Open-weight local LLM
Qwen 3 Coder (30B)
Qwen flagship coding model. Designed for agentic coding with 256K context. Outperforms Claude 3.5 Sonnet on SWE-bench. Apache 2.0.
32 GB power user
24 GB RAM
Q4_K_M
Agentic coding (autonomous code generation)
Parameters
30B
Minimum RAM
24 GB
Model size
18 GB
Quantization
Q4_K_M
Can Qwen 3 Coder (30B) run locally?
Qwen 3 Coder (30B) belongs on 32 GB machines when you want stronger quality without jumping to server hardware.
Search for qwen3-coder-30b in LM Studio or another GGUF-compatible runtime.
Qwen/Qwen3-Coder-30B-GGUFcodepowerquality
Install path
01
Check RAM fitMinimum 24 GB RAM. Start with the Q4_K_M quant.02
Load the modelSearch qwen3-coder-30b in LM Studio.03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.Strengths
- Outperforms Claude 3.5 Sonnet on SWE-bench
- 256K context — handles entire codebases
- Designed for agentic coding (multi-step, autonomous)
- Apache 2.0
- Excellent at refactoring and multi-file edits
Limitations
- 24GB+ RAM required
- Focused on code — less versatile for general chat
- Can be verbose in explanations
Best use cases
- Agentic coding (autonomous code generation)
- Full codebase refactoring
- Multi-file code review
- CI/CD automation
- Code completion and debugging
Capability profile
Technical notes
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.