Phonon
Phonon is an open-weight text-to-speech (TTS) model and inference runtime for developers adding speech generation to applications that need local, offline audio. It converts text into spoken audio and can stream speech as it is generated. The runtime provides Rust and Python interfaces, a Swift package for iOS and macOS, JavaScript for browsers, and Android libraries; it can also run as a self-hosted server with an OpenAI-compatible API. Depending on the model variant, it supports English, French, German, Spanish, and Portuguese. Phonon is intended for developers integrating speech into mobile, desktop, web, embedded, and server applications, including offline or privacy-sensitive use cases. The 31-million-parameter English model weights use the Apache 2.0 license; 40-million-parameter language-specific and multilingual weights use CC BY-NC 4.0. The runtime code is separately available under Apache 2.0 or MIT.
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WhollyAPI
WhollyAPI is a hosted AI inference platform that gives developers a unified API for using AI models in applications and workflows. Its model catalog includes text generation, embeddings, image generation, video generation, speech synthesis and recognition, and other multimodal tasks. Model pages provide model information, usage demonstrations, API compatibility details, and usage-based pricing; text-generation pages document OpenAI-compatible chat-completion requests through WhollyAPI's serverless API. The service is aimed at developers and teams building AI-enabled software who want to access multiple model types through one hosted service instead of operating inference infrastructure themselves. Potential uses include generating or transforming text and images, creating video, processing audio, and adding model-powered features to applications. Available models, capabilities, and charges vary by model and usage.
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Qualcomm Cloud AI SDK
The Qualcomm Cloud AI SDK is a comprehensive software suite designed to optimize trained deep learning models for high-performance inference on Qualcomm Cloud AI 100 accelerators. It supports a wide range of AI frameworks, including TensorFlow, PyTorch, and ONNX, enabling developers to compile, optimize, and execute models efficiently. The SDK provides tools for model onboarding, tuning, and deployment, facilitating end-to-end workflows from model preparation to production deployment. Additionally, it offers resources such as model recipes, tutorials, and code samples to assist developers in accelerating AI development. It ensures seamless integration with existing systems, allowing for scalable and efficient AI inference in cloud environments. By leveraging the Cloud AI SDK, developers can achieve enhanced performance and efficiency in their AI applications.
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Google GenAI SDK
The Gemini API libraries provide official, production-ready Google GenAI SDKs for building with the Gemini API in popular programming languages. Google recommends using the Google GenAI SDK when building with Gemini, since these libraries are developed and maintained by Google, used across official documentation and examples, and are generally available for production use. The SDKