8 Best Jarvis Alternatives in 2026 (Open Source)
Jarvis — Jarvis AI Assistant - Voice-powered AI assistant for Mac. vs Wispr Flow ($10-24/month): 100% free, open-source, fully offline-capable voice dictation with zero telemetry
These 8 open-source tools do the same job. They are ordered by how closely they match Jarvis, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| Jarvis(original) | 643 | +29 | 2026-09-23 |
| Buzz | 21.8k | +535 | 2026-09-23 |
| WhisperS2T | 580 | +4 | 2024-08-25 |
| whisperX | 24.3k | +541 | 2026-09-26 |
| Insanely Fast Whisper | 13.1k | +209 | 2024-05-27 |
| RealChar | 6.2k | +1 | 2024-02-03 |
| agents | 14.4k | +1,370 | 2026-09-30 |
| Pipecat | 16.1k | +833 | 2026-09-30 |
| Ultravox | 4.6k | +31 | 2025-12-12 |
1. Buzz
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
What sets it apart: vs Whisper CLI: full GUI with live transcription, speaker ID, and watch folders; vs cloud transcription (AssemblyAI/Deepgram): completely offline with zero data leaving the device
Best for: Offline audio/video transcription with privacy; Live presentation captioning; Batch transcription of media files
2. WhisperS2T
An Optimized Speech-to-Text Pipeline for the Whisper Model Supporting Multiple Inference Engine
What sets it apart: vs WhisperX / HuggingFace Pipeline: 2.3-3X speed improvement through superior pipeline architecture (not just backend optimization) — with multiple inference backend choices and built-in hallucination reduction
Best for: High-volume speech transcription requiring speed optimization; Multilingual audio processing with backend flexibility; Applications needing reduced hallucination output from Whisper
3. whisperX
WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
What sets it apart: Adds word-level timestamps and speaker diarization on top of Whisper — solving the two biggest gaps in OpenAI's original model
Best for: Batch transcription with accurate word-level timestamps; Meeting transcription with speaker identification
4. Insanely Fast Whisper
What sets it apart: vs OpenAI Whisper CLI/faster-whisper: leverages HF Transformers + Flash Attention 2 + batching for up to 6x faster transcription than faster-whisper
Best for: Batch transcription of large audio archives; Teams needing fastest possible Whisper inference
5. RealChar
🎙️🤖Create, Customize and Talk to your AI Character/Companion in Realtime (All in One Codebase!). Have a natural seamless conversation with AI everywhere (mobile, web and terminal) using LLM OpenAI G
What sets it apart: vs Character.AI: fully open-source with voice cloning, multi-platform (web+iOS+phone), and pluggable LLM/TTS backends — own your AI characters
Best for: Building interactive AI character experiences with voice; Developers creating multi-platform conversational AI personas
6. agents
A framework for building realtime voice AI agents 🤖🎙️📹
What sets it apart: The leading open-source framework for realtime voice AI agents with WebRTC infrastructure, semantic turn detection, multi-agent handoff, and native telephony — vs alternatives that bolt voice onto text-first frameworks
Best for: Building production voice AI agents and assistants; Real-time conversational AI with telephony integration; Multi-agent voice workflows with handoffs
7. Pipecat
Open Source framework for voice and multimodal conversational AI
What sets it apart: Only production-grade framework for real-time voice AI with composable pipelines — supports 17+ STT and 20+ TTS providers with ultra-low latency, unlike text-focused agent frameworks
Best for: Building real-time voice AI agents and assistants; Multimodal conversational interfaces with audio, video, and text
8. Ultravox
A fast multimodal LLM for real-time voice
What sets it apart: vs ASR+LLM pipelines (Whisper+GPT): direct audio-to-embedding projection eliminates ASR latency bottleneck, enabling true real-time voice understanding
Best for: Real-time voice AI agents requiring sub-100ms latency; Custom domain voice applications with proprietary audio data