Emu3.5 is a native multimodal model developed by the Beijing Academy of Artificial Intelligence (BAAI). It can jointly predict the next state across vision and language, enabling coherent world modeling and generation. After end-to-end pre-training and large-scale reinforcement learning post-training, it demonstrates excellent performance in multimodal tasks.

MultimodalTransformers

Qwen3-Next-80B-A3B-Thinking is a new-generation thinking large language model launched by the Tongyi Qianwen team. It adopts an innovative hybrid attention mechanism and a highly sparse MoE architecture. While maintaining efficient reasoning, it has powerful complex reasoning capabilities and natively supports a context length of 262K.

Natural Language ProcessingTransformers

Qwen3-Next-80B-A3B-Instruct is a cutting-edge large language model in the Qwen3-Next series. It improves parameter efficiency and inference speed through an innovative architecture and demonstrates excellent performance in multiple domains. It natively supports long context processing.

Natural Language ProcessingTransformers

Sungur-14B is a large language model specifically designed for Turkish, derived from Qwen/Qwen3-14B. The model is fine-tuned using a dataset containing 41,100 Turkish samples, covering reasoning dialogues in fields such as mathematics, medicine, and general knowledge, aiming to enhance the native reasoning ability in Turkish.

Natural Language ProcessingGgufOther

LLaVA-OneVision-1.5 is a series of fully open-source large multimodal models that achieve advanced performance at a lower cost by training on native resolution images. This model demonstrates excellent performance in multiple multimodal benchmark tests, surpassing competitors such as Qwen2.5-VL.

MultimodalTransformers

Qwen3-Next-80B-A3B-Instruct is the latest generation of large language model developed by the Tongyi Qianwen team at Alibaba. It adopts an innovative hybrid attention mechanism and a highly sparse mixture-of-experts architecture. While maintaining a total of 80B parameters, only 3B parameters are activated, achieving efficient context modeling and inference acceleration. It natively supports a context length of 262K and can be extended to 1M tokens.

Natural Language ProcessingTransformers

Seed-OSS is an open-source large language model series developed by the ByteDance Seed team. It has powerful long context processing, reasoning, and agent interaction capabilities. Trained with only 12T tokens, it performs excellently in multiple public benchmark tests and supports native long context processing of up to 512K.

Natural Language ProcessingTransformers

InternVL3 - 78B - Instruct is an advanced multimodal large language model that performs excellently in multimodal perception, reasoning, and language processing. Through the native multimodal pre - training method, this model integrates visual and language learning into a unified training stage and demonstrates outstanding capabilities in multiple fields such as tool use, GUI agents, industrial image analysis, and 3D visual perception.

MultimodalTransformersOther

InternVL3-2B-Instruct is an advanced multimodal large language model. Compared with its predecessors, it has better multimodal perception and reasoning capabilities, and has expanded in aspects such as tool usage, GUI agents, industrial image analysis, and 3D visual perception. It adopts a native multimodal pre-training method, integrating language and visual learning into a single pre-training stage.

MultimodalTransformersOther

Llama Guard 4 is a native multimodal safety classifier with 12 billion parameters, jointly trained on text and multiple images for content safety evaluation of large language model inputs and outputs.

MultimodalTransformersEnglish

InternVL3-1B is an advanced multimodal large language model developed by OpenGVLab, which has completed native multimodal pretraining but has not undergone post-training.

MultimodalTransformersOther

Kanana 1.5 is a bilingual large language model developed by Kakao Corporation, supporting English and Korean, with significant improvements in programming, mathematics, and function calling capabilities, natively supporting a 32K tokens context length

Natural Language ProcessingTransformersMultiple Languages

The first open-source, native 1-bit large language model developed by Microsoft Research, with a parameter scale of 2 billion, trained on a corpus of 4 trillion tokens.

Natural Language ProcessingGgufEnglish

The first open-source 2-billion-parameter native 1-bit large language model developed by Microsoft Research, trained on 4 trillion tokens, demonstrating that native 1-bit large language models can significantly improve computational efficiency while maintaining performance comparable to full-precision open-source models of the same scale.

Natural Language ProcessingTransformersEnglish

An open-source native 1-bit large language model developed by Microsoft Research, with 2 billion parameters trained on a 4 trillion token corpus, significantly improving computational efficiency.

Natural Language ProcessingTransformersEnglish

Kumru-2B is a lightweight, open-source large language model developed from scratch by VNGRS specifically for Turkish. This model was pre-trained on 300 billion tokens from a 500GB cleaned and deduplicated Turkish corpus. It is equipped with a modern tokenizer optimized for Turkish, supports code, math, and chat templates, and has a default native context length of 8192 tokens.

Natural Language ProcessingTransformersOther

A large language model (LLM) specifically customized for translation applications, dedicated to providing convenient multilingual native-level information experiences.

Natural Language ProcessingGgufMultiple Languages

Tucano-2b4 is a large - scale language model that is natively pre - trained specifically for Portuguese. It is based on the Transformer architecture and trained on the GigaVerbo dataset with 200 billion tokens.

Natural Language ProcessingTransformersOther

A multimodal language model based on the Llama-3 architecture, natively supporting audio and text input comprehension, focusing on enhancing large language models' understanding of audio.

MultimodalSafetensorsEnglish

Tucano-1b1 is a decoder-transformer model that is natively pre-trained specifically for Portuguese. It is trained on a large-scale Portuguese text corpus and focuses on Portuguese text generation tasks, with 1.1 billion parameters.

Natural Language ProcessingTransformersOther