What GPU do I need to run microsoft/Phi-4-mini-reasoning?
3.8B parameters, published in BF16. View on Hugging Face
Phi-4-mini-reasoning is published by microsoft on Hugging Face, with 94,407 downloads and 240 likes to date. It's a Phi3ForCausalLM model built for text-generation, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 caveat: requires a quantized checkpoint actually published for this model — check its Hugging Face page before relying on this row.
Cheapest way to run Phi-4-mini-reasoning at its published (BF16) precision: 1× RTX 3060 on simplepod, at $0.070/hr per GPU ($0.070/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More microsoft models
- Florence-2-base (232M, F16)
- phi-2 (2.8B, F16)
- Phi-3.5-vision-instruct (4.1B, BF16)
- Phi-3.5-mini-instruct (3.8B, BF16)
- VibeVoice-ASR (8.7B, BF16)
- phi-4 (14.7B, BF16)
