LocalClaw/LLM/Phi-4 Mini (3.8B)
Open-weight local LLM

Phi-4 Mini (3.8B)

Microsoft's latest small miracle. Punches way above its weight in reasoning & code.

Laptop ready 4 GB RAM Q5_K_M Quick coding help
Run with LocalClaw Compare all models
Parameters
3.8B
Minimum RAM
4 GB
Model size
2.5 GB
Quantization
Q5_K_M

Can Phi-4 Mini (3.8B) run locally?

Phi-4 Mini (3.8B) is a good fit for normal laptops and compact desktops with 8 GB RAM or more.

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

lmstudio-community/Phi-4-mini-instruct-GGUF
chatcodelightspeed

Install path

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

Strengths

  • MIT license
  • Punches way above weight class
  • 128K context at 3.8B
  • Great at reasoning & code for its size

Limitations

  • English-only
  • Limited factual knowledge
  • Can hallucinate

Best use cases

  • Quick coding help
  • Reasoning on-the-go
  • Edge deployment
  • Education

Capability profile

speed
9
quality
6
coding
7
reasoning
6

Technical notes

Developer
Microsoft Research
License
MIT
Context window
131,072 tokens
Architecture
Transformer decoder-only, 128K context

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.

Entry laptop fitMacBook Air 8GBMore headroomMac mini M4 16GBAll compatible picks8GB RAM guide

Similar models to compare

Qwen 3 (4B) 4BGemma 3 (4B) 4BLlama 3.2 (3B) 3B

Where to go next