LocalClaw/LLM/DeepSeek Coder V2 (16B)
Open-weight local LLM

DeepSeek Coder V2 (16B)

MoE code model rivaling GPT4-Turbo on coding benchmarks. 1.1M downloads.

16 GB sweet spot 12 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
16B
Minimum RAM
12 GB
Model size
9.5 GB
Quantization
Q4_K_M

Can DeepSeek Coder V2 (16B) run locally?

DeepSeek Coder V2 (16B) is a practical pick for 16 GB machines, especially with Q4_K_M quantization.

Search for deepseek-coder-v2-lite-instruct in LM Studio or another GGUF-compatible runtime.

bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF
codepower

Install path

01
Check RAM fitMinimum 12 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch deepseek-coder-v2-lite-instruct in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • MoE code model rivaling GPT4-Turbo on coding benchmarks. 1.1M downloads.

Limitations

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

Best use cases

  • code
  • power

Capability profile

speed
6
quality
8
coding
9
reasoning
7

Technical notes

Developer
deepseek
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.

Starter desktopMac mini M4 16GBPortable fitMacBook Air M4 16GBBest 16GB models16GB RAM guide

Where to go next