Whisper Large V3 Turbo is an optimized version of OpenAI's Whisper Large V3 speech recognition model, designed for high-speed and cost-efficient transcription. It supports 99+ languages and accepts common audio formats including mp3, mp4, wav, webm, flac, and ogg. With a ~12% word error rate and real-time speed factors up to 216×, it delivers fast, scalable performance for latency-sensitive and high-throughput transcription workloads, making it ideal for real-time and large-scale speech processing applications.
Use the Apertis AI SDK, the OpenAI SDK, or make direct HTTP requests to our API.
from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="whisper-large-v3-turbo", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="whisper-large-v3-turbo",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )Common parameters: modelfilelanguagepromptresponse_format
Extended parameters: temperaturetimestamp_granularities
Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
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