Post by @Rentlar@lemmy.ca

2026-10-31 17:02 UTC

Local LLMs are the way to go on AI, they can’t suddenly change the model up on you. And also, I guess Anthropic just wants their models to be more useless ahead of going public? Because I presume people that want to use AI, who don’t care where they send their data to, but don’t want to nagged about how they can’t do benign programming and analysis tasks, will just choose another model provider.

Replies (2)

@Spite_By_Design_LLC@lemmy.dbzer0.com 2026-11-01 07:40

The are the way to go, but hardware pricing makes it cost prohibitive to match frontier capabilities, which makes decomp and recomp difficult. Or rather, require more skill and take longer, introducing some barriers. We all know the eye watering prices GPUs and RAM cost now, to say nothing of UnifiedMenory devices like the Strix. Most people just don’t have a spare $10K to throw at an inference box that can run (say) a 300B model. Coming at this from another angle tho, I note that according to Steam stats, the most popular GPUs are in the 8Gb and 16Gb range…which is smack bang in the VRAM range of what a good MoE (say, Qwen 3.6 35B-A3B) runs on (for 8gb) or arguably the best local dense coder (Qwen 3.8 27B) can live at. I think there’s probably room for great LLM improvement in the 8-16gb range…and given that most consumer pcs and laptops live there, I’m sanguine the open weight devs might make it happen. But I also suspect the gate keeping of high end capacities is intentional. We’re probably note going to have the ability to vibe code Mario into Elden Ring again…not without significantly more skill. Dunno.

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@W98BSoD@lemmy.dbzer0.com 2026-10-31 18:35

Is there a local LLM I can run on an 8-10th gen i5 with 16GB RAM?

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