Huggingface Best
Hugging FaceOfficialPublished by Hugging Face
- Skill
- Research and analysis
- Data and AI
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill assists users in selecting the most suitable AI models for specific tasks by querying official leaderboard data. It processes user requirements regarding task type and hardware specifications to provide a ranked comparison table. The skill evaluates models based on benchmark scores, parameter counts, and licensing, while offering guidance on whether a model can run locally on the user's device or requires cloud-based execution.
What it does
- Parses user requests to identify specific AI tasks and hardware constraints.
- Calculates parameter budgets based on available device memory.
- Retrieves and aggregates data from official benchmark leaderboards.
- Enriches model data with parameter counts and license information.
- Filters and ranks models based on benchmark performance and hardware compatibility.
- Generates a structured comparison table for easy model evaluation.
When to use it
- When you need to find the best AI model for a specific task like coding, RAG, or image classification.
- When you want to compare models based on objective benchmark scores.
- When you need to determine if a specific model will fit on your local hardware.
- When you are looking for state-of-the-art models for a particular use case.
Advantages
- Provides data-driven recommendations based on official benchmark results.
- Considers hardware limitations to ensure model feasibility.
- Offers clear visibility into model licensing and size.
- Simplifies the selection process by aggregating fragmented leaderboard information.
Usage examples
- “What is the best model for coding that I can run on my 16GB MacBook?”
- The agent identifies top-performing coding models, filters them by your 16GB memory constraint, and provides a comparison table showing which models fit in fp16 or Q4 quantization.
- “Compare the top models for speech recognition.”
- The agent retrieves the latest benchmark data for speech recognition and presents a ranked table of the top models, including their benchmark scores and license types.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/huggingface/huggingface-best/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip huggingface-best.zip -d .agents/skills
Documentation by Hugging Face
HuggingFace Best Model Finder
Finds the best models for a task by querying official HF benchmark leaderboards, enriching results with model size data, filtering for what fits on the user's device, and returning a comparison table with benchmark scores.
Step 1: Parse the request
Extract from the user's message:
Task: what they want the model to do (coding, math/reasoning, chat, OCR, RAG/retrieval, speech recognition, image classification, multimodal, agents, etc.)
Device: hardware constraints (MacBook M-series 8/16/32/64GB unified memory, RTX GPU with VRAM amount, CPU-only, cloud/no constraint, etc.)
If device is not mentioned, skip filtering entirely and return the highest-performing models regardless of size. If the task is genuinely ambiguous, ask one clarifying question.
Device → max parameter budget
When a device is specified, extract its available memory (unified RAM for Apple Silicon, VRAM for discrete GPUs) and apply:
fp16 max params (B) ≈ memory (GB) ÷ 2
Q4 max params (B) ≈ memory (GB) × 2
Examples: 16GB → 8B fp16 / 32B Q4 — 24GB VRAM → 12B fp16 / 48B Q4 — 8GB → 4B fp16 / 16B Q4
Step 2: Find relevant benchmark datasets
Fetch the full list of official HF benchmarks:
curl -s -H "Authorization: Bearer $(cat ~/.cache/huggingface/token)" \
"https://huggingface.co/api/datasets?filter=benchmark:official&limit=500" | jq '[.[] | {id, tags, description}]'Read the returned list and select the datasets most relevant to the user's task — match on dataset id, tags, and description. Use your judgment; don't limit yourself to 2-3. Aim for comprehensive coverage: if 5 benchmarks clearly cover the task, use all 5.
Step 3: Fetch top models from leaderboards
For each selected benchmark dataset:
curl -s -H "Authorization: Bearer $(cat ~/.cache/huggingface/token)" \
"https://huggingface.co/api/datasets/<namespace>/<repo>/leaderboard" | jq '[.[:15] | .[] | {rank, modelId, value, verified}]'Collect model IDs and scores across all benchmarks. If a leaderboard returns an error (404, 401, etc.), skip it and note it in the output.
Step 4: Enrich with model metadata
For the top 10-15 candidate model IDs, get model infos.
# REST API
curl -s -H "Authorization: Bearer $(cat ~/.cache/huggingface/token)" \
"https://huggingface.co/api/models/org/model1" | jq '{safetensors, tags, cardData}'
# CLI (hf-cli)
hf models info org/model1 --json | jq '{safetensors, tags, cardData}'Extract from each response:
Parameters:
safetensors.total→ convert to B (e.g., 7_241_748_480 → "7.2B")License: from model card tags (look for
license:apache-2.0,license:mit, etc.)If
safetensorsis absent, parse size from the model name (look for "7b", "8b", "13b", "70b", "72b", etc.)
Step 5: Filter and rank
If a device was specified:
Remove models exceeding the fp16 parameter budget for the device
Flag models that fit only with Q4 quantization (multiply budget by ~4 for Q4 capacity)
If a highly-ranked model is slightly over budget, keep it with a "needs Q4" note — don't silently drop it
If no device was mentioned: skip all size filtering — just rank by benchmark score.
Then: rank by benchmark score (descending), keep top 5-8 models.
Include proprietary models (GPT-4, Claude, Gemini) if they appear on leaderboards, but flag them as "API only / not self-hostable". If the user explicitly asked for local/open models only, exclude them.
Step 6: Output
Comparison table
| # | Model | Params | [Benchmark 1] | [Benchmark 2] | License | On device |
|---|-------|--------|--------------|--------------|---------|-----------|
| ⭐1 | [org/name](https://huggingface.co/org/name) | 7B | 85.2% | — | Apache 2.0 | Yes (fp16) |
| 2 | [org/name](https://huggingface.co/org/name) | 13B | 83.1% | 71.5% | MIT | Q4 only |
| 3 | [org/name](https://huggingface.co/org/name) | 70B | 90.0% | 81.0% | Llama | Too large |Link model names to
https://huggingface.co/<model_id>Use
—for benchmarks where the model wasn't evaluatedStar the top recommended pick with ⭐
"On device" values:
Yes (fp16),Q4 only,Too large,API only
Follow-up
After presenting the table, ask the user: "Would you like to run [top recommended model]?"
If they say yes, ask whether they'd prefer to:
Run locally — ask about their device if not already known, then give appropriate setup instructions
Run on HF Jobs — point them to the HF Jobs guide: https://huggingface.co/docs/huggingface_hub/en/guides/jobs
Error handling
Leaderboard not found: skip, note "leaderboard unavailable" in output
Model missing from hub_repo_details: fall back to parsing size from model name
No benchmarks found for task: use the curated fallback table above, or try
hub_repo_searchwithfilters=["<task>"]sorted bytrendingScoreAll leaderboards fail: fall back to
hub_repo_searchfor popular models tagged with the task, note that results are by popularity rather than benchmark score
Files
- ATTRIBUTION.mdAdded by AutoGineer876 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md5.7 KiB
LICENSE
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright [yyyy] [name of copyright owner]
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Hugging Face
- Publisher
- Hugging Face (Official)
- Source
- huggingface/skills · skills/huggingface-best · commit 25910b3
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Hugging Face or Hugging Face.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download huggingface-best.zip