NobodyWho
NobodyWho is an open-source, on-device inference library and SDK that runs text, vision, and speech models (LLM, STT, TTS) locally across platforms, emphasizing performance, privacy, and offline use.
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Best for: Voice & Speech
What it does
AI Tools software for decision-makers comparing workflow fit and alternatives.
Best fit
Voice & Speech
Pricing snapshot
Free from $0
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NobodyWho is an open-source on-device inference library and SDK designed to run text, vision, and speech models locally without servers. It provides SDKs and examples (Chat, STT, TTS) across multiple languages and platforms so developers can integrate AI with minimal code. The project emphasizes fast, optimized inference (Metal, CUDA, Vulkan), strict local privacy (no cloud logging, offline operation), and broad model compatibility (GGUF format and Hugging Face model URIs). The library is licensed under EUPL 1.2 and is free for individuals and companies.
Run AI models on any device Discussion | Link
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Claim this listing for $29Key Features
On-device LLM, STT, and TTS
Provides SDKs and runtime support for chat (LLM), speech-to-text (STT), and text-to-speech (TTS) with code examples in multiple languages.
Multi-platform SDKs
Platform bindings and examples for React Native, Flutter, Kotlin, Swift, Python, and Godot, plus explicit platform support for Apple, Android, Windows, and Linux.
High-performance inference
Optimized kernels for Metal, CUDA, and Vulkan to deliver fast inference even on integrated graphics and mobile chips.
Privacy & offline-first
Designed to keep data local: no cloud logging, prompts remain in local GPU memory, and models can run offline in secure environments.
Model compatibility
Direct support for GGUF format and the ability to pick models from Hugging Face; examples reference HF URIs (e.g., hf://onnx-community/whisper-base).
Open-source and permissive for companies
The library is open source under EUPL 1.2 and stated to be free for both individuals and companies.
Pricing
Completely free, no API keys, or usage fees.
Free
$0- Open-source library under EUPL 1.2
- No API keys or usage fees
Use Cases
On-device chat assistants
Embed chat/LLM functionality directly in apps using Chat.fromPath with local GGUF models for low-latency, private responses.
Speech transcription
Use STT.transcribeFile with locally hosted models (e.g., onnx-community/whisper) to transcribe audio without sending data to the cloud.
Text-to-speech for apps
Synthesize speech locally with Tts.load and save WAV output for offline or private TTS in applications.
Secure and offline deployments
Run models on-device for scenarios requiring no internet connectivity or strict data locality, such as in-flight or secure environments.
Integrations
Hugging Face
Pick and run models hosted on Hugging Face; site advises selecting models from Hugging Face and supports HF URIs.
onnx-community (Whisper)
STT examples reference hf://onnx-community/whisper-base for speech transcription.
Third-party model authors (Mistral, Qwen, Gemma, Liquid, OpenAI listed)
The site lists model names (Mistral, Open AI, Liquid, Qwen, Deepseek, Gemma) as supported model sources or examples.
Benefits
Limitations
No verified limitations are available.
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Explore the Docs and pick a model from Hugging Face or a GGUF model.
- 2 Install or import the NobodyWho SDK for your platform (examples shown for React Native, Flutter, Kotlin, Swift, Python, Godot).
- 3 Load a model path (e.g., Chat.fromPath({ modelPath: "./model.gguf" })) and call the provided APIs (ask, transcribeFile, synthesize) to run inference locally.
Support
docs
Documentation referenced on the site (Docs link in navigation).
github
Project and source code available via GitHub (link in site navigation).
community
Community channels listed on the site (Discord and social links).
Email contact is listed in the site footer/navigation (explicit address not shown).
API
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