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NVIDIA: Parakeet TDT 0.6B v3

nvidia/parakeet-tdt-0.6b-v3

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Parakeet TDT 0.6B v3 is NVIDIA's 600M-parameter multilingual speech-to-text model built on the FastConformer-TDT architecture. Trained on the Granary dataset (670,000+ hours of audio), it supports automatic language detection across all official EU languages and achieves a 6.34% average word error rate on the HuggingFace Open ASR Leaderboard. Returns transcribed text with punctuation and segment timestamps.

Modalities

Price

$0.0015per minute

Released

May 27, 2026

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API

Sample code and API for Parakeet TDT 0.6B v3

OpenRouter normalizes requests and responses across providers for you.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

2

Make your first request

Use nvidia/parakeet-tdt-0.6b-v3 with the OpenRouter API:

OpenRouter provides a speech-to-text API that transcribes audio into text. Send base64-encoded audio with a model, and receive the transcribed text in JSON.

The generation ID is returned in the X-Generation-Id response header for tracking.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

Endpoint

POSThttps://openrouter.ai/api/v1/audio/transcriptions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelnvidia/parakeet-tdt-0.6b-v3

Parameters

NameTypeDefaultDescription
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penaltyfloat0This setting aims to control the repetition of tokens based on how often they appear in the input.
presence_penaltyfloat0Adjusts how often the model repeats specific tokens already used in the input.
top_kinteger0This limits the model's choice of tokens at each step, making it choose from a smaller set.
repetition_penaltyfloat1Helps to reduce the repetition of tokens from the input.
logit_biasmap—Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100.
min_pfloat0Represents the minimum probability for a token to be considered, relative to the probability of the most likely token.