LocalLLaMA seeks uncensored Qwen2.5-Coder 7B

The blunt take is that uncensored is not a coding benchmark, and the smallest useful models usually win because they are code-tuned first. If you want a local assistant that actually ships patches, start with a strong code model and treat behavior tuning as a second pass.

• –Qwen2.5-Coder-7B-Instruct is the cleanest official baseline here: Apache 2.0, 128K context, and explicit code-generation, reasoning, and fixing focus.
• –Jan-Code-4B is the lightweight fallback the thread points to, especially if you want a fast local worker model rather than your primary coder.
• –Third-party uncensored fine-tunes exist, but they vary widely and are usually derivatives rather than first-party releases.
• –The thread mirrors the broader LocalLLaMA reality: small models can work well in one-shot or tool-assisted tasks, but fully autonomous coding still hits a ceiling quickly.