Ask HN: How close are we to local LLMs being useful? What's the impact?
6 points
6 hours ago
| 4 comments
| HN
Feels to me like local models are an under-covered aspect of this whole AI boom.

If everything improves over time, at some point a good chunk of tasks won’t need to be done in data centers or be subject to the whims of a few frontier AI labs.

How close are we to that? Or is my thinking flawed?

segmondy
3 hours ago
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Local LLMs have been useful since 2024. If you don't know this then you are just far behind. Catch up!
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david927
6 hours ago
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I think we're past that point; they're absolutely useful already for a lot of tasks. I think it's about costs, convenience, and benefits of a frontier model for what you're doing.
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AbstractH24
5 hours ago
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Which ones are most useful? Any suggestions on where to go to start exploring this world?
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lgl
1 hour ago
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A good place to browse is the LocalLLaMa subreddit. [0]

A good software to start is LM Studio [1]. Another popular alternative is Ollama [2].

A better software when you're used to it all is llama.cpp as it's usually a bit faster and more frequently updated [3].

A good place to get models is HuggingFace, particularly the Unsloth models [4]

Most popular models lately to run on "regular" gaming PC's, workstations, Macs etc are: Qwen 3.5 9b, Qwen 3.6 35B-A3B, Qwen 3.6 27B, Gemma 4.

But there are hundreds or thousands of other models and different quantizations, finetunes, etc, etc. Have fun :)

[0] https://www.reddit.com/r/LocalLLaMA/

[1] https://lmstudio.ai/

[2] https://ollama.com/

[3] https://github.com/ggml-org/llama.cpp

[4] https://huggingface.co/unsloth/collections

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PaulHoule
6 hours ago
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I do classification with SLMs and for my tasks when I have a few thousand samples the frontier models in zero-shot and few-shot modes are embarassingly bad in comparison.
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buffer_overlord
6 hours ago
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until its cheaper to train and infer than 100k gpu data centers...i doubt it will ever compete.
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