Molmo2 O 7B Alternatives

Molmo2-4B is an open-source vision-language model developed by the Allen Institute for AI. It supports a wide range of multimodal tasks including image and video captioning, visual question answering, pointing, and instruction following. The model weights are publicly available on Hugging Face for local inference or fine-tuning by developers and researchers.

Molmo2-8B is a multimodal foundation model developed by the Allen Institute for AI. It excels at a wide variety of vision-language tasks including captioning, visual question answering, pointing, and video understanding. The model supports numerous specialized prompting styles and is provided with open weights for researchers and developers to build upon.

OLMo-2-0425-1B is part of AllenAI's Open Language Model (OLMo) series. It is a fully open 1-billion-parameter model with training data, code, and weights released to the public. Designed for research and experimentation, it supports text generation and can be run locally or fine-tuned for specific tasks. The model emphasizes transparency in AI development.

OLMo-3-1025-7B is the latest iteration of the Allen Institute for AI's fully open language model series. Trained on the Dolma 3 Mix dataset, it offers transparent weights, architecture, and training data for the research community. The model supports standard transformer inference with Apache 2.0 licensing.

OLMoE-1B-7B-0924 is an open language model hosted on Hugging Face. It is designed for text-generation tasks and follows a Mixture-of-Experts architecture under the OLMo family. The model carries the pipeline tag text-generation and the tags moe and olmoe along with the language code en. It was created by allenai and made available as a public repository on 20 July 2024. The associated training dataset is allenai/OLMoE-mix-0924 and the work is referenced in arxiv:2409.02060. Model files use the safetensors format and the implementation relies on the transformers library. As of the latest update the repository has recorded more than 1.27 million lifetime downloads. Access occurs through the standard Hugging Face model hub where users can download weights directly. No inference providers are listed as available within the repository metadata and the model is not gated. The page indicates compatibility with existing transformers-based workflows for loading and running the model on supported hardware.

Olmo-Hybrid-7B is an open-source large language model released by the Allen Institute for AI. It supports local inference for text generation and research, with open weights and compatibility with Python and Docker. Designed for AI researchers and developers.

OLMoE-1B-7B-0125-Instruct is an open-source mixture-of-experts language model developed by the Allen Institute for AI. The 1B+7B parameter model is instruction-tuned and released with full weights and training code. It supports standard chat templates and is designed for research and local deployment by developers and researchers.

Olmo-3-7B-Instruct is the latest instruction-tuned model in the OLMo series developed by the Allen Institute for AI. It features fully open training data, architecture, and weights. The model supports function calling and is designed for researchers and developers who want complete transparency and the ability to run or fine-tune locally.