How much VRAM does Phi-4 14B need?

At Q4_K_M with 8K context: 9.0GB weights + 1.7GB KV cache + 1.5GB runtime overhead = 12.2GB total. RTX 4090 offers 24.0GB usable VRAM, so the verdict is: Comfortable.

What is the best quantization for Phi-4 14B on RTX 4090?

Q8_0 — the highest tier that still fits within 24.0GB usable VRAM at 8K context. Lower tiers (Q3/Q2) fit too but cost noticeable quality.

How fast does Phi-4 14B run on RTX 4090?

About 48 tokens/s at Q8_0 (theoretical estimate, ±30% in real-world use).

Can RTX 4090 run Phi-4 14B?

✅ Comfortable

Phi-4 14B @ Q4_K_M · 8K context

Needed

12.2 GB

Usable

24.0 GB

VRAM breakdown

Weights (Q4_K_M)	9.0 GB
KV cache (8K context)	1.7 GB
Runtime overhead	1.5 GB
Total	12.2 GB

Computed at 8K context with fp16 KV cache. Longer contexts need more VRAM — use the VRAM calculator for other settings.

Recommended quantization

Q8_0

Estimated generation speed

~48 tok/s @ Q8_0

Theoretical estimates based on published architecture data and measured GGUF sizes; real-world speed varies ±30%.

Cheaper GPUs that run it

Smaller models this GPU runs well

FAQ

How much VRAM does Phi-4 14B need?: At Q4_K_M with 8K context: 9.0GB weights + 1.7GB KV cache + 1.5GB runtime overhead = 12.2GB total. RTX 4090 offers 24.0GB usable VRAM, so the verdict is: Comfortable.
What is the best quantization for Phi-4 14B on RTX 4090?: Q8_0 — the highest tier that still fits within 24.0GB usable VRAM at 8K context. Lower tiers (Q3/Q2) fit too but cost noticeable quality.
How fast does Phi-4 14B run on RTX 4090?: About 48 tokens/s at Q8_0 (theoretical estimate, ±30% in real-world use).

Check another combination in the GPU Checker →

Data verified 2026-08-04