Phi-4 (14B)
Phi-4 (14B) by Microsoft (14B parameters). At Q4_K_M with an 8K context it needs about 10.4 GiB of memory. Microsoft's dense 14B, aimed at math and reasoning, mostly in English; its 16K context is short, but it fits a 12 GB card at 5-bit.
Last updated: 2026-10-13
Model facts
Run it
ollama run phi4:14b
Memory needed
Weights + KV cache + runtime overhead, in GiB. Lower quantization = less memory, slightly lower quality.
| Quantization | 4K context | 8K context | 32K context |
|---|---|---|---|
| Q4_K_M | 9.6 GiB | 10.4 GiB | 15.0 GiB |
| Q5_K_M | 11.0 GiB | 11.8 GiB | 16.5 GiB |
| Q6_K | 12.6 GiB | 13.3 GiB | 18.0 GiB |
| Q8_0 | 15.8 GiB | 16.6 GiB | 21.3 GiB |
| FP16 | 28.7 GiB | 29.4 GiB | 34.1 GiB |
Which hardware runs it
Best quantization that fits each device with a 8K context. Estimates, not benchmarks. See the methodology.
Frequently asked questions
How much VRAM does Phi-4 (14B) need?
With an 8K context, about 10.4 GiB at Q4_K_M and 16.6 GiB at Q8_0 (weights + KV cache + runtime overhead). Longer contexts need more memory for the KV cache.
Can Phi-4 (14B) run on an GeForce RTX 4090?
Yes. Phi-4 (14B) fits on the GeForce RTX 4090 (24 GB) at Q8_0 with an 8K context, using about 16.6 GiB, at an estimated 47 tokens/s.
Can I run Phi-4 (14B) on a Mac?
Yes. Phi-4 (14B) fits on the M3 Ultra (96 GB) at FP16 with an 8K context, using about 29.4 GiB, at an estimated 19 tokens/s.
Can Phi-4 (14B) be used commercially?
Phi-4 (14B) is released under MIT. The licence allows commercial use (read its conditions).