You can’t let it overflow if you’re using LLMs on windows. There’s a toggle for it in the Nvidia settings, and get llama.cpp to offload though its settings (or better yet, use exllama instead).
But…. Yeah. Qwen 32B fits in 24GB perfectly, and it’s great, but 72B really feels like the intelligence tipping point where I can dump so many API models, and that won’t fit in 24GB.
You are not logged in. However you can subscribe from another Fediverse account, for example Lemmy or Mastodon. To do this, paste the following into the search field of your instance: !selfhosted@lemmy.world
A place to share alternatives to popular online services that can be self-hosted without giving up privacy or locking you into a service you don’t control.
Rules:
Be civil: we’re here to support and learn from one another. Insults won’t be tolerated. Flame wars are frowned upon.
No spam posting.
Posts have to be centered around self-hosting. There are other communities for discussing hardware or home computing. If it’s not obvious why your post topic revolves around selfhosting, please include details to make it clear.
Don’t duplicate the full text of your blog or github here. Just post the link for folks to click.
Submission headline should match the article title (don’t cherry-pick information from the title to fit your agenda).
No trolling.
Resources:
selfh.st Newsletter and index of selfhosted software and apps
I’ve got a 3090, and I feel ya. Even 24 gigs is hitting the cap pretty often and slowing to a crawl once system ram starts being used.
You can’t let it overflow if you’re using LLMs on windows. There’s a toggle for it in the Nvidia settings, and get llama.cpp to offload though its settings (or better yet, use exllama instead).
But…. Yeah. Qwen 32B fits in 24GB perfectly, and it’s great, but 72B really feels like the intelligence tipping point where I can dump so many API models, and that won’t fit in 24GB.