Open-weight local LLM

LLaVA-Phi3 (3.8B)

Small LLaVA on Phi 3. Vision understanding at ultra-compact size. 126K downloads.

Laptop ready 6 GB RAM Q5_K_M Vision tasks
Parameters
3.8B
Minimum RAM
6 GB
Model size
2.3 GB
Quantization
Q5_K_M

Can LLaVA-Phi3 (3.8B) run locally?

LLaVA-Phi3 (3.8B) is a good fit for normal laptops and compact desktops with 8 GB RAM or more.

Search for llava-phi-3-mini in LM Studio or another GGUF-compatible runtime.

visionlightspeed

Install path

01
Check RAM fitMinimum 6 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch llava-phi-3-mini in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Small LLaVA on Phi 3. Vision understanding at ultra-compact size. 126K downloads.

Limitations

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

Best use cases

  • vision
  • light
  • speed

Capability profile

speed
9
quality
5
coding
3
reasoning
5

Technical notes

Developer
llava
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.

Where to go next