Gladia vs Whisper

Gladia provides audio infrastructure through an API for recording, transcribing, and enriching audio. It offers asynchronous and real-time transcription, including live streaming, with Starter supporting 100+ languages and automatic language detection and switching. Listed audio tools include speaker diarization, sentiment analysis, PII redaction, entity detection, and audio-to-LLM processing. Developers can use Python or Node.js SDKs, WebSocket streaming, or REST uploads; named integrations include Pipecat, LiveKit, Twilio, Retell, Zapier, Make, and n8n. Transcripts can include speaker labels and timestamps, and SRT and VTT are listed export formats. Starter is listed at free and includes 50€ in one-time credits that do not expire. Flexible pay-as-you-go Starter rates are $0.61 a month for asynchronous transcription and $0.75 a month for real-time transcription. Hourly call and total audio limits vary by tier. Gladia also offers GladiaFlow, a desktop voice dictation app for Mac and Windows; its code is available under the MIT license.

Whisper is an open-source speech recognition model for transcription, speech translation, language identification, and voice activity detection. Its documented command-line and Python interfaces process audio files, and it can translate speech from multiple languages into English. The repository lists six model sizes—tiny, base, small, medium, large, and turbo—with different speed and memory tradeoffs; stated VRAM needs range from about 1 GB to 10 GB, depending on size. Installation is documented through pip and requires the ffmpeg command-line tool. Rust may be needed if a prebuilt tiktoken wheel is unavailable. The code and model weights are released under the MIT License, with local installation using Python and ffmpeg. Whisper is listed for Linux, macOS, Windows, and self-hosted deployment. OpenAI says it was trained on 680,000 hours of multilingual and multitask supervised data collected from the web. Performance varies widely by language, and it does not outperform models specialized for LibriSpeech. Turbo is not trained for translation; multilingual models are recommended for translating non-English speech into English.