Open-weight local LLM

DeepCoder (14B)

O3-mini level open coder. Strong reasoning + coding combo. 326K downloads.

16 GB sweet spot 12 GB RAM Q4_K_M Coding assistant
Parameters
14B
Minimum RAM
12 GB
Model size
8.5 GB
Quantization
Q4_K_M

Can DeepCoder (14B) run locally?

DeepCoder (14B) is a practical pick for 16 GB machines, especially with Q4_K_M quantization.

Search for deepcoder-14b-preview in LM Studio or another GGUF-compatible runtime.

codereasoningpower

Install path

01
Check RAM fitMinimum 12 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch deepcoder-14b-preview in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • O3-mini level open coder. Strong reasoning + coding combo. 326K downloads.

Limitations

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

Best use cases

  • code
  • reasoning
  • power

Capability profile

speed
6
quality
8
coding
9
reasoning
8

Technical notes

Developer
deepcoder
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