Can I Run Phi-4 Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?

Written by Jakub Rusinowski · Last updated January 6, 2025

Yes — comfortably

Yes, comfortably — Phi-4 (14B) at Q8_0 needs about 17.4 GB of the 128 GB usable on Framework Desktop (Ryzen AI Max+ 395, 128 GB), leaving ~110.6 GB spare and running at ~11.9 tok/s (estimated), with room for about 16,384 tokens of context.

Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~11.9 tok/s

Framework Desktop (Ryzen AI Max+ 395, 128 GB) — what it gives a model

Usable memory for models128 GB
Memory bandwidth256 GB/s
Form factorMini PC
Operating systemWindows or Linux
Memory upgradeableNo — soldered

Phi-4 Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB): memory by quantization

QuantMemory neededFits 128 GB?Max contextEst. speedDownload
F1630.5 GB✓ Yes16K~6.6 tok/s28 GB
Q8_017.4 GB✓ Yes16K~11.9 tok/s14.9 GB
Q6_K14 GB✓ Yes16K~15.1 tok/s11.5 GB
Q5_K_M12.4 GB✓ Yes16K~17.2 tok/s9.9 GB
Q4_K_M10.9 GB✓ Yes16K~19.7 tok/s8.5 GB
Q3_K_M8.4 GB✓ Yes16K~26.5 tok/s6 GB
Q2_K7.1 GB✓ Yes16K~32.7 tok/s4.6 GB

What to watch out for

Framework Desktop 128 GB limitations

Recommended setup

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

How these numbers are calculated

FAQ

Can I run Phi-4 Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?

Yes, comfortably — Phi-4 (14B) at Q8_0 needs about 17.4 GB of the 128 GB usable on Framework Desktop (Ryzen AI Max+ 395, 128 GB), leaving ~110.6 GB spare and running at ~11.9 tok/s (estimated), with room for about 16,384 tokens of context.

Which quantization of Phi-4 Family should I use on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?

Q8_0 — it needs about 17.4 GB of the 128 GB available, downloads as roughly 14.9 GB, and runs at an estimated 11.9 tokens/sec with up to 16K of context.

What limits Phi-4 Family on Framework Desktop (Ryzen AI Max+ 395, 128 GB)?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Which runtime should I use?

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

Other Computers

Other Models on Framework Desktop (Ryzen AI Max+ 395, 128 GB)

Phi-4 Family on GPUs

What This Model Is Good At

Model & Tools

← Can I Run It? | Phi-4 Family model page | Check your hardware