Coding
Build a local coding assistant.
Code models are selected on fill-in-the-middle support, repository-scale context and latency rather than general chat quality. Coding mode biases the catalogue toward those properties and configures the project for editor integration.
- You want completion and review without sending source to a vendor
- Your codebase uses internal patterns a general model has never seen
- Latency matters more than the last few points of benchmark score
- General-purpose assistants — a chat model will serve you better
Local coding AI
A completion and review model quantized to sit permanently in VRAM alongside your editor, with your source never leaving the machine.
Qwen2.5 7B Instruct
7.6B · 32k · Apache 2.0
The default starting point for local work on 8–12 GB cards. Strong instruction following and reliable tool-call formatting for its size.
Qwen2.5 14B Instruct
14.8B · 32k · Apache 2.0
The sweet spot for 24 GB cards. Meaningfully stronger reasoning than 7B while still fine-tunable locally with QLoRA.
Qwen2.5 32B Instruct
32.8B · 32k · Apache 2.0
Approaches 70B quality at half the memory. Runs on a single 24 GB card at Q4_K_M with a modest context window.
Qwen2.5 72B Instruct
72.7B · 32k · Qwen License
Frontier-adjacent open weights. Needs a workstation, a multi-GPU rig or a large unified-memory Mac.
Qwen2.5 Coder 7B Instruct
7.6B · 32k · Apache 2.0
The practical local copilot. Supports fill-in-the-middle, so it works as an inline completion model rather than only a chat assistant.
Qwen2.5 Coder 32B Instruct
32.8B · 32k · Apache 2.0
The strongest open code model that still fits one 24 GB card. The reason a lot of people buy a 4090.