Turn audio or video into accurate text

+ Free, runs fully offline, and remains the accuracy benchmark that most commercial transcription services are measured against.
− No speaker diarization out of the box, it hallucinates text during silence, and large models are slow without a GPU.

+ Strong accuracy plus built-in audio intelligence (speaker labels, chapters, PII redaction) and LeMUR for asking questions of a transcript.
− No consumer app, and per-hour pricing adds up on high volumes compared with self-hosted Whisper.

+ Among the fastest real-time transcription APIs available, with diarization and keyword boosting built in.
− Developer-only; there is no end-user app, and accuracy on heavily accented speech trails Whisper-class models.

+ Deep integration list (Salesforce, HubSpot, Slack, Notion) and searchable transcripts across every past meeting.
− Speaker labeling and accuracy drop on noisy or accented audio, and the bot joining every calendar event by default surprises people.

+ Live transcript you can read during the call, with a generous free tier for individuals.
− The OtterPilot bot auto-joins meetings and emails attendees unless you turn it off, which annoys other participants.

+ The option to upgrade any file to a human transcript gives you a guaranteed-accuracy path for legal or published work.
− AI transcripts cost more per minute than pure-API rivals, and human turnaround can take hours to days.

+ Deleting a word from the transcript deletes it from the audio, and Studio Sound removes room echo and noise in one click.
− Studio Sound can make voices sound processed, and the desktop app is heavy on large projects.

+ Hits broadcast loudness targets and balances multiple speakers automatically, which saves manual mixing every episode.
− The interface is dated and the per-hour credit model is awkward for occasional users.