C-RADIOv2-g
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C-RADIOv2-H
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View details ↗C-RADIOv2-L
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View details ↗C-RADIOv2-VLM-H
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View details ↗C-RADIOv2-VLM-H-RC3
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View details ↗C-RADIOv3-B
NVIDIAThis model performs visual feature extraction. For instance, RADIO generates image embeddings that can be used by a downstream model to classify images. C-RADIOv3 models are available in multiple sizes: * Base (90M parameters). * Large (320M parameters). * Huge (653M parameters). (In training) * Gigantic (1.1B parameters). C-RADIOv3 was trained for 1M steps (400k more steps than v1), using inverse frequency sampling for data balancing, and PHI Standardization for teacher distribution balancing. As well as new techniques for summary distribution matching, and domain generalization.
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View details ↗C-RADIOv3-g
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View details ↗C-RADIOv3-H
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View details ↗C-RADIOv3-L
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View details ↗C-RADIOv4-1D-H
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View details ↗C-RADIOv4-H
NVIDIAThis model performs visual feature extraction. For instance, RADIO generates image embeddings that can be used by a downstream model to classify images. C-RADIOv4 models are available in multiple sizes: * Shape-Optimized (431M parameters). * Huge (653M parameters). The embeddings generated by this model are expected to be used by a downstream application. For example:
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View details ↗C-RADIOv4-SO400M
NVIDIAThis model performs visual feature extraction. For instance, RADIO generates image embeddings that can be used by a downstream model to classify images. C-RADIOv4 models are available in multiple sizes: * Shape-Optimized (431M parameters). * Huge (653M parameters). The embeddings generated by this model are expected to be used by a downstream application. For example:
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View details ↗canary-180m-flash
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View details ↗canary-1b
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View details ↗canary-1b-flash
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View details ↗canary-1b-v2
NVIDIA**``Canary-1b-v2``** is a powerful 1-billion parameter model built for high-quality speech transcription and translation across 25 European languages. It excels at both automatic speech recognition (ASR) and speech translation (AST), supporting: * **Speech Transcription (ASR) for 25 languages** * **Speech Translation (AST) from English → 24 languages** * **Speech Translation (AST) from 24 languages → English**
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View details ↗canary-qwen-2.5b
NVIDIANVIDIA NeMo Canary-Qwen-2.5B is an English speech recognition model that achieves state-of-the art performance on multiple English speech benchmarks. With 2.5 billion parameters and running at 418 RTFx, Canary-Qwen-2.5B supports automatic speech-to-text recognition (ASR) in English with punctuation and capitalization (PnC). The model works in two modes: as a transcription tool (ASR mode) and as an LLM (LLM mode). In ASR mode, the model is only capable of transcribing the speech into text, but does not retain any LLM-specific skills such as reasoning. In LLM mode, the model retains all of the original LLM capabilities, which can be used to post-process the transcript, e.g. summarize it or answer questions about it. In LLM mode, the model does not "understand" the raw audio anymore - only its transcript. This model is ready for commercial use. Canary-Qwen-2.5B is released under the CC-BY-4.0 license. By using this model, you are agreeing to the terms and conditions of the license. For documentation, deployment guides, enterprise-ready APIs, and the latest open models—including Nemotron and other cutting-edge speech, translation, and generative AI—visit the NVIDIA Developer Portal at developer.nvidia.com. Join the community to access tools, support, and resources to accelerate your development with NVIDIA’s NeMo, Riva, NIM, and foundation models.
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View details ↗CARI4D
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View details ↗cari4d_commercial
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View details ↗cbottle
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