Bee-8B is an advanced fully open-source multimodal large language model that focuses on data quality and aims to narrow the performance gap with proprietary models. By using the high-quality Honey-Data-15M corpus and the advanced data processing pipeline HoneyPipe, it demonstrates excellent performance in complex reasoning and other aspects.

MultimodalTransformersEnglish

Apertus is a fully open multilingual large language model developed by Swiss AI, offering two parameter scales of 7 billion and 8 billion. This model supports over 1000 languages, uses fully compliant and open training data, and its performance can rival that of closed-source models. Apertus was pre-trained on 15T tokens and adopts a phased curriculum training method, supporting a context length of up to 65,536 tokens.

Natural Language ProcessingTransformersOther

Apertus is a fully open multilingual large language model developed by Swiss AI. It has parameter scales of 8 billion and 70 billion, supports over 1000 languages and long context processing, and only uses fully compliant open training data. Its performance can rival that of closed-source models.

Natural Language ProcessingTransformersOther

GLM-4.6 is a new-generation text generation model launched by Zhipu AI. Compared with GLM-4.5, it has significant improvements in multiple aspects, including a longer context window, better coding performance, and stronger reasoning ability. This model performs excellently in multiple public benchmark tests and has a competitive advantage compared with leading models at home and abroad.

Natural Language ProcessingTransformersMultiple Languages

CoDA is a code generation language model based on diffusion models developed by Salesforce AI Research. It has the ability to understand bidirectional context and is specifically designed for powerful code generation and completion tasks. This model only has 1.7 billion parameters and achieves excellent code generation performance while maintaining low computational requirements.

Natural Language ProcessingTransformersEnglish

AcTora is an advanced language model and Python library designed to predict user interactions on social media. This project was developed by AmrTweg with the support of RdivxeAI and MechaML, aiming to apply language models to marketing research.

Natural Language ProcessingTransformers

GA Guard Lite is a lightweight open-source moderation model developed by General Analysis, specifically designed to detect prohibited content in the outputs of language models. This model can identify seven categories of security risks, including illegal activities, hate speech, and personal information leakage, providing efficient content security protection for AI applications.

Natural Language ProcessingTransformersEnglish

This project is a quantized version of swiss-ai/Apertus-8B-Instruct-2509, aiming to make knowledge models more accessible and usable through quantization technology. The project is currently in the experimental stage and uses the GGUF format for optimization.

Natural Language ProcessingGguf

This is a quantized version based on the Huihui-Hunyuan-MT-Chimera-7B model, aiming to make large language models easier to deploy and use through quantization technology, enabling knowledge to be accessible to everyone.

Natural Language ProcessingGguf

This project provides a quantized version of Tencent's Hunyuan-MT-7B large language model. Through model compression technology, it reduces the computing and storage requirements, aiming to make knowledge accessible to everyone and make high-performance AI models more popular and user - friendly.

Natural Language ProcessingGguf

GLM-4.5V-AWQ-4bit is a quantized multimodal model built on Zhipu AI's next-generation flagship text foundation model. Optimized by AWQ-4bit quantization technology, it significantly reduces the computational resource requirements while maintaining excellent performance. This model achieves SOTA performance among models of the same scale in 42 public visual language benchmark tests and has powerful visual reasoning capabilities.

MultimodalTransformersMultiple Languages

DINOv3 is a series of general visual foundation models developed by Meta AI. Without fine-tuning, it can outperform specialized state-of-the-art models in a wide range of visual tasks. This model uses self-supervised learning to generate high-quality dense features and performs excellently in various tasks such as image classification, segmentation, and depth estimation.

Computer VisionTransformersEnglish

DINOv3 is a versatile visual foundation model developed by Meta AI. It can outperform specialized models in a wide range of visual tasks without fine-tuning. This model can generate high-quality dense features and performs excellently in various visual tasks, significantly surpassing previous self-supervised and weakly supervised foundation models.

Computer VisionTransformersEnglish

DINOv3 is a series of general visual foundation models developed by Meta AI. It can outperform specialized advanced models in various visual tasks without fine-tuning. The model adopts the Vision Transformer architecture and is pre-trained on 1.689 billion web images. It can generate high-quality dense features and performs excellently in tasks such as image classification, segmentation, and retrieval.

Computer VisionTransformersEnglish

Cthulhu 24B 1.1 GGUF is a large language model fused based on the Mistral Small series of models, integrating 17 different model components. It has the capabilities of creative writing, uncensored dialogue, and rich language interaction. Inspired by the Cthulhu mythos, this model aims to provide a'super fusion' experience that goes beyond the capabilities of a single model.

Natural Language ProcessingTransformersEnglish

GLM-4.1V-9B-Thinking is an open-source model developed based on the Vision-Language Model (VLM), aiming to explore the upper limit of the reasoning ability of vision-language models. By introducing the 'thinking paradigm' and reinforcement learning, it significantly improves the model's ability and reaches the leading level among VLMs with 10B parameters.

MultimodalTransformersMultiple Languages

Devstral 1.1 is an intelligent large language model jointly developed by Mistral AI and All Hands AI, specifically designed for software engineering tasks. This model performs excellently in the SWE-bench benchmark test, ranking first among open-source models. It has 24 billion parameters and a long context window of 128k tokens.

Natural Language ProcessingSafetensorsMultiple Languages

SmolLM3 is a language model with 3 billion parameters, aiming to break the performance boundary of small models. It supports 6 languages, has advanced reasoning ability and long context processing ability, and is a fully open-source model.

Natural Language ProcessingTransformersMultiple Languages

The Deep Ignorance Model Suite is a collection of 18 large language models with 6.9 billion parameters each. It aims to study methods of preventing models from learning unsafe technical capabilities (such as CBRN-related capabilities) by filtering pretrained data. This suite demonstrates that filtering data can effectively avoid the learning of bad knowledge while maintaining general performance and having anti-tampering capabilities.

Natural Language ProcessingTransformersEnglish

MedGemma is a series of AI models developed by Google, specifically optimized for medical scenarios. It includes two versions: a 4B multimodal version and a 27B pure-text version. Based on the Gemma 3 architecture, it performs excellently in medical text and image understanding tasks and can effectively support the development of medical AI applications.

MultimodalTransformers