MambaVision-L2-512-21K
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MambaVision-L3-256-21K
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View details ↗MambaVision-L3-512-21K
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View details ↗MambaVision-S-1K
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View details ↗MambaVision-T-1K
NVIDIAWe have developed the first hybrid model for computer vision which leverages the strengths of Mamba and Transformers. Specifically, our core contribution includes redesigning the Mamba formulation to enhance its capability for efficient modeling of visual features. In addition, we conducted a comprehensive ablation study on the feasibility of integrating Vision Transformers (ViT) with Mamba. Our results demonstrate that equipping the Mamba architecture with several self-attention blocks at the final layers greatly improves the modeling capacity to capture long-range spatial dependencies. Based on our findings, we introduce a family of MambaVision models with a hierarchical architecture to meet various design criteria. MambaVision demonstrates a strong performance by achieving a new SOTA Pareto-front in terms of Top-1 accuracy and throughput. For each model, we offer two variants for image classification and feature extraction that can be imported with 1 line of code.
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View details ↗MambaVision-T2-1K
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View details ↗megatron-bert-cased-345m
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View details ↗megatron-gpt2-345m
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View details ↗mel-codec-22khz
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View details ↗mel-codec-44khz
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View details ↗Metatron-v1
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View details ↗MiniMax-M2.5-NVFP4
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View details ↗MiniMax-M2.7-DFlash
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View details ↗MiniMax-M2.7-NVFP4
NVIDIAMiniMax M2.7 is a large language model for complex software engineering, agentic tool use, and office productivity workflows. It is presented as a model deeply participating in its own evolution, with support for complex agent harnesses, dynamic tool search, Agent Teams, and high-fidelity coding and document-editing tasks. This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA MiniMax M2.7 Model Card **GOVERNING TERMS:** Use of this model is governed by the NVIDIA Software and Model Evaluation license.
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View details ↗MiniMax-M3-DSpark
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View details ↗MiniMax-M3-NVFP4
NVIDIAMiniMax-M3 is a multimodal model with frontier-level coding and agentic capabilities, built on a Mixture-of-Experts architecture with a 1M-token context window. The model processes text, image, video, and computer use inputs and produces text outputs, with emphasis on long-horizon coding tasks, agentic and tool-use workflows, and long-form video understanding. The NVIDIA MiniMax-M3 NVFP4 model is quantized with Model Optimizer. This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA MiniMax-M3 Model Card. **GOVERNING TERMS:** Use of the checkpoints is governed by the MiniMax Community License. **Additional Information:** Built with MiniMax M3.
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View details ↗Minitron-4B-Base
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View details ↗Minitron-8B-Base
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View details ↗Mistral Medium 3.5 128B is Mistral AI's first flagship merged model. It is a dense 128B model with a 256k context window, handling instruction-following, reasoning, and coding in a single set of weights. Mistral Medium 3.5 replaces its predecessor Mistral Medium 3.1 and Magistral in Le Chat. It also replaces Devstral 2 in our coding agent Vibe. Concretely, expect better performance for instruct, reasoning and coding tasks in a new unified model in comparison with our previous released models. The NVIDIA Mistral-Medium-3.5-128B NVFP4 model is quantized with Model Optimizer. This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA Mistral-Medium-3.5-128B Model Card **GOVERNING TERMS:** **GOVERNING TERMS:** Use of this model is governed by Mistral’s Modified MIT license. To deploy and customize the model in your environment, please contact Mistral[https://mistral.ai/contact/].
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View details ↗Mistral-NeMo-12B-Base
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