Qwen3-VL-8B-Thinking is an 8-billion-parameter multimodal large language model developed by the Qwen team at Alibaba Cloud. It is designed for deep multimodal reasoning, supporting visual understanding, long context processing, and structured chain-of-thought generation, and performs excellently in complex reasoning tasks.

MultimodalMlx

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

PaDT Pro 3B is a multimodal large language model based on Qwen2.5VL-3B. It adopts a unified paradigm of decodable block tokens and can directly generate text and visual outputs, achieving advanced performance in multiple visual perception and understanding tasks.

MultimodalTransformersMultiple Languages

Ming-UniVision is a large multimodal language model that first integrates continuous visual representations into the next-token prediction framework, unifying vision and language under a single autoregressive paradigm without discrete quantization or modality-specific heads. This model supports joint image understanding and generation, converges faster in vision-language training, and also supports multi-round context visual tasks.

MultimodalTransformersMultiple Languages

UniPixel-3B is a unified multimodal large language model for pixel-level vision-language understanding, which can flexibly support various fine-grained tasks, including image/video segmentation, region understanding, and the novel PixelQA task. The model jointly requires object-centric reference, segmentation, and question answering in videos, achieving pixel-level visual reasoning capabilities.

MultimodalSafetensors

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

Step-Audio 2 is an end-to-end multimodal large language model designed to meet the industry-level audio understanding and voice dialogue needs. It has advanced voice and audio understanding capabilities, intelligent voice dialogue functions, tool invocation, and multimodal retrieval enhanced generation capabilities, and has achieved leading performance in multiple audio understanding and dialogue benchmark tests.

MultimodalTransformers

Kuaishou Keye-VL is a cutting - edge multimodal large language model developed by the Kuaishou Keye team, which performs excellently in video understanding, visual perception, and reasoning tasks. The 1.5 version reaches a new height in video understanding, image perception, and reasoning ability through innovative fast - slow video encoding strategies, LongCoT cold - start data pipelines, and reinforcement learning training strategies, and supports an extended context length of up to 128k tokens.

MultimodalSafetensorsMultiple Languages

This model is the GGUF quantized version of Qwen2.5-Omni-7B, converted from the original model using the llama.cpp tool. Qwen2.5-Omni-7B is a 7-billion-parameter multimodal large language model that supports input and output in multiple modalities such as text, images, and audio.

MultimodalTransformersEnglish

Gemma 3 is a lightweight open-source multimodal model family launched by Google, capable of processing text and image inputs and generating text outputs. It has a 128K large context window, supports over 140 languages, and is suitable for various tasks such as text generation and image understanding.

MultimodalTransformers

Gemma 3 is a lightweight and state-of-the-art multimodal open model family launched by Google, built on the same research and technology as the Gemini model. This model can handle text and image inputs and generate text outputs. It has a large context window of 128K and supports over 140 languages, offering various sizes ranging from 270M to 27B.

MultimodalTransformers

Gemma 3 is a lightweight, state-of-the-art multimodal open model family launched by Google. It can handle text and image inputs and generate text outputs. It has a 128K large context window, supports over 140 languages, and offers a variety of scale options from 270M to 27B, suitable for various text generation and image understanding tasks.

MultimodalTransformers

Ultravox is a large multimodal speech language model capable of understanding and processing speech input, supporting multiple languages and noisy environments.

MultimodalTransformersMultiple Languages

Ultravox is a multimodal large speech language model that can process both speech and text inputs simultaneously, providing strong support for speech interaction scenarios.

MultimodalTransformersMultiple Languages

The Lingshu-32B GGUF model is a multimodal large language model suitable for the medical field. It supports multiple medical image modalities and performs excellently in medical Q&A and report generation tasks.

MultimodalTransformers

Ultravox is a multimodal large speech language model that combines a pre-trained large language model and a speech encoder. It can understand and process speech input and supports functions such as multilingual speech recognition, translation, and audio analysis.

MultimodalTransformersMultiple Languages

Lingshu is a SOTA multimodal large language model in the medical field, performing excellently in medical visual Q&A and report generation tasks.

MultimodalTransformers

Lingshu is a multimodal large language model that performs excellently in the medical field. It can effectively process medical image and text information and demonstrates top - notch performance in medical Q&A and report generation tasks.

MultimodalTransformers

This is a multimodal large language model quantized with A8W8, based on Qwen2.5-VL-7B-Instruct, supporting vision and language tasks.

MultimodalTransformers

LLaDA-V is a vision-language model based on the diffusion model, outperforming other diffusion multimodal large language models in performance.

MultimodalSafetensors