# Models, Page 279 of 501 Source: https://savrn.com/models/page/279 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- 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](https://savrn.com/model-hub/methodology) ## Filter Models Task - [Text generation1,467](https://savrn.com/models?task=Text+generation) - [Image and text to text542](https://savrn.com/models?task=Image+and+text+to+text) - [Robotics370](https://savrn.com/models?task=Robotics) - [Feature extraction352](https://savrn.com/models?task=Feature+extraction) - [Text classification326](https://savrn.com/models?task=Text+classification) - [Text to image224](https://savrn.com/models?task=Text+to+image) - [Speech recognition176](https://savrn.com/models?task=Speech+recognition) - [Audio classification160](https://savrn.com/models?task=Audio+classification) - [Text to speech141](https://savrn.com/models?task=Text+to+speech) - [Image classification138](https://savrn.com/models?task=Image+classification) - [Sentence similarity103](https://savrn.com/models?task=Sentence+similarity) - [Token classification97](https://savrn.com/models?task=Token+classification) - [Reinforcement learning96](https://savrn.com/models?task=Reinforcement+learning) - [Zero-shot classification93](https://savrn.com/models?task=Zero-shot+classification) - [Image segmentation90](https://savrn.com/models?task=Image+segmentation) - [Object detection86](https://savrn.com/models?task=Object+detection) - [Any to any79](https://savrn.com/models?task=Any+to+any) - [Translation79](https://savrn.com/models?task=Translation) - [Question answering73](https://savrn.com/models?task=Question+answering) - [Fill mask69](https://savrn.com/models?task=Fill+mask) - [Time series forecasting64](https://savrn.com/models?task=Time+series+forecasting) - [Video classification60](https://savrn.com/models?task=Video+classification) - [Image to text59](https://savrn.com/models?task=Image+to+text) - [Text to video55](https://savrn.com/models?task=Text+to+video) Library - [transformers2,877](https://savrn.com/models?library=transformers) - [peft357](https://savrn.com/models?library=peft) - [diffusers199](https://savrn.com/models?library=diffusers) - [pytorch189](https://savrn.com/models?library=pytorch) - [gguf175](https://savrn.com/models?library=gguf) - [lerobot148](https://savrn.com/models?library=lerobot) - [mlx148](https://savrn.com/models?library=mlx) - [sentence-transformers139](https://savrn.com/models?library=sentence-transformers) - [timm49](https://savrn.com/models?library=timm) - [transformers.js45](https://savrn.com/models?library=transformers.js) - [flaxspeaker44](https://savrn.com/models?library=flaxspeaker) - [llama.cpp44](https://savrn.com/models?library=llama.cpp) - [onnx39](https://savrn.com/models?library=onnx) - [vllm38](https://savrn.com/models?library=vllm) - [openpi35](https://savrn.com/models?library=openpi) - [diffusion-single-file28](https://savrn.com/models?library=diffusion-single-file) - [minimax-h326](https://savrn.com/models?library=minimax-h3) - [ultralytics24](https://savrn.com/models?library=ultralytics) - [PaddleOCR22](https://savrn.com/models?library=PaddleOCR) - [openvino20](https://savrn.com/models?library=openvino) - [exllamav319](https://savrn.com/models?library=exllamav3) - [coreml18](https://savrn.com/models?library=coreml) - [litert17](https://savrn.com/models?library=litert) - [rkllm15](https://savrn.com/models?library=rkllm) Modality - [Other6,847](https://savrn.com/models?modality=Other) - [Text2,701](https://savrn.com/models?modality=Text) - [Image and text601](https://savrn.com/models?modality=Image+and+text) - [Image586](https://savrn.com/models?modality=Image) - [Audio495](https://savrn.com/models?modality=Audio) - [Control466](https://savrn.com/models?modality=Control) - [Video115](https://savrn.com/models?modality=Video) - [Multimodal79](https://savrn.com/models?modality=Multimodal) - [Time series64](https://savrn.com/models?modality=Time+series) - [Tabular56](https://savrn.com/models?modality=Tabular) License - [apache-2.03,220](https://savrn.com/models?license=apache-2.0) - [mit1,282](https://savrn.com/models?license=mit) - [other743](https://savrn.com/models?license=other) - [cc-by-nc-4.0201](https://savrn.com/models?license=cc-by-nc-4.0) - [cc-by-4.0155](https://savrn.com/models?license=cc-by-4.0) - [bsd-3-clause108](https://savrn.com/models?license=bsd-3-clause) - [gemma63](https://savrn.com/models?license=gemma) - [cc-by-nc-sa-4.051](https://savrn.com/models?license=cc-by-nc-sa-4.0) - [llama3.240](https://savrn.com/models?license=llama3.2) - [agpl-3.032](https://savrn.com/models?license=agpl-3.0) - [unknown29](https://savrn.com/models?license=unknown) - [llama3.128](https://savrn.com/models?license=llama3.1) - [cc-by-sa-4.020](https://savrn.com/models?license=cc-by-sa-4.0) - [gpl-3.017](https://savrn.com/models?license=gpl-3.0) - [openrail++17](https://savrn.com/models?license=openrail%2B%2B) - [openmdw-1.115](https://savrn.com/models?license=openmdw-1.1) - [llama314](https://savrn.com/models?license=llama3) - [openrail14](https://savrn.com/models?license=openrail) - [cc-by-nc-nd-4.013](https://savrn.com/models?license=cc-by-nc-nd-4.0) - [creativeml-openrail-m13](https://savrn.com/models?license=creativeml-openrail-m) - [llama28](https://savrn.com/models?license=llama2) - [afl-3.07](https://savrn.com/models?license=afl-3.0) - [osl-3.06](https://savrn.com/models?license=osl-3.0) - [cc0-1.04](https://savrn.com/models?license=cc0-1.0) Access - [Open weights11,627](https://savrn.com/models?access=open_access) - [Access requested at publisher383](https://savrn.com/models?access=gated) Publisher - [Team Mradermacher313](https://savrn.com/models?publisher=mradermacher) - [Yurun Yuan106](https://savrn.com/models?publisher=ryanyr) - [RunningHub.ai101](https://savrn.com/models?publisher=runninghubai) - [Qwen91](https://savrn.com/models?publisher=qwen) - [Jenny Wilson85](https://savrn.com/models?publisher=jenny08311) - [Jessen Pu77](https://savrn.com/models?publisher=putty77) - [RKNNAI73](https://savrn.com/models?publisher=rknnai) - [AI at Meta72](https://savrn.com/models?publisher=facebook) - [Convergent Intelligence66](https://savrn.com/models?publisher=reaperdoesntknow) - [Google64](https://savrn.com/models?publisher=google) - [Yurun Yuan63](https://savrn.com/models?publisher=yurunyyr) - [Firza Hadzami61](https://savrn.com/models?publisher=firzahdzm) - [Zeyuan Yang59](https://savrn.com/models?publisher=miiche) - [Yurun Yuan59](https://savrn.com/models?publisher=yuruny) - [Yanggangu57](https://savrn.com/models?publisher=yanggangu) - [Hongao56](https://savrn.com/models?publisher=cisco1963) - [Francesca Padovani53](https://savrn.com/models?publisher=francesca9805) - [Szekely52](https://savrn.com/models?publisher=attila115) - [Yurun Yuan51](https://savrn.com/models?publisher=yyuan244) - [Wang49](https://savrn.com/models?publisher=davidwdw) - [Christopher Subia-Waud48](https://savrn.com/models?publisher=cwaud) - [Microsoft48](https://savrn.com/models?publisher=microsoft) - [NVIDIA48](https://savrn.com/models?publisher=nvidia) - [BAAR46](https://savrn.com/models?publisher=aixk) [Most downloaded](https://savrn.com/models?sort=downloads)[Most liked](https://savrn.com/models?sort=likes)[Recently updated](https://savrn.com/models?sort=updated)[Name](https://savrn.com/models?sort=name)[Largest](https://savrn.com/models?sort=params) 12,010 models, sorted by most downloaded. Model ### [cat09](https://savrn.com/models/cat09) [Trick](https://savrn.com/model-publishers/jokerjokerjoker) Open weights [View model](https://savrn.com/models/cat09) Model ### [cat09b](https://savrn.com/models/cat09b) [Trick](https://savrn.com/model-publishers/jokerjokerjoker) Open weights [View model](https://savrn.com/models/cat09b) Model ### [cat10](https://savrn.com/models/cat10) [Trick](https://savrn.com/model-publishers/jokerjokerjoker) Open weights [View model](https://savrn.com/models/cat10) Model ### [cat10b](https://savrn.com/models/cat10b) [Trick](https://savrn.com/model-publishers/jokerjokerjoker) Open weights [View model](https://savrn.com/models/cat10b) Model · Robotics ### [cawm](https://savrn.com/models/cawm) [Amin Abyaneh](https://savrn.com/model-publishers/aabyaneh) Pretrained checkpoints for