SAVRN Model Hub
Open-Weight Models
An open-weight model is an AI model whose trained weights are published for anyone to download. The weights are what the model learned in training. With a copy of them you can run the model on hardware you control and train it further on your own data.
Open weights are not the same as open source. Many publishers release the weights without the training data or code, and the license sets what you may do with the model. This library puts each model's full card, architecture, files, license and published evaluations on one page.
12,010Models
3,413Datasets
288Papers
7,298Publishers
12,421Sourced relationships
Updated 2026-10-21 · How the library is built
12,010 models, sorted by most downloaded.
An unchanged copy of mobiuslabsgmbh/faster-whisper-large-v3-turbo at commit 0a363e9161cbc7ed1431c9597a8ceaf0c4f78fcf, kept so the Capset caption panel for After Effects downloads from a source that cannot change under it. Whisper large-v3-turbo by OpenAI, converted to CTranslate2 by Mobius Labs. Original model: openai/whisper-large-v3-turbo. Licence: MIT (the LICENSE file), the same as the original. No file here has been modified; the original model card is kept as UPSTREAM-README.md.
An unchanged copy of istupakov/parakeet-tdt-0.6b-v3-onnx at commit 8f23f0c03c8761650bdb5b40aaf3e40d2c15f1ce, kept so the Capset caption panel for After Effects downloads from a source that cannot change under it. Parakeet TDT 0.6B v3 by NVIDIA, exported to ONNX by istupakov. Original model: nvidia/parakeet-tdt-0.6b-v3. Licence: CC-BY-4.0 (https://creativecommons.org/licenses/by/4.0/), the same as the original. No file here has been modified; the original model card is kept as UPSTREAM-README.md.
Base model: indobenchmark/indobert-base-p1; Input: title, description; Tokenization: maxlength=256, truncation=True; Output: Single label, with confidence score for each label..
The optional in-browser model of the career assistant on Jinwoo Seol's portfolio site. in English or Korean; decline personal, off-topic and unknown questions with fixed sentences.
CARI4D CoCoNet Native Momentum Human Rig (MHR) refines one human's native MHR parameters and one rigid object's pose over video and predicts one contact logit per hand. It supports 4D human-object reconstruction, motion analysis, visualization, data curation, and robotics perception without direct autonomous actuation. CARI4D CoCoNet Native MHR was developed by NVIDIA Research. This model is ready for commercial or non-commercial use. GOVERNING DOWNLOAD TERMS: Use of the model is governed by the NVIDIA Open Model Agreement. Global. For developers and researchers building commercial or noncommercial computer-vision systems for 3D/4D human-object pose estimation, motion analysis…
Model Collections
Hand-picked starting points, each with the reason it exists.
Collection · 4 entries
Embedding models for retrieval
Sentence and document embedding models used to build retrieval systems. Dimension and sequence length matter more than size here, and both come from the publisher.
Collection · 4 entries
Models that fit on one accelerator
Models whose publisher-reported parameter count puts them within reach of a single accelerator at common precisions. Memory needed depends on precision and serving configuration, so treat the parameter count as the starting point, not the answer.
Collection · 6 entries
Open-weight text models worth knowing
Widely used open-weight language models, chosen because each one is a distinct family rather than a variant of the one above it. Selection, not a ranking.
Collection · 3 entries
Speech and audio models
Recognition and synthesis models, grouped so the two directions are easy to compare.
Open-Weight Models Explained
What is an open-weight model?
An AI model whose trained weights are published for anyone to download, so it can be run, tested and fine-tuned on hardware the user controls.
Is an open-weight model the same as open source?
Not always. Open weights means the trained model can be downloaded. Open source usually also means the training code and data are available and the license allows broad reuse. Many open-weight models release the weights only.
Can I use an open-weight model commercially?
It depends on the license. Apache 2.0 and MIT allow commercial use. Other licenses limit it, for example to non-commercial use or below a set number of users. Every model page here shows its license.
How much memory does an open-weight model need?
About two bytes per parameter at 16-bit precision, so a 7-billion-parameter model needs roughly 14 GB for its weights, plus memory for the context it processes. Each model page lists its parameter count and the size of its files.
Related SAVRN Research
The hub sits beside SAVRN's market data and infrastructure research: what models cost to run, and what it takes to run them.
SAVRN Index
What open models cost to run
The same open-weight model priced by every host that serves it, per million tokens.
Research Hub
Data center trackers and maps
Moratoriums, permits, power, water and capital behind the facilities that run these models.
Method
How the Model Hub is built
Sources, evidence labels, refresh behaviour, and the limits of every comparison here.