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探索 AI 模型 1050
parakeet-ctc-1.1b
NVIDIA`parakeet-ctc-1.1b` is an ASR model that transcribes speech in lower case English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is an XXL version of FastConformer CTC [1] (around 1.1B parameters) model. See the model architecture section and NeMo documentation for complete architecture details. To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest PyTorch version. See the NeMo-Speech.cpp documentation for more details.
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查看详情 ↗parakeet-rnnt-0.6b
NVIDIA`parakeet-rnnt-0.6b` is an ASR model that transcribes speech in lower case English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is an XL version of FastConformer Transducer [1] (around 600M parameters) model. See the model architecture section and NeMo documentation for complete architecture details. License to use this model is covered by the CC-BY-4.0. By downloading the public and release version of the model, you accept the terms and conditions of the CC-BY-4.0 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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查看详情 ↗parakeet-rnnt-1.1b
NVIDIA`parakeet-rnnt-1.1b` is an ASR model that transcribes speech in lower case English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is an XXL version of FastConformer Transducer [1] (around 1.1B parameters) model. See the model architecture section and NeMo documentation for complete architecture details. 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. The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
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查看详情 ↗parakeet-rnnt-110m-da-dk
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查看详情 ↗parakeet-tdt-0.6b-v2
NVIDIA> **🎉 NEW: Multilingual Parakeet TDT 0.6B V3 is now available!** > 🌍 **25 European Languages** | 🚀 **Enhanced Performance** | 🔗 **Try it here: nvidia/parakeet-tdt-0.6b-v3** `parakeet-tdt-0.6b-v2` is a 600-million-parameter automatic speech recognition (ASR) model designed for high-quality English transcription, featuring support for punctuation, capitalization, and accurate timestamp prediction. Try Demo here: https://huggingface.co/spaces/nvidia/parakeet-tdt-0.6b-v2 This XL variant of the FastConformer [1] architecture integrates the TDT [2] decoder and is trained with full attention, enabling efficient transcription of audio segments up to 24 minutes in a single pass. The model achieves an RTFx of 3380 on the HF-Open-ASR leaderboard with a batch size of 128. Note: *RTFx Performance may vary depending on dataset audio duration and batch size.*
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查看详情 ↗parakeet-tdt-0.6b-v3
NVIDIA`parakeet-tdt-0.6b-v3` is a 600-million-parameter multilingual automatic speech recognition (ASR) model designed for high-throughput speech-to-text transcription. It extends the parakeet-tdt-0.6b-v2 model by expanding language support from English to 25 European languages. The model automatically detects the language of the audio and transcribes it without requiring additional prompting. It is part of a series of models that leverage the Granary [1, 2] multilingual corpus as their primary training dataset. **Supported Languages:** Bulgarian (**bg**), Croatian (**hr**), Czech (**cs**), Danish (**da**), Dutch (**nl**), English (**en**), Estonian (**et**), Finnish (**fi**), French (**fr**), German (**de**), Greek (**el**), Hungarian (**hu**), Italian (**it**), Latvian (**lv**), Lithuanian (**lt**), Maltese (**mt**), Polish (**pl**), Portuguese (**pt**), Romanian (**ro**), Slovak (**sk**), Slovenian (**sl**), Spanish (**es**), Swedish (**sv**), Russian (**ru**), Ukrainian (**uk**) `parakeet-tdt-0.6b-v3`'s key features are built on the foundation of its predecessor, parakeet-tdt-0.6b-v2, and include:
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查看详情 ↗parakeet-tdt-1.1b
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查看详情 ↗parakeet-tdt_ctc-0.6b-ja
NVIDIA`parakeet-tdt_ctc-0.6b-ja` is an ASR model that transcribes Japanese speech with Punctuations. This model is developed by NVIDIA NeMo team. It is an XL version of Hybrid FastConformer [1] TDT-CTC [2] (around 0.6B parameters) model. See the model architecture section and NeMo documentation for complete architecture details. To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest PyTorch version. The model is available for use in the NeMo Framework [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
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查看详情 ↗parakeet-tdt_ctc-1.1b
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查看详情 ↗parakeet-tdt_ctc-110m
NVIDIA`parakeet-tdt_ctc-110m` is an ASR model that transcribes speech with Punctuations and Capitalizations of the English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is a Large version of Hybrid FastConformer [1] TDT-CTC [2] (around 114M parameters) model. This model has been trained with fastconformer architecture with full attention hence this model can transcribe up to 20 minutes of audio in one single pass. This model achieves super fast RTFx values across all datasets, with an average RTFx of ~5300 on Hugging Face leaderboard evaluation sets on A100. See the model architecture section and NeMo documentation for complete architecture details. To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest PyTorch version. The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
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查看详情 ↗parakeet-unified-en-0.6b
NVIDIAParakeet-unified-en-0.6b is an English automatic speech recognition (ASR) model based on transducer architecture (RNN-T) combining both offline and streaming inference (with a minimum latency of 160ms) in one model [1]. It is trained mostly on the English part of the Granary dataset [4], which contains approximately 250,000 hours of US English (en-US) speech across diverse acoustic conditions. The model transcribes speech to English alphabet, spaces, and apostrophes with punctuation and captalization support. Average WER comparison on the HF ASR Leaderboard datasets including offline and streaming inference with different latency values. This model consists of a 🦜 Parakeet (FastConformer) encoder (jointly trained in offline and streaming modes) with an RNN-T decoder. It is designed for offline and streaming speech-to-text applications where latency can be as low as 160ms, such as voice assistants, live captioning, and conversational AI systems. The current inference pipeline supports only buffered streaming (left context is recomputed for each chunk) that can be longer than cache-aware streaming.
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查看详情 ↗暂未找到匹配模型
可以调整厂商、分类或输入输出条件；新模型正持续收录。
COST EXPLORER
好模型，也要算好成本。
调整月度 Token 用量，直观比较不同模型的预估 API 开支。
1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价
仅比较同一渠道的基础文本 Token 报价
使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照；不计缓存优惠、阶梯价、推理额外输出与税费，请以来源的当前报价为准。
MODEL HANDBOOK
读懂模型，再做选择
API 价格应该怎么比较？+
先区分输入、输出和缓存价格，再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费，不能直接与 Token 单价比较。
开放权重，就代表可以免费商用吗？+
不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。
排行榜第一，就是最适合我的模型吗？+
榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本，再选择模型。