Best Self Hosted Alternatives to Google Translate

LibreTranslate is a free and open-source machine translation service that provides a simple HTTP API and a web interface for translating text and supported documents. It is designed to be self-hosted and can run fully offline without relying on proprietary translation providers.

Key Features

• REST API for language detection and machine translation
• Web UI for interactive translations
• Offline-capable translation engine powered by Argos Translate
• Support for translating text and selected document/file formats
• Docker-based deployment options for quick setup

Use Cases

• Add private translation capabilities to internal applications via an API
• Run an on-premises translation service for sensitive or regulated content
• Provide translation features for websites and tools without third-party dependencies

LibreTranslate is a practical choice when you need a straightforward, self-controlled translation API with an open-source stack and the ability to operate in disconnected environments.

Speaches is an OpenAI API-compatible server for speech-to-text, translation, and text-to-speech, designed to be a local “model server” for voice workflows. It supports streaming and realtime interactions so applications can transcribe or generate audio with minimal integration changes.

Key Features

• OpenAI API compatibility for integrating with existing OpenAI SDKs and tools
• Streaming transcription via Server-Sent Events (SSE) for incremental results
• Speech-to-text powered by faster-whisper, with support for transcription and translation
• Text-to-speech using Piper and Kokoro models
• Realtime API support for low-latency voice interactions
• Dynamic model loading and offloading based on request parameters and inactivity
• CPU and GPU execution support
• Deployable with Docker and Docker Compose and designed to be highly configurable

Use Cases

• Replace hosted speech APIs with a self-managed, OpenAI-compatible voice backend
• Build realtime voice assistants that need streaming STT and fast TTS responses
• Batch transcription/translation pipelines for recordings with optional sentiment analysis

Speaches is a practical choice when you want OpenAI-style endpoints for voice features while retaining control over models and infrastructure. It fits well into existing OpenAI-oriented application stacks while focusing specifically on TTS/STT workloads.

Lingarr is a subtitle translation application that combines multiple translation services to automatically translate subtitle files to a target language. It supports LibreTranslate, local AI, and cloud providers like DeepL, Anthropic, OpenAI, and more, and can run as a local or SaaS deployment with a RESTful API for integration. (github.com)

Key Features

• Supports multiple translation services including LibreTranslate, Local AI, DeepL, Anthropic, OpenAI, DeepSeek, Gemini, Google, Bing, Yandex and Azure. (github.com)
• Local and SaaS deployment options with Docker Compose and Docker runtime support. (github.com)
• Multi-architecture Docker images (amd64 and arm64) with deployment flexibility. (github.com)
• Exposes a RESTful API for integration into other apps. (github.com)
• Explicit setup guidance for running Lingarr via Docker and Docker Compose. (github.com)

Use Cases

• Self-hosted media libraries: deploy Lingarr with Docker Compose to automatically translate and apply subtitles for movies and TV shows. (github.com)
• Flexible translation workflows: choose from LibreTranslate, OpenAI, DeepL, or other providers to match cost, latency, and quality needs. (github.com)
• API-driven integrations: use the RESTful API to incorporate Lingarr subtitle translation into custom media workflows or apps. (github.com)

Limitations and Considerations

• Lingarr supports a variety of translation providers, which may have different terms of service, pricing, and data handling. (Implemented via the multi-provider approach described in the README.) (github.com)

Conclusion

Lingarr provides a flexible, multi-provider subtitle translation solution that can run locally or as a SaaS service, with a RESTful API for programmatic control. Its Docker-based deployment and broad provider support make it adaptable to diverse translation needs in media workflows. (github.com)

OmniPoly is a web frontend that centralizes translation and language-enhancement workflows. It integrates translation and grammar-checking backends and can optionally use LLMs to provide AI-driven insights and sentence extraction.

Key Features

• Text translation across multiple languages using an external translation backend
• Grammar and style checking via an external LanguageTool instance
• Optional LLM-powered analysis (Ollama) for sentiment, interesting-sentence extraction, and text modification
• File upload for batch translation and download of translated results
• Add words to a user dictionary for grammar checks and configurable language filters
• Docker and Docker Compose support with environment-variable configuration; UI hides features when their backend is not configured

Use Cases

• Translate and proofread emails, documents, or short texts while preserving grammar and style
• Extract and highlight interesting sentences or sentiment from translated text using an LLM
• Build a lightweight internal tool to unify translation, grammar checking, and simple AI text transformations

Limitations and Considerations

• OmniPoly is a frontend and requires external instances of LibreTranslate, LanguageTool, and/or Ollama to enable corresponding features
• Some features are only available when respective backend services and API keys are provided via environment variables

OmniPoly is suited for teams or individuals who want a single interface for translation and language quality workflows and who can provide the required backend services. It emphasizes configurable integrations and simple deployment via Docker.