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Find the best model for a task v1.0.0

Use this resource to choose the best AI model for a given task and device

New

  • 388 downloads
  • 192 likes
  • 237 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install best-model-finder-benchmarks

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent identifies the task and hardware, queries the official benchmark leaderboards, enriches the results with model size and keeps only models that fit on the device. It then presents a comparison table with the scores.

Mostly picked by

Updated November 2, 2026

Card for the “Find the best model for a task” skill

Details

Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • SKILL.md: request analysis, memory budget per device and filtering
  • SKILL.md: comparison table and follow-up questions

Good fit for

  • You want a code model that runs on a 16 GB MacBook
  • You are choosing between reasoning models based on their scores

Not for

    Tags

    • benchmarks
    • models
    • comparison
    • hardware

    About

    You say

    “What is the best code model that fits on my 12 GB RTX card?”

    Card for the “Find the best model for a task” skill

    Skill published by huggingface under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to choose the best AI model for a given task and device
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md5.8 KB

    Origin and licence

    Listed unmodified

    Author
    huggingface
    Source
    github.com/huggingface/skills/tree/fabc634a893f62ad5c2039830397efa35fa62715/skills/huggingface-best
    Licence
    Apache-2.0

    Notice

    « huggingface-best » (huggingface, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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