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Phi-4 14B: RAM and VRAM requirements

Phi-4 14B needs about 10.8 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~9.05 GB to download; KV cache and overhead add the rest), or about 17.3 GB at Q8_0. The lightest hardware that runs it is Nvidia GeForce RTX 3060 (12GB).

phi family · 14B params · released Dec 2024 · 7.3M Ollama pulls · LMArena Elo 1256.

Shopping for hardware? See what runs Phi-4 14B →

License MIT · Commercial OK ↓ 664.4K/mo ♥ 2.3K on HuggingFace
Q4_K_M GGUF
9.05 GB
Q8_0 GGUF
15.58 GB
Memory @ Q4 (4k)
~10.8 GB
Context
16 k

Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.

Will it run on your device?

Phi-4 14B runs on 24 of 40 tracked devices at Q4_K_M.

17 run well 7 tight fit 16 too small
Fit check Q4_K_M
No, not enough memory
needs 10.8 GB usable 10.5 GB
See the full breakdown

Memory breakdown

Weights (Q4_K_M)9.05 GB
+
KV cache (4k)0.9 GB
+
Overhead0.8 GB
=
Total10.8 GB

How context length changes it

4k context ~10.8 GB 32k context ~17.1 GB 128k context ~38.6 GB

Longer context grows the KV cache quickly: Phi-4 14B needs ~10.8 GB at 4k but ~38.6 GB at 128k, which can push it past a device that fits it at a short context.

Speed drops too: every token re-reads the KV cache, so at 128k context Phi-4 14B generates at roughly ~24% of its short-context speed. How this is estimated.

Benchmark scores

BFCL · tool use

#10 of 19 ranked · Overall Acc on the Berkeley Function-Calling Leaderboard.

28.8%

LMArena · chat (elo)

#11 of 16 ranked · Human-preference Elo from LMArena's blind head-to-head votes.

1256

Sourced third-party benchmarks for the full-precision Phi-4 14B, not a specific quant. See the full leaderboard.

Quantization sizes

GGUF quantson disk
Quantization Size on disk
Q2_K 5.9 GB est
Q3_K_M 6.8 GB est
Q4_K_M (default) 9.05 GB
Q5_K_M 10 GB est
Q6_K 11.5 GB est
Q8_0 15.58 GB
FP16 28 GB est

Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.

Run it

Ollama
$ ollama run phi4:14b
llama.cpp
$ llama-cli -hf bartowski/phi-4-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/phi-4-GGUF

Which devices can run Phi-4 14B?

Apple Silicon Macs

RAM-only laptops

iPhone & iPad

Android

NVIDIA GPUs

AMD GPUs

Same job, different size

Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.

Next size down Mistral Nemo 12B 12.2B Next size up DeepSeek-V2-Lite 16B

Similar models

Head-to-head

FAQ

How much VRAM or RAM does Phi-4 14B need?

At Q4_K_M, Phi-4 14B needs about 10.8 GB (weights ~9.05 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~17.3 GB.

What is the Q4_K_M GGUF file size of Phi-4 14B?

The Q4_K_M GGUF file is about 9.05 GB to download, and the Q8_0 GGUF is about 15.58 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~10.8 GB of memory at Q4_K_M.

Can Phi-4 14B run on a laptop?

Phi-4 14B is large; you need a 24 GB+ GPU or a 32-48 GB Mac at Q4_K_M.

Can I use Phi-4 14B commercially?

Yes. Phi-4 14B is licensed MIT, which permits commercial use.

Understand the numbers

Short guides to the ideas behind Phi-4 14B's memory and quant figures.

Released December 12, 2024 by Microsoft. Strong math and reasoning. Default context 16K. Ollama shows 9.1GB; bartowski HF gives precise 9.05GB Q4_K_M and 15.58GB Q8_0.

Sources

Last validated 2026-08-03. Memory figures are estimates. See methodology.