NVIDIAParakeet TDT 0.6B V3
NVIDIA's Parakeet Tdt 0.6B V 3 is a multilingual automatic speech recognition model designed for high-throughput speech-to-text transcription, exceling at transcribing audio in 25 European languages with automatic language detection and punctuation. It is notable for its ability to transcribe long audio, supporting audio up to 24 minutes long with full attention.
Input
Output
Context
448
Max Output
-
Parameters
627.1M
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Resources & Links
Estimated GPU requirements for Parakeet TDT 0.6B V3
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Parakeet TDT 0.6B V3
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Parakeet TDT 0.6B V3 advertises a context window of 448 tokens. The figure is the creator's published maximum; a given provider may serve less, and the gateway routes on what each provider actually serves.
Yes. Parakeet TDT 0.6B V3 is an open-weight model released under the Cc by 4.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Parakeet TDT 0.6B V3 accepts Audio and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Parakeet TDT 0.6B V3 is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Yes. Parakeet TDT 0.6B V3 is served on the managed pool through the OpenAI-compatible endpoint as nvidia-parakeet-tdt-0-6b-v3, pinned by name or chosen by routing when it is the best fit for a request. The Try in Playground button opens it directly.
About 1.0 GB at INT8 for the weights and a default context, from the catalog's 627.1M parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Oct 15, 2026
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