the interactive world simulator (umi-wm / iws-model): an action-conditioned latent world model with a joint vision + tactile branch. The matching data lives in the dataset repo of the same name, Superseded releases are kept under legacy/ for reproducibility. Do not use them as defaults. Checkpoints for other world models, trained on the same data for comparison. They are not IWS models and do not follow the /checkpoints/ layout above. Most tasks have all four files. rubik and rubikeasy2cam currently ship stage 1 only — their wm.ckpt does not exist yet, because stage 2 has not been run for them. Every.yaml was verified to rebuild the model and load its checkpoint… Access requested at publisher mit [View model](https://savrn.com/models/cawm) Model ### [cc12m-3m-checkpoints](https://savrn.com/models/cc12m-3m-checkpoints) [Shdjd017](https://savrn.com/model-publishers/shdjd017) Open weights [View model](https://savrn.com/models/cc12m-3m-checkpoints) Model · Text to image ### [cdn3-hf](https://savrn.com/models/cdn3-hf) [Avik Banerjee](https://savrn.com/model-publishers/theavikb) A DreamBooth-LoRA for Krea 2, trained on Krea 2 RAW and shown on Krea 2 Turbo. The samples below were generated with this LoRA on Turbo (8 steps). Use the token cdn3 woman to invoke the concept. Open weights apache-2.0 diffusers [View model](https://savrn.com/models/cdn3-hf) Model ### [ce_checkpoints](https://savrn.com/models/ce-checkpoints) [Yang](https://savrn.com/model-publishers/milesyc) Open weights [View model](https://savrn.com/models/ce-checkpoints) Model ### [cefadf](https://savrn.com/models/cefadf) [Kgr4we](https://savrn.com/model-publishers/kgr4we) Open weights [View model](https://savrn.com/models/cefadf) Model ### [ceia-chess-models](https://savrn.com/models/ceia-chess-models) [Federico Fontanri](https://savrn.com/model-publishers/zfonta) Open weights [View model](https://savrn.com/models/ceia-chess-models) Model ### [cellpose-dino](https://savrn.com/models/cellpose-dino) [Arthur Zucker](https://savrn.com/model-publishers/arthurz) Open weights 303M parameters [View model](https://savrn.com/models/cellpose-dino) Model ### [cellpose-dino-vitb](https://savrn.com/models/cellpose-dino-vitb) [Arthur Zucker](https://savrn.com/model-publishers/arthurz) Open weights 86M parameters [View model](https://savrn.com/models/cellpose-dino-vitb) Model ### [cellpose-sam](https://savrn.com/models/cellpose-sam) [Arthur Zucker](https://savrn.com/model-publishers/arthurz) Open weights 305M parameters [View model](https://savrn.com/models/cellpose-sam) Model ### [cellpose-sam-v2](https://savrn.com/models/cellpose-sam-v2) [Arthur Zucker](https://savrn.com/model-publishers/arthurz) Open weights 305M parameters [View model](https://savrn.com/models/cellpose-sam-v2) Model · Text generation ### [cerulean-lab4-k0-df4cf9cb](https://savrn.com/models/cerulean-lab4-k0-df4cf9cb) [Nathan Tung](https://savrn.com/model-publishers/nat1an) This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). Open weights 124M parameters transformers [View model](https://savrn.com/models/cerulean-lab4-k0-df4cf9cb) Model · Text generation ### [cerulean-lab4-k1-964f796a](https://savrn.com/models/cerulean-lab4-k1-964f796a) [Nathan Tung](https://savrn.com/model-publishers/nat1an) This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). Open weights 124M parameters transformers [View model](https://savrn.com/models/cerulean-lab4-k1-964f796a) Model · Text generation ### [cerulean-lab4-k2-9e65f935](https://savrn.com/models/cerulean-lab4-k2-9e65f935) [Nathan Tung](https://savrn.com/model-publishers/nat1an) This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). Open weights 124M parameters transformers [View model](https://savrn.com/models/cerulean-lab4-k2-9e65f935) Model · Text generation ### [cevher-test-10-lc-it-4-GGUF](https://savrn.com/models/cevher-test-10-lc-it-4-gguf) [Bilal Cckfdn](https://savrn.com/model-publishers/bcckfdn) SmolLM2 (Llama) mimarisiyle sıfırdan eğitilmiş modelin GGUF sürümleri. Eğitim token sayısı: ~/.cache/lm-studio/models/bcckfdn/cevher-test-10-lc-it-4-GGUF/ altına koyun ya da uygulama içinden arayın. Open weights apache-2.0 [View model](https://savrn.com/models/cevher-test-10-lc-it-4-gguf) Model · Text generation ### [cevher-test-5-GGUF](https://savrn.com/models/cevher-test-5-gguf) [Bilal Cckfdn](https://savrn.com/model-publishers/bcckfdn) SmolLM2 (Llama) mimarisiyle sıfırdan eğitilmiş modelin GGUF sürümleri. Eğitim token sayısı: ~/.cache/lm-studio/models/bcckfdn/cevher-test-5-GGUF/ altına koyun ya da uygulama içinden arayın. Open weights apache-2.0 [View model](https://savrn.com/models/cevher-test-5-gguf) Model · Text generation ### [cfop-triage-ministral3-14b-v6](https://savrn.com/models/cfop-triage-ministral3-14b-v6) [ANDREW E ACHTENBERG](https://savrn.com/model-publishers/aachtenberg) A QLoRA fine-tune of Ministral 3 14B Instruct for cfoperator, an autonomous monitoring agent for a Kubernetes homelab. It replaced a 26B general model on that path at roughly 5x lower latency with the same accuracy on the project's triage suite. This is not a general assistant. It was trained on exactly one system prompt and answers with exactly one JSON shape. Outside that prompt it is just a slightly bent Ministral. Read What it is not before downloading 8 GB. The vision projector (mmproj) is not included. Triage is text-only and the training run never exercised the vision layers. With ollama, either pull straight from the Hub or build from the Modelfile. The Modelfile is the… Open weights apache-2.0 [View model](https://savrn.com/models/cfop-triage-ministral3-14b-v6) Model ### [cftvae-d128-vavae0.2-flux2enc-vitamindec-native32](https://savrn.com/models/cftvae-d128-vavae0-2-flux2enc-vitamindec-native32) [Xuantong LIU](https://savrn.com/model-publishers/xuantonglll) Open weights mit pytorch [View model](https://savrn.com/models/cftvae-d128-vavae0-2-flux2enc-vitamindec-native32) Model ### [cftvae-d128-vavae0.5-flux2enc-vitamindec-native32](https://savrn.com/models/cftvae-d128-vavae0-5-flux2enc-vitamindec-native32) [Xuantong LIU](https://savrn.com/model-publishers/xuantonglll) Open weights mit pytorch [View model](https://savrn.com/models/cftvae-d128-vavae0-5-flux2enc-vitamindec-native32) Model ### [ch](https://savrn.com/models/ch) [Big](https://savrn.com/model-publishers/loolooch) Open weights [View model](https://savrn.com/models/ch) Model · Text generation ### [ch01-text-finetune](https://savrn.com/models/ch01-text-finetune) [Kingsman1](https://savrn.com/model-publishers/kingsman1) Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). - PEFT 0.21.1 Open weights peft [View model](https://savrn.com/models/ch01-text-finetune) ## Model Collections Hand-picked starting points, each with the reason it exists. Collection · 4 entries ### [Embedding models for retrieval](https://savrn.com/collections/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. [View collection](https://savrn.com/collections/embedding-models-for-retrieval) Collection · 4 entries ### [Models that fit on one accelerator](https://savrn.com/collections/models-that-run-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. [View collection](https://savrn.com/collections/models-that-run-on-one-accelerator) Collection · 6 entries ### [Open-weight text models worth knowing](https://savrn.com/collections/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. [View collection](https://savrn.com/collections/open-weight-text-models-worth-knowing) Collection · 3 entries ### [Speech and audio models](https://savrn.com/collections/speech-and-audio) Recognition and synthesis models, grouped so the two directions are easy to compare. [View collection](https://savrn.com/collections/speech-and-audio) ## 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](https://savrn.com/ai-index/pricing/open-models) The same open-weight model priced by every host that serves it, per million tokens. Research Hub ### [Data center trackers and maps](https://savrn.com/data-center-research) Moratoriums, permits, power, water and capital behind the facilities that run these models. Method ### [How the Model Hub is built](https://savrn.com/model-hub/methodology) Sources, evidence labels, refresh behaviour, and the limits of every comparison here.