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.
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.
Local LLMs have been useful since 2024. If you don't know this then you are just far behind. Catch up!
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.
Which ones are most useful? Any suggestions on where to go to start exploring this world?
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
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.
until its cheaper to train and infer than 100k gpu data centers...i doubt it will ever compete.