LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.
Latest Updates: In addition to the original formula, we have further enhanced Qwen2.5-VL-32B's mathematical and problem-solving abilities through reinforcement learning. This has also significantly improved the model's subjective user experience, with response styles adjusted to…
This repository contains an FP8 quantized version of the Qwen3-VL-8B-Instruct model. The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original BF16 model. Enjoy!
In the past five months since Qwen2-VL’s release, numerous developers have built new models on the Qwen2-VL vision-language models, providing us with valuable feedback. During this period, we focused on building more useful vision-language models. Today, we are excited to introdu…
We're excited to unveil Qwen2-VL , the latest iteration of our Qwen-VL model, representing nearly a year of innovation.
Welcome the Era of One-shot Long-horizon Parsing.
We're excited to unveil Qwen2-VL , the latest iteration of our Qwen-VL model, representing nearly a year of innovation.
SmolVLM2-500M-Video is a lightweight multimodal model designed to analyze video content. The model processes videos, images, and text inputs to generate text outputs - whether answering questions about media files, comparing visual content, or transcribing text from images. Despi…
HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better
Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.