LLM Models · Multimodal
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
A Pocket-Sized MLLM for Ultra-Efficient Image and Video Understanding on Your Phone
This repository hosts the GPTQ (W4A16, GPTQModel) quantized version of MiniCPM-V 4.6 Thinking. For the original BF16 weights and the full model card, please refer to openbmb/MiniCPM-V-4.6-Thinking.
A GPT-4V Level MLLM for Single Image, Multi Image and Video on Your Phone
This repository hosts the bitsandbytes (NF4, 4-bit) quantized version of MiniCPM-V 4.6. For the original BF16 weights and the full model card, please refer to openbmb/MiniCPM-V-4.6.
This repository hosts the GPTQ (W4A16, GPTQModel) quantized version of MiniCPM-V 4.6. For the original BF16 weights and the full model card, please refer to openbmb/MiniCPM-V-4.6.
Molmo is a family of open vision-language models developed by the Allen Institute for AI. Molmo models are trained on PixMo, a dataset of 1 million, highly-curated image-text pairs. It has state-of-the-art performance among multimodal models with a similar size while being fully…
Molmo2 is a family of open vision-language models developed by the Allen Institute for AI (Ai2) that support image, video and multi-image understanding and grounding. Molmo2 models are trained on publicly available third party datasets as referenced in our technical report and Mo…
LFM2.5‑VL-1.6B is Liquid AI's refreshed version of the first vision-language model, LFM2-VL-1.6B, built on an updated backbone LFM2.5-1.2B-Base and tuned for stronger real-world performance. Find more about LFM2.5 family of models in our blog post.
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
A Pocket-Sized MLLM for Ultra-Efficient Image and Video Understanding on Your Phone