Qwen3-VL-30B-A3B-Instruct is a multimodal vision-language model based on the Qwen3-VL-30B model, which supports joint understanding and generation tasks of images and text. This model adopts an advanced vision-language fusion architecture and can handle complex multimodal reasoning tasks.

MultimodalGguf

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

GLM-4.6-FP8 is a new-generation text generation model launched by Zhipu AI. It has significant improvements in multiple key aspects compared to GLM-4.5. This model has a longer context window, excellent coding performance, advanced reasoning ability, and more powerful agent functions, enabling it to handle more complex tasks.

Natural Language ProcessingTransformersMultiple Languages

This is the GGUF quantized version of Alibaba's Qwen series large language model with 8 billion parameters, designed for advanced reasoning, intelligent agent behavior, and multilingual tasks, and can be used with llama.cpp and compatible tools.

Natural Language ProcessingGgufMultiple Languages

InternVL3.5-4B is a medium-scale version of the open-source multimodal model series, containing 470 million parameters. It adopts an advanced cascaded reinforcement learning framework and visual resolution router technology, significantly improving the multimodal reasoning ability and efficiency.

MultimodalTransformersOther

InternVL3.5 is a new member of the open-source multimodal model family, significantly improving the versatility, reasoning ability, and reasoning efficiency of the InternVL series. It supports new functions such as GUI interaction and reaches the advanced level of open-source multimodal large language models.

MultimodalTransformersOther

TSLAM-15B is a 15-billion parameter telecom-specific language model developed by NetoAI Solutions. It is based on the Mixture-of-Experts (MoE) architecture and optimized for telecom domain expertise, advanced reasoning, and action-oriented workflows.

Natural Language ProcessingSafetensors

Intern-S1 is currently the most advanced open-source multimodal reasoning model. It combines powerful general task processing capabilities with excellent performance in a wide range of scientific tasks and can be comparable to leading closed-source commercial models. The model is continuously pre-trained on a 5T token dataset, of which more than 50% is professional scientific data. It has a dynamic word segmenter that can natively understand molecular formulas, protein sequences, and seismic signals.

MultimodalSafetensors

Intern-S1 is currently the most advanced open-source multimodal reasoning model, combining powerful general task capabilities with excellent performance on a wide range of scientific tasks, and can compete with leading closed-source commercial models.

MultimodalSafetensors

EXAONE-4.0-32B is a multilingual large model that combines advanced quantization technology with an efficient architecture. It has excellent text generation and reasoning capabilities and supports English, Korean, and Spanish.

Natural Language ProcessingTransformersMultiple Languages

Audio Flamingo 3 is an advanced, fully open-source large audio language model that can enhance the reasoning and understanding abilities of speech, sound, and music.

MultimodalSafetensorsEnglish

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

Spiral-Qwen3-4B is a model obtained by training the Qwen3 base model in a multi-game scenario based on the self-play reinforcement learning framework SPIRAL. It demonstrates advanced reasoning strategies in two-player zero-sum text games and performs excellently in mathematical and general reasoning benchmark tests.

Natural Language ProcessingTransformers

InternVL3-38B-Instruct is an advanced Multimodal Large Language Model (MLLM) that demonstrates exceptional overall performance, with strong multimodal perception and reasoning capabilities.

MultimodalTransformersmultilingual

InternVL3-8B-Instruct is an advanced multimodal large language model (MLLM) that demonstrates exceptional overall performance, with strong multimodal perception and reasoning capabilities.

MultimodalTransformersmultilingual

InternVL3-14B-Instruct is an advanced Multimodal Large Language Model (MLLM) that demonstrates exceptional multimodal perception and reasoning capabilities, supporting various tasks such as tool usage, GUI agents, industrial image analysis, and 3D visual perception.

MultimodalTransformersmultilingual

InternVL3-14B is an advanced multimodal large language model that significantly improves multimodal perception and reasoning capabilities on the basis of InternVL 2.5 and expands applications in areas such as tool use, GUI agents, industrial image analysis, and 3D visual perception.

MultimodalTransformersOther

InternVL3 is an advanced multimodal large language model series, demonstrating exceptional overall performance with robust multimodal perception and reasoning capabilities.

MultimodalTransformersmultilingual

InternVL3 - 8B is an advanced multimodal large - language model with excellent multimodal perception and reasoning capabilities, capable of processing multimodal data such as images and videos.

MultimodalTransformersmultilingual

InternVL3 - 2B is an advanced multimodal large language model with powerful multimodal perception, reasoning, and language processing capabilities. It is widely used in multiple fields such as image analysis and tool usage.

MultimodalTransformersOther