multimodal

MiniCPM-o 2.6 is the latest and most powerful model in the MiniCPM-o series. The model is built based on SigLip-400M, Whisper-medium-300M, ChatTTS-200M and Qwen2.5-7B and has 8B parameters. It performs well in visual understanding, voice interaction and multi-modal live broadcast, supporting real-time voice dialogue and multi-modal live broadcast functions. This model has performed well in the open source community, surpassing several well-known models. Its advantages lie in efficient inference speed, low latency, low memory and power consumption, and it can efficiently support multi-modal live broadcast on terminal devices such as iPad. In addition, MiniCPM-o 2.6 is easy to use and supports multiple usage methods, including CPU inference of llama.cpp, quantization models in int4 and GGUF formats, high-throughput inference of vLLM, etc.

Valley is a multi-modal large-scale model (MLLM) developed by ByteDance and is designed to handle a variety of tasks involving text, image and video data. The model achieved the best results in internal e-commerce and short video benchmarks, far outperforming other open source models, and demonstrated excellent performance on the OpenCompass multimodal model evaluation rankings, with an average score of 67.40, ranking among the top two among known open source MLLMs (<10B).