Posted by threeturn 4 days ago
Ask HN: Who uses open LLMs and coding assistants locally? Share setup and laptop
Which model(s) are you running (e.g., Ollama, LM Studio, or others) and which open-source coding assistant/integration (for example, a VS Code plugin) you’re using?
What laptop hardware do you have (CPU, GPU/NPU, memory, whether discrete GPU or integrated, OS) and how it performs for your workflow?
What kinds of tasks you use it for (code completion, refactoring, debugging, code review) and how reliable it is (what works well / where it falls short).
I'm conducting my own investigation, which I will be happy to share as well when over.
Thanks! Andrea.
Also are there good solutions for searching through a local collection of documents?
There's also google, which gives you 100 requests a day or something.
Here's the search.py I use
    import os
    import json
    from req import get
    # https://programmablesearchengine.google.com/controlpanel/create
    GOOGLE_SEARCH_API_KEY = os.getenv('GOOGLE_SEARCH_API_KEY')
    GOOGLE_SEARCH_API_ID = os.getenv('GOOGLE_SEARCH_API_ID')
    url = "https://customsearch.googleapis.com/customsearch/v1"
    def search(query):
        data = {
            "q": query,
            "cx": GOOGLE_SEARCH_API_ID,
            "key": GOOGLE_SEARCH_API_KEY,
        }
        results_json = get(url, data)
        results = json.loads(results_json)
        results = results["items"]
        return results
    if __name__ == "__main__":
        while True:
            query = input('query: ')
            results = search(query)
            print(results)
and the ddg version    from duckduckgo_search import DDGS
    def search(query, max_results=8):
        results = DDGS().text(query, max_results=max_results)
        return resultsMy daily drivers though are still either Codex or GPT5, Claude Code used to be but it just doesn't deliver the same results as it has previously.
It’s not very fast, and I built it up slowly without knowing quite where I was headed. If I could do it over again, I’d go with a recent EPYC with 12 channels of DDR5 and pair it with a single RTX 6000 Pro Blackwell.