LocalClaw/LLM/Phi-4 (14B)
Open-weight local LLM

Phi-4 (14B)

Microsoft's full Phi-4. Compact powerhouse with exceptional reasoning and coding for its size. MIT licensed.

16 GB sweet spot 16 GB RAM Q5_K_M Coding assistance
Run with LocalClaw Compare all models
Parameters
14B
Minimum RAM
16 GB
Model size
9 GB
Quantization
Q5_K_M

Can Phi-4 (14B) run locally?

Phi-4 (14B) is a practical pick for 16 GB machines, especially with Q5_K_M quantization.

Search for phi-4-instruct in LM Studio or another GGUF-compatible runtime.

lmstudio-community/Phi-4-Instruct-GGUF
chatcodepowerreasoning

Install path

01
Check RAM fitMinimum 16 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch phi-4-instruct in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Exceptional reasoning for 14B
  • MIT license
  • Strong coding
  • State-of-the-art at its size

Limitations

  • 16K context only
  • English-only
  • Smaller than Phi-4 Mini context

Best use cases

  • Coding assistance
  • Math and reasoning
  • Research
  • Technical writing

Capability profile

speed
7
quality
8
coding
9
reasoning
8

Technical notes

Developer
Microsoft Research
License
MIT
Context window
16,384 tokens
Architecture
Transformer decoder-only

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Starter desktopMac mini M4 16GBPortable fitMacBook Air M4 16GBBest 16GB models16GB RAM guide

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Where to go next