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Get all the details on Whisper, an AI model from OpenAI. This page covers its token limits, pricing structure, key capabilities such as speech_recognition, multilingual_speech_recognition, speech_translation, available API code samples, and performance strengths.
Key Metrics
Input Limit
No data tokens
Output Limit
No data tokens
Input Cost
N/A/1M
Output Cost
N/A/1M
Sample API Code
import openai
client = openai.OpenAI()
audio_file = open("/path/to/audio.mp3", "rb")
transcript = client.audio.transcriptions.create(
model="whisper-1",
file=audio_file
)
print(transcript.text)Required Libraries
openai
openai
Notes
Whisper is a general-purpose speech recognition model, trained on a large dataset of diverse audio. It can also be used as a multitask model to perform multilingual speech recognition, speech translation, and language identification.
Supported Data Types
Input Types
audio
Output Types
text
Strengths & Weaknesses
Exceptional at
speech recognition
multilingual speech recognition
speech translation
language identification
Additional Information
Latest Update
May 22, 2025
Knowledge Cutoff
No data