ElevenLabs vs Alexandria-audiobook
Alexandria-audiobook is the stronger fit for self-hosted, GPU-backed audiobook production when users need multi-voice narration, local TTS, voice cloning, line-level control, and audiobook/DAW exports. ElevenLabs remains the better choice for teams needing a broader managed audio platform—particularly transcription, cross-language dubbing, application APIs, music or sound-effect generation, and conversational agents—
Decision guide
The practical reasons to choose either option, based on documented capabilities.
Choose Alexandria-audiobook if
- Audiobook producers converting TXT, Markdown, or EPUB books into multi-character narration
- Creators who need per-line speaker, text, and delivery editing with selective regeneration
- Teams requiring self-hosted TTS, locally cached models, and direct control of voice and output files operation equipment allows for it hardware wise though resource intensive at least GPU 8 GB VRAM minimum, 16 GB+ recomm
Stay with ElevenLabs if
- You need documented speech-to-text transcription or speaker diarization
- You need multilingual dubbing that preserves the original performance across languages
- You need supported audio or agent APIs for embedding capabilities in applications Features no support for dedicated API exposed beyond web UI though OpenAI compatible backend requirements exist within the documentation,
Deployment and operations
Alexandria-audiobook is an MIT-licensed, self-hostable Python project. It supports Pinokio installation, Google Colab, and Docker Compose for NVIDIA GPU deployments; no Kubernetes support is documented. Local operation requires an OpenAI-compatible LLM server or cloud API connection. The documented baseline is 8 GB GPU VRAM, 8 GB RAM, and about 20 GB disk, with 16 GB+ VRAM and 16 GB RAM recommended. CPU mode is available but described as significantly slower. TTS model variants download on first
Migration considerations
Alexandria accepts .txt, .md, and .epub book files; EPUB content is converted to plain text. It exports combined MP3, separate per-line MP3 files, chaptered M4B, and an Audacity package with per-speaker WAV tracks, labels, and an LOF project file. No direct ElevenLabs project, voice, or configuration importer is documented, so migration would be file-based rather than project-compatible.
Feature fit
What Alexandria-audiobook covers
- Text-to-speech generation
- Multilingual speech synthesis
- Voice cloning
- Prompt-based voice design
- Line-level voice direction
- Browser-based editing
- Batch audio generation
What’s different or missing
- No documented speech transcription
- No documented multilingual dubbing workflow
- No documented public audio or agent APIs
- No documented conversational agents
- No documented agent testing or guardrails
- No documented music generation
- No documented sound-effect generation
Project snapshot
- GitHub stars
- 863
- Contributors
- 8
- Language
- Python
- Last commit
- Aug 2, 2026
- Latest release
- Mar 3, 2026
Categories: Audio Editing, Live Chat, Customer Support
Sources and editorial review11 linked sources
Public documentation supports this comparison. Automation assists collection and classification; editorial standards and corrections remain the responsibility of Kris.
AI-powered multi-voice audiobook generator — LLM script annotation, voice cloning, voice design, LoRA training, per-line style control, and export to MP3, chaptered M4B, or Audacity multi-track.
repository description · github.comTransform any book or novel into a fully-voiced audiobook using AI-powered script annotation and text-to-speech.
readme · github.comVoice Cloning — Clone any voice from a 5-15 second reference audio sample.
readme · github.comVoice Designer — Create new voices from text descriptions.
readme · github.comThe web UI is available at http://localhost:4200.
readme · github.comdocker compose up --build
readme · github.comAI-powered multi-voice audiobook generator — LLM script annotation, voice cloning, voice design, LoRA training, per-line style control, and export to MP3, chaptered M4B, or Audacity multi-track. Built on Qwen3-TTS.
verdict · github.com- **Multi-Language Support** - English, Chinese, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish, or Auto-detect - **Custom Voices** - 9 pre-trained voices with instruct-based emotion/tone control - **Voice Cloning** - Clone any voice from a 5-15 second reference audio sample
shared feature · github.comRequires [Docker](https://docs.docker.com/get-docker/) with the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html). The web UI is available at `http://localhost:4200`. TTS models download on first use and are cached in a Docker volume.
deployment · github.com- **Combined Audiobook** - Single MP3 with all voices and natural pauses - **Individual Voicelines** - Separate MP3 per line for DAW editing (Audacity, etc.) - **Audacity Export** - One-click zip with per-speaker WAV tracks, LOF project file, and labels for automatic multi-track import into Audacity
migration · github.comSelect your book file (.txt, .md, or .epub) using the file picker — it uploads automatically
migration · github.com
