Open-weight local LLM

CodeLlama 34B

Massive coding model. Handles complex refactoring, architecture, and multi-file edits.

32 GB power user 32 GB RAM Q4_K_M Coding assistant
Parameters
34B
Minimum RAM
32 GB
Model size
20 GB
Quantization
Q4_K_M

Can CodeLlama 34B run locally?

CodeLlama 34B belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for codellama-34b-instruct in LM Studio or another GGUF-compatible runtime.

codepowerquality

Install path

01
Check RAM fitMinimum 32 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch codellama-34b-instruct in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Massive coding model. Handles complex refactoring, architecture, and multi-file edits.

Limitations

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

Best use cases

  • code
  • power
  • quality

Capability profile

speed
4
quality
7
coding
9
reasoning
7

Technical notes

Developer
codellama
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