LocalClaw/LLM/Phi-3.5 MoE Instruct
Open-weight MoE

Phi-3.5 MoE Instruct

Microsoft Phi-3.5 MoE: compact mixture-of-experts model with only ~6.6B active parameters. Strong reasoning and coding for local power users. MIT licensed.

32 GB power user 32 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
42B (6.6B active, MoE)
Minimum RAM
32 GB
Model size
24 GB
Quantization
Q4_K_M

Can Phi-3.5 MoE Instruct run locally?

Phi-3.5 MoE Instruct belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for phi-3.5-moe-instruct in LM Studio or another GGUF-compatible runtime.

microsoft/Phi-3.5-MoE-instruct
chatcodereasoningpowermoe

Install path

01
Check RAM fitMinimum 32 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch phi-3.5-moe-instruct in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Microsoft Phi-3.5 MoE: compact mixture-of-experts model with only ~6.6B active parameters. Strong reasoning and coding for local power users. MIT licensed.

Limitations

  • Performance depends on quantization, RAM bandwidth and runtime support.

Best use cases

  • chat
  • code
  • reasoning
  • power
  • moe

Capability profile

speed
6
quality
8
coding
8
reasoning
8

Technical notes

Developer
phi
License
See model repository
Context window
Unknown tokens
Architecture
See model card

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.

Comfortable headroomMac mini M4 Pro 48GBMobile workstationMacBook Pro M4 Max 36GBPower-user picks32GB RAM guide

Where to go next