The MiMo Embodied Model (MiMo-Embodied) is a powerful cross-embodied vision-language model that has demonstrated excellent performance in both autonomous driving and embodied AI tasks. It is the first open-source vision-language model that combines these two key domains, significantly enhancing the understanding and reasoning abilities in dynamic physical environments.

MultimodalTransformers

MiMo Audio is an audio language model developed by Xiaomi, which demonstrates strong few-shot learning ability through large-scale pre-training. This model breaks through the limitations of traditional models that rely on fine-tuning for specific tasks and performs excellently in tasks such as speech intelligence and audio understanding, reaching an advanced level among open-source models.

Audio ProcessingSafetensors

MiMo Audio is an audio language model based on large-scale pre-training, achieving SOTA performance among open-source models in speech intelligence and audio understanding benchmark tests. This model demonstrates strong few-shot learning ability and can generalize to tasks not included in the training data, supporting various audio tasks such as speech conversion, style transfer, and speech editing.

Audio ProcessingSafetensors

This is a quantized version of XiaomiMiMo's MiMo-VL-7B-SFT-2508 model, optimized using llama.cpp to improve the model's running performance on specific hardware. This model is a vision-language model with 7 billion parameters, supporting image-to-text generation tasks.

MultimodalGguf

This is the GGUF quantized version of the Xiaomi MiMo-VL-7B-RL-2508 model, quantized using the imatrix option of llama.cpp. It supports multiple quantization levels and is suitable for different hardware configurations and performance requirements.

MultimodalGguf

This is the GGUF quantized version of the XiaomiMiMo/MiMo-VL-7B-RL-2508 model, using the Q6_K quantization level. This model is a multimodal visual language model with a scale of 7B parameters, supporting joint understanding and generation tasks of images and text.

MultimodalTransformers

MiMo-VL is a compact and powerful vision-language model that combines a native resolution ViT encoder, an MLP projector, and the MiMo-7B language model. It performs excellently in tasks such as multimodal reasoning. This model shows outstanding performance in multiple benchmark tests, has a chain-of-thought control function, and significantly improves the user experience.

MultimodalTransformers

MiMo-VL is a compact and powerful vision-language model that combines a native resolution ViT encoder, an MLP projector, and the MiMo-7B language model optimized for complex reasoning tasks. Through multi-stage pre-training and post-training, it has achieved excellent results in multiple vision-language tasks.

MultimodalTransformers

MiMo is a series of 7B parameter models trained from scratch for inference tasks. Through optimized pre-training and post-training strategies, it performs excellently in mathematical and code reasoning tasks.

Natural Language ProcessingTransformers

MiMo-7B is a language model series launched by Xiaomi, specifically designed for reasoning tasks, including base models, SFT models, and RL models, excelling in mathematical and code reasoning tasks.

Natural Language ProcessingTransformers

MiMo-7B-RL is a reinforcement learning model trained based on the MiMo-7B-SFT model, demonstrating outstanding performance in mathematical and code reasoning tasks, comparable to OpenAI o1-mini.

Natural Language ProcessingTransformers

A 7B-parameter specialized inference language model series launched by Xiaomi, significantly enhancing mathematical and code reasoning capabilities through optimized pre-training and post-training strategies

Natural Language ProcessingTransformers

MiMo-7B-RL is a reinforcement learning model trained based on the MiMo-7B-SFT model, achieving performance comparable to OpenAI o1-mini in mathematical and code reasoning tasks.

Natural Language ProcessingTransformers