · 8K context

Not recommended

The model needs about 46.6 GB but only 23.3 GB of VRAM is usable: 23.3 GB must be loaded into system RAM. It runs, 50% on the GPU, but more slowly.

Estimated speed is at most 1.6 tokens/s: too slow to be usable for chat.

Your hardware
RX 7900 XTX 24 GB · 64 GB RAM
Estimated memory
~46.6 GB estimate
VRAM (usable memory)
23.3 GB
GPU only
No
CPU/GPU offload
Required (23.3 GB)
Generation speed
0.8–1.6 tok/s estimate
Largest context in fast memory
None
Confidence: low

Based on: memory bandwidth (960 GB/s) and model size · system RAM bandwidth (~51 GB/s)

Memory breakdown

~46.6 GB (45.4 GB–47.9 GB) needed · estimate

23.3 GB must be offloaded to system RAM

  • Model weights41 GB
  • KV cache2.5 GB
  • Runtime overhead0.9 GB
  • Safety margin2.2 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (ROCm) · 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
  • split CPU/GPU runs vary a lot with the CPU and PCIe link
  • system RAM speed unknown (dual-channel DDR4-3200 assumed)

Other quantizations on the RX 7900 XTX

Qwen2.5 72B Instruct on RX 7900 XTX + 64 GB RAM · 8K context
Qwen2.5 72B Instruct Q8_08K~79.4 GB · No dataIncompatible
Qwen2.5 72B Instruct Q6_K8K~62.1 GB · 0.5–1 tok/s estimateNot recommended
Qwen2.5 72B Instruct Q5_K_M8K~54.1 GB · 0.6–1.2 tok/s estimateNot recommended
Qwen2.5 72B Instruct Q4_K_M8K~46.6 GB · 0.8–1.6 tok/s estimateNot recommended
Qwen2.5 72B Instruct IQ4_XS8K~42.4 GB · 1–2 tok/s estimatePossible but slow
Qwen2.5 72B Instruct Q3_K_M8K~38.3 GB · 1.3–2.5 tok/s estimatePossible but slow

Alternatives

GPUs that run Qwen2.5 72B Instruct Q4_K_M entirely in VRAM

Other models that fit the RX 7900 XTX

Hardware that runs Qwen2.5 72B Instruct Q4_K_M entirely in memory

Prices and links follow the market you choose.

Radeon PRO W7900

AMD

CompatibleRuns Qwen2.5 72B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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Affiliate link

AMD Ryzen AI Max+ 395

Unified memory PC

CompatibleRuns Qwen2.5 72B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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GeForce RTX 5090

Lowest memory tier

ExcellentRuns Qwen2.5 72B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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No current offer imported for this market: the link opens a marketplace search.

Frequently asked questions

Can the RX 7900 XTX run Qwen2.5 72B Instruct?
The model needs about 46.6 GB but only 23.3 GB of VRAM is usable: 23.3 GB must be loaded into system RAM. It runs, 50% on the GPU, but more slowly. Estimated speed is at most 1.6 tokens/s: too slow to be usable for chat.
Which quantization should I use on the RX 7900 XTX?
None fits entirely in VRAM at 8K context; the smallest, Q3_K_M, still needs offload.
What is the largest context on the RX 7900 XTX?
At Q4_K_M, the model does not fit entirely in VRAM even at a short context.
How fast is Qwen2.5 72B Instruct (RX 7900 XTX)?
We estimate 0.8–1.6 tok/s (estimate, confidence low). Based on: memory bandwidth (960 GB/s) and model size, system RAM bandwidth (~51 GB/s).