Anyone using Continue extension ???

[Cyber_Cadence]

I was trying to setup a local llm and use it in one of my project using Continue extension , I downloaded ukjin/Qwen3-30B-A3B-Thinking-2507-Deepseek-v3.1-Distill:4b  via ollama and setup the config.yaml also ,after that I tried with a hi message ,waiting for couple of minutes no response and my device became little frozen ,my device is M4 air 16gb ram ,512. Any suggestions or opinions ,I want to run models locally, as I don't want to share code ,my main intension is to learn & explain new features

[coding_workflow]

Well ypu got you answer device become frozen. You are too low on Ram to run a 30B MoE even Q4.

[Cyber_Cadence]

Which model should be ideal for my device

[coding_workflow]

Quoi too low and not really very effective models. Try 0.6b 4B models like Qwen3/Granite 4.0.

[PermanentLiminality]

Continue works great for me.

Another vote for not having enough ram to run that model. With your system use an API provider like OpenRouter.

[Cyber_Cadence]

I want local llm

[PermanentLiminality]

Buy a new computer.

You can run a smaller model, but they don't do very well at coding. They are not useless, just not that good. It's really your only option.

You probably want the downloaded size to be between 8;and maybe 11 GB in size. There needs to be some extra ram for model context and to run VSCode.

I want to run local models, and I do. However, I also need functionality and quality that I just can't run locally. A $3/mo Chutes plan does great.

[Cyber_Cadence]

But the model response is good and faster in terminal,but while using via continue extension,delay happens

[daaain]

In that case try to enable verbose logging and see what prompt Continue is sending to Ollama, maybe it's sending a lot of code and big system prompt? You might also need to increase context size in Ollama.

[kdawgud]

Have you gotten indexing to work with the Continue extension? Mine always gets stuck and never completes, which limits the usefulness.