OpenAI / openai.com
OpenAI's open source speech recognition model with broad language support and strong accuracy, widely used in applications and self-hosted deployments.
Free plan
Yes
API access
Yes
Open source
Yes
Platforms
4
Whisper is OpenAI's open source automatic speech recognition (ASR) model, released in September 2022, and it quickly established itself as one of the most capable and widely deployed speech recognition systems available. Its combination of strong accuracy, broad language support, and open source availability has made it a foundational component in many AI applications, transcription services, and developer projects.
The model was trained on 680,000 hours of multilingual audio from the internet, which produced exceptional breadth across languages, accents, and audio conditions. Whisper handles accented speech, background noise, and technical vocabulary significantly better than many specialised commercial transcription services, particularly for languages outside the major Western European group.
Whisper comes in multiple model sizes: tiny, base, small, medium, large, and the more recent turbo variants. Smaller models run faster on consumer hardware with lower accuracy; larger models produce better transcription at higher computational cost. The large-v3 model is the most accurate and is used in most production applications where quality matters.
For developers, Whisper represents a free, high-quality alternative to commercial speech APIs like Google Speech-to-Text or AWS Transcribe. Self-hosted deployment keeps audio data on the developer's own infrastructure without paying per-minute API fees, which is a significant cost advantage for high-volume transcription workloads.
Whisper runs as speech-to-text software built around audio and text workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on python, docker, and web (via third-party), with API access for teams that want to embed it into their own products.
The capabilities that matter most for teams evaluating Whisper.
Recognises and transcribes speech in 99 languages from audio files with strong robustness to accents and background noise.
Choose from tiny to large model variants trading off speed and accuracy based on available hardware and use case requirements.
Can transcribe audio in another language and simultaneously translate to English, useful for multilingual content workflows.
Open source model weights free to download and self-host. Accessible via OpenAI API at $0.006/minute of audio. Available through many third-party platforms.
Model
Open Source
Starting price
Free
Free trial
No
Otter.ai and Fathom provide consumer-friendly meeting transcription experiences. Rev.ai provides enterprise transcription API with strong accuracy and HIPAA support. Google Speech-to-Text and AWS Transcribe are competing commercial APIs.
A side-by-side look at the closest alternative in this category.
Key facts about model providers, platforms, and team support.
Model Provider
OpenAI
Models
Whisper large-v3, Whisper turbo, Whisper small
Platforms
Python, Docker, Web (via third-party), API
Deployment
Open Source, SaaS (OpenAI API)
Integrations
Groq (fast inference), Replicate, Hugging Face, OpenAI API
Team Collaboration
No
Launch Year
2022
Compliance signals and data-handling notes as reported by the vendor.
Self-hosted: complete data privacy with no cloud upload. OpenAI API: review OpenAI's data handling policy for audio files. Third-party hosting: review each provider's terms.
Editorial Verdict
Whisper is the best choice for developers who need high-quality multilingual transcription and want open source flexibility or cost-effective API access. For consumer meeting transcription, Otter.ai and Fathom provide better user experiences.
Last verified July 24, 2026.
Whisper is accessible through the OpenAI API at $0.006 per minute for users who do not want to manage their own deployment. Many third-party platforms including Groq (which runs Whisper at very high speed) and Replicate also provide hosted Whisper access.
Limitations include real-time performance, which is challenging with larger models, and word-level timestamps that require additional tooling on some model versions. For very low-latency real-time transcription, purpose-built streaming systems may perform better.
Open source model weights free to download and self-host. Accessible via OpenAI API at $0.006/minute of audio. Available through many third-party platforms.
Free trial with 300 minutes of transcription. Usage-based at $0.02/minute for async transcription. $0.021/minute for streaming. Custom enterprise pricing.
Self-hosted: complete data privacy with no cloud upload. OpenAI API: review OpenAI's data handling policy for audio files. Third-party hosting: review each provider's terms.
Enterprise includes HIPAA Business Associate Agreements. SOC 2 Type II certified. GDPR compliant.
Self-hosted Whisper keeps all audio on your own infrastructure. OpenAI API processes audio through OpenAI's servers. Review privacy settings if using for sensitive recordings.
Review Rev.ai's data handling policy. Audio submitted for transcription is processed by Rev.ai's infrastructure. Enterprise includes BAA for HIPAA compliance.
Self-hosted Whisper keeps all audio on your own infrastructure. OpenAI API processes audio through OpenAI's servers. Review privacy settings if using for sensitive recordings.
Verified reviews from signed-in users, stored in the backend and averaged into this tool's rating.
Sign in to rate Whisper and leave a review.
No other reviews yet — be the first to share how this tool performs in practice.
