WhisperX provides speech recognition with word-level timestamps and speaker diarization, according to its project description.
Open source
24 alternativesWhisper
OpenAI Whisper is a general-purpose speech-recognition model trained with large-scale weak supervision.
About Whisper
Whisper is an open-source, general-purpose speech recognition model published as a GitHub repository by OpenAI. It is a Transformer sequence-to-sequence model trained on a large dataset of diverse audio, and it performs multilingual speech recognition, speech translation, spoken language identification and voice activity detection as a single multitasking model rather than a multi-stage pipeline.
Key features
- Handles multilingual speech recognition, speech translation, language identification and voice activity detection
- Offers six model sizes: tiny, base, small, medium, large and turbo
- Provides English-only .en variants for tiny, base, small and medium
- Lists approximate VRAM needs from ~1 GB to ~10 GB by model
- Installable with pip as openai-whisper; ffmpeg required separately
- Turbo is an optimized version of large-v3 with faster transcription speed
Best for: Developers and researchers who want to install and run an open-source speech recognition model locally.
Good for
- Open-source codebase with published models and model card
- One model covers several speech tasks that would otherwise need separate stages
- Multiple model sizes let users trade off speed, accuracy and memory use
Watch out for
- Setup requires Python 3.8-3.11, PyTorch and the ffmpeg command-line tool
- Performance varies widely depending on the language
- The large model needs roughly 10 GB of VRAM
Whisper at a glance
- Website
- github.com/openai/whisper
- Category
- Online Tools › Text Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
Whisper alternatives
Tools and sites you could use instead, ranked by how closely they match.
LilySpeech lets Windows users dictate emails and documents with speech-to-text voice recognition.
TalkTyper provides browser-based speech-to-text dictation, with language options including English, French, German, and Spanish.
Voice Notepad converts speech to text in a browser and lets users copy, save, publish, or email dictated content.
VoiceToText transcribes speech online for writing emails and documents, according to its page.
Buzz transcribes and translates audio offline on a personal computer, using Whisper models according to its project description.
Open source
24 alternativesPopular in Text Tools
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Whisper FAQ
What tasks can Whisper perform?
It performs multilingual speech recognition, speech translation, spoken language identification and voice activity detection.
What is needed to install and run Whisper?
The codebase uses Python 3.9.9 and PyTorch 1.10.1 for training and testing and is expected to work with Python 3.8-3.11 and recent PyTorch versions. It also requires the ffmpeg command-line tool, and Rust may be needed if tiktoken has no pre-built wheel for the platform.
How much memory do the different model sizes require?
Approximate VRAM requirements are ~1 GB each for tiny and base, ~2 GB for small, ~5 GB for medium, ~10 GB for large and ~6 GB for turbo.
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