Whisper is OpenAI's open-source speech recognition model that approaches human-level accuracy. Transcribe and translate audio in 99 languages. Robust to accents, background noise, and technical language. Run locally for privacy or use OpenAI's API for convenience. Multiple model sizes balance accuracy and speed. The speech recognition model that finally makes transcription reliable enough to trust.

Louis Corneloup Updated May 26, 2026 · how we evaluate Source openai.com ↗

Ratings Across the Web

2.6 (577 reviews)

Whisper holds an aggregate rating of 2.6 out of 5 from 577 reviews across Trustpilot and G2, last checked September 17, 2026.

Trustpilot 525 reviews

1.6/5

G2 52 reviews

4.3/5

Ratings aggregated from independent review platforms. Learn more

Key Features

Speech recognition
Transcription
Translation
Multi-language
Open source
Local deployment

Pricing Plans

Pricing checked Sep 29, 2026

Whisper plans and prices, checked September 2026
Plan	Price	Details
Open Source (Self-Hosted)	$0	MIT licensed 99 languages Local processing +2 more Show less Unlimited transcription No API costs
API	$0.006/minute	$0.006/min ($0.36/hour) Fast processing No GPU needed +1 more Show less OpenAI hosted

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Is Whisper worth the price?

Great value

Whisper's pricing is incredibly generous, especially with its robust open-source option.

The API at $0.006/minute is competitive, offering a cost-effective solution for those needing hosted processing. This structure is best for a wide range of users, from developers to enterprises, seeking flexible and affordable speech-to-text.

Full Whisper pricing: every plan, hidden costs and alternatives

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2.6/5

Across 577 verified user reviews on Trustpilot, G2

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AssemblyAI Paid

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Still deciding?

Most buyers shortlist 2 or 3 tools before committing. Pull a side-by-side comparison or browse the full alternatives shortlist below.

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Whisper FAQ

How does Whisper handle diverse audio inputs?

Whisper is designed to be robust to various audio challenges, including different accents, background noise, and technical language. It can transcribe and translate audio in 99 languages, approaching human-level accuracy.

Which teams would benefit most from using Whisper?

Teams requiring highly accurate transcription and translation for audio content, such as those developing AI Assistants or needing to process multilingual communications, would find Whisper particularly useful. Its open-source nature also suits teams with strong privacy requirements or those who prefer self-hosting solutions.

Can Whisper be used for real-time transcription?

While Whisper offers excellent speech recognition, its real-time capabilities are limited due to its resource-intensive nature. Users may experience setup complexity and hardware requirements when attempting real-time applications.

How is Whisper priced?

Whisper is free to use as an open-source speech recognition model, meaning there is no paid plan required to access its core functionalities. Users can run it locally for privacy or utilize OpenAI's API for convenience, which may have its own associated costs.

What kind of hardware is needed to run Whisper locally?

Running Whisper locally requires specific hardware due to its resource-intensive nature. Users should anticipate needing sufficient computing power to handle the model effectively, especially for larger model sizes that balance accuracy and speed.

How does Whisper compare to AssemblyAI for transcription accuracy?

Whisper is an open-source speech recognition model from OpenAI that approaches human-level accuracy for transcription and translation across 99 languages. It is known for its robustness to accents, background noise, and technical language, offering a reliable alternative to services like AssemblyAI.

Does Whisper support multiple model sizes?

Yes, Whisper offers multiple model sizes, allowing users to balance accuracy with speed based on their specific needs. This flexibility enables optimization for different applications and computational environments.

Source: openai.com

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