Capto Auto Subtitle Generator vs Whisper

Capto Auto Subtitle Generator creates editable, timestamped transcripts from uploaded videos using OpenAI Whisper. It automatically detects more than 100 spoken languages and can translate subtitles into 60+ languages. In its workspace, users can edit text and segment timestamps before exporting SRT, VTT, TXT, DOCX, or a burned-in MP4; the homepage also lists ASS. Optional multi-speaker diarization labels speakers and costs 1.5 credits per video minute. Accepted video formats are MP4, MOV, WebM, AVI, and MKV. Transcription costs 1 credit per minute, translation costs 0.2 credits per minute per language, and burned-in MP4 costs 2 credits per minute. The Free plan costs nothing and includes five minutes without a credit card. Essential costs $4 a month as a one-time purchase, with 120 credits that never expire and a 15-minute video limit. Creator and Pro are also one-time purchases at $9 a month and $17 a month, respectively. Growth costs $32 a month and auto-renews. Plans vary in credits, file size, video length, and concurrent exports or jobs. The privacy policy says source videos are deleted within 48 hours and extracted audio after transcription; audio or text may be processed by OpenAI, and optional diarization audio is sent to AssemblyAI.

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.