Whisper
Whisper is a general-purpose speech recognition model, trained on a large dataset of diverse audio. It is a multitask model that handles multilingual speech recognition, translation and language identification. It serves the transcription and translation endpoints of the Audio API, and it is the one transcription model that takes audio alone, with no text prompt.
The real OpenAI model
Same weights, same API, same answers. We change only how you pay for it: one key for every maker, one bill, no separate account to open. Every figure on this page comes from OpenAI’s own page — check it.
Maker's own pagePrice
input / output · per minute
OpenAI
Official price
Modalities
How it is served
Requests are retried automatically if a provider is unavailable.
Similar models
Models built for the same kind of work, at a similar price.
We do not mark up the price of tokens. It is the same price the maker charges.
Use it from your code
from openai import OpenAI
# Works with the official openai package (pip install openai)
client = OpenAI(
base_url="https://api.flintbeam.com/v1",
api_key="sk-live-your-api-key"
)
response = client.chat.completions.create(
model="openai/whisper-1",
messages=[
{"role": "system", "content": "You are an experienced software engineer."},
{"role": "user", "content": "Describe the architecture of a distributed cache."}
],
temperature=0.7,
max_tokens=1500
)
print(response.choices[0].message.content)