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How to pick a local open model for typed decisions with Awesome Jev Gallery

Match your hardware to a listed open decision model and check its README before running it.

  • Top pick
  • Research
  • Intermediate
  • 60 minutes
  • From the README
  • Any agent

Who it is forA developer who wants typed decisions without a cloud API and has a specific GPU or Mac.

The problemThe Open Source section lists many models with different hardware targets, sizes and licenses, and it is hard to tell which one fits.

The outcomeA shortlist of one or two models that match your hardware, with the license and setup notes read from each repo.

What you need first

  • A web browser to read the list and the linked repositories
  • Hardware that matches the open model you choose, such as an RTX GPU or Apple Silicon for local runs
  • A decision task with a fixed set of options you want scored

Steps

  1. Open the Open Source section of the Awesome JEV README.
  2. Match your hardware to an entry: Rizzo Flow for local runs through llama.cpp, or Laya-MLX or Laya Ultrafast for a local MLX port on Apple Silicon.
  3. Open that repo and read its README for setup steps the list does not cover.
  4. Follow the Hugging Face link on the entry to find the model weights.
  5. Send one typed question with a fixed option set and check that you get one probability per option.

Prompt for your agent

Using the Awesome JEV list at https://github.com/OmniJev/awesome-jev-gallery, find the Open Source entry that matches <hardware>, read its README, and report the setup steps and the output format for one typed decision. Verify that the README states a license before you recommend the entry.

Caveat. Many entries are unofficial or independent projects, and the speed and accuracy figures are reported by their authors, not verified here.

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Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page