Open-Source Otter.ai Alternative (2026, Free)

Listed models: pyannote speaker-diarization-community-1, Nemotron 3.5 Transcribe (NVIDIA 30B-A4B offline ASR/AST, OpenMDW-1.1; not Bolt/Super VL; compare vs Granite Speech 5.0), Granite Speech 5.0 (5.0-2B ASR/AST; speaker tags live on the 4.1-2B Plus sibling), Hy-SimulMT (Tencent Hunyuan 30B-A3B simultaneous Chinese–English speech MT; compare vs Granite Speech 5.0), and Hibiki-Zero (Kyutai 3B streaming S2ST, fr/es/pt/de→en; compare vs Hy-SimulMT). Related local STT engine: whisper.cpp on Descript alternatives. Related TTS (not meeting notes) is on ElevenLabs alternatives. Related video generation is on Runway alternatives. Chat models are on ChatGPT alternatives. Text MT: DeepL alternatives.

Sourced snapshot (2026-10-13)

Field	community-1
Hosts	huggingface.co/pyannote/speaker-diarization-community-1 (gated); github.com/pyannote/pyannote-audio
HF likes / downloads	2,840 / 5,444,861
GitHub stars / forks	10,638 / 1,117
Card license	CC-BY-4.0
Toolkit license	MIT
Output	speaker turns (start, stop, speaker_id)
Quality vs Otter	Not independently tested; Otter is not in the DER table

Why a diarization pipeline is on an Otter hub

Otter.ai sells a meeting agent: live notes, summaries, and related workspace features. Searchers still type “open source Otter alternative” when they want speaker-aware local audio. The open artifact we could fully source on 2026-10-13 without a gated README login is community-1: 2,840 likes, about 5.44 million HF downloads, CC-BY-4.0 on the card, created 2025-04-15. The installable toolkit is pyannote.audio (10,638 GitHub stars, MIT).

That is an honest, narrow substitute: who spoke when, on your machine, after you accept the gated card. It is not a drop-in Otter workspace.

What you actually run

ffmpeg, pip install pyannote.audio (or uv), a Hugging Face token, then Pipeline.from_pretrained("pyannote/speaker-diarization-community-1", token=...). The README prints start=… stop=… speaker_… lines. GPU is optional in the sense that .to(cuda) is shown when available. An H100 speed row in that README (31 seconds of compute per hour of AMI IHM audio) is upstream, not our stopwatch.

License split

Do not mix the two SPDX strings. The pipeline card is CC-BY-4.0. The toolkit repository is MIT. If you redistribute weights, start from the card. If you vendor the Python package, start from GitHub. Not legal advice.

What we left out

Whisper, faster-whisper, and other ASR stacks are the usual next hop if you need words rather than speaker ids. They are queued. precision-2 is a paid/hosted pyannoteAI line in the same README; it is mentioned so you do not confuse it with community-1, not as a listed open option.

How to choose

• Need local speaker turns and can accept a gated HF card: community-1.
• Need NVIDIA offline 30B-class ASR/AST (OpenMDW-1.1; not Bolt/Super VL): Nemotron 3.5 Transcribe — Nemotron 3.5 Transcribe vs Granite Speech 5.0.
• Need Apache-2.0 ASR/AST, or speaker tags on the Plus sibling: Granite Speech 5.0.
• Need live Chinese–English simultaneous speech-to-speech (not meeting notes): Hy-SimulMT — Hy-SimulMT vs Granite Speech 5.0.
• Need live French / Spanish / Portuguese / German → English speech-to-speech: Hibiki-Zero — Hibiki-Zero vs Hy-SimulMT. Weights are CC-BY-NC-SA-4.0.
• Need a Whisper-family local engine (no meeting UI): whisper.cpp.
• Need a chat LLM, not meeting audio: DeepSeek-V4.1-Flash or MiniMax M3.1 Flash via ChatGPT alternatives.
• Need video generation, not notes: LTX-2.5.

What “open” does not mean

community-1 is gated. You accept Hugging Face user conditions and pass a token. The toolkit README is public; the card README is not (HTTP 401 without access). CC-BY-4.0 on the card is not the same string as MIT on pyannote.audio. precision-2 is a server-side premium pipeline in the same README — useful so you do not paste the wrong from_pretrained id, not as a listed free local option.

Otter’s marketing screenshot on this hub identifies the commercial search (live transcription UI). pyannote’s official talk thumbnail on the model page identifies the toolkit. Neither image is a quality proof.

If you need words on a timeline, you still need ASR. This hub does not invent a Whisper row. If you need a chat bot that “was in the meeting,” you are in ChatGPT alternatives territory, not diarization. If you need to generate a video of a meeting that never happened, that is Runway alternatives — a different job.

Telemetry in pyannote.audio can be disabled with PYANNOTE_METRICS_ENABLED=0, per the README. That is optional library behavior, not an Otter privacy comparison.