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What you can do with Awesome Jev Gallery

A curated list of papers, open models, benchmarks, commentary and projects tied to TypeSafe's System One models and Jev.

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OmniJev/awesome-jev-gallery on GitHub

Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk.

What do you want to do?

4 use cases

  • Pick a local open model for typed decisions

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

    View prompt
    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.

  • Compare typed-decision models on shared benchmarks

    Use the Benchmark and Leaderboard section to run the same public tasks on two candidate models.

    View prompt
    Using the Benchmark and Leaderboard section of https://github.com/OmniJev/awesome-jev-gallery, collect the public evaluation suites and their task counts, then produce a table of <model A> and <model B> accuracy on one shared suite. Verify that both models were scored on identical tasks before you report a difference.

  • Route Thai or Japanese intents with a small model

    Use the Thai and Japanese decision models to score fixed intent labels for local-language messages.

    View prompt
    Using the OpenThai-SystemOne and sokudan entries in https://github.com/OmniJev/awesome-jev-gallery, map <intent labels> to a fixed option set and score a held-out sample of <language> messages. Report the label probabilities for each message. Verify that the labels cover every intent you plan to route.

  • Have an AI agent design a System One workflow

    Install TypeSafe's agent skill files so Claude Code or Codex can draft a typed System One workflow.

    View prompt
    Using the skill files in https://github.com/typesafe-ai/skills, design a System One workflow for <decision task> using the Choice, Score or Noul primitive. Output the typed question and the fixed option set. Verify that every option is listed and that the output asks for a probability per option.

How to use Awesome Jev Gallery

  1. Check you have what it needs: 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.
  2. Open OmniJev/awesome-jev-gallery on GitHub and read the README and license.
  3. Open the Open Source section of the Awesome JEV README.
  4. 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.
  5. Open that repo and read its README for setup steps the list does not cover.
  6. Follow the Hugging Face link on the entry to find the model weights.

These steps come from our top use case, Pick a local open model for typed decisions, which also has a copy-paste agent prompt.

Awesome Jev Gallery alternatives · Best AI repos for Research

About this repo

Requirements

  • 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
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Questions about Awesome Jev Gallery

What is Awesome Jev Gallery?

A curated list of papers, open models, benchmarks, commentary and projects tied to TypeSafe's System One models and Jev. It is an open-source project on GitHub: https://github.com/OmniJev/awesome-jev-gallery.

Who is Awesome Jev Gallery for?

Useful for ML engineers, product teams and agent builders who want to pick, compare or design typed-decision models.

What can I do with Awesome Jev Gallery?

4 use cases so far, for example: Pick a local open model for typed decisions; Compare typed-decision models on shared benchmarks; Route Thai or Japanese intents with a small model. Each has steps and a copy-paste agent prompt.

What do I need to run Awesome Jev Gallery?

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.

What are alternatives to Awesome Jev Gallery?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Awesome Jev Gallery safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.