Microsoft
Can the Radeon AI Pro R9700 run Phi-4 14B?
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Yes. Phi-4 14B is a 9.1 GB download (Q4_K_M). The Radeon AI Pro R9700 gives the GPU 32 GB, leaving about 22.9 GB for context and runtime (our arithmetic).
Does it fit?
| Phi-4 14B memory | 9.1 GB at Q4_K_M (Ollama: phi4 tags) |
|---|---|
| Radeon AI Pro R9700 GPU memory | 32 GB of VRAM (product listing). |
| Left over | About 22.9 GB (our arithmetic) |
| Verdict | Fits 4 GB or more to spare (our estimate bands) |
Recommended quantization and context
Use the Q4_K_M build that Ollama's tag downloads; the memory figure above is for that build. The model supports up to 16K of context, but longer context uses more memory. Ollama starts at a 4096-token context by default (Ollama FAQ).
With about 22.9 GB spare you have room to raise the context. Raise it in steps and re-check with ollama ps.
Run it
ollama run phi4:14bThen check it's on the GPU:
ollama psThe PROCESSOR column should read 100% GPU. Driver setup for AMD cards on Windows, Linux and macOS, plus common fixes, is in the install and run section.
Where to buy the Radeon AI Pro R9700
ASUS Turbo Radeon AI Pro R9700 32GB
$1,999.99 Newegg · checked Oct 27, 2026, about 12:35 PM CT
Out of stock / unavailable
OUT OF STOCK when checked (search page)
Check price at Newegg (opens in a new tab)FAQ
Can the Radeon AI Pro R9700 run Phi-4 14B?
Yes: Phi-4 14B needs 9.1 GB (Q4_K_M, Ollama library) and the Radeon AI Pro R9700 gives the GPU 32 GB, leaving about 22.9 GB. That leaves room to raise the context above the 4096-token default. The fit bands are our estimate.
How much VRAM does Phi-4 14B need?
9.1 GB for the Q4_K_M build in the Ollama library, plus roughly 1–4 GB for context and runtime (our estimate). See the 12 GB page for other models that fit.
What command runs Phi-4 14B?
ollama run phi4:14b. Then run "ollama ps" and check the PROCESSOR column reads 100% GPU.
How fast is Phi-4 14B on the Radeon AI Pro R9700?
We don't list a speed because we have no sourced measurement for this pairing. Speed depends on memory bandwidth, quantization and context length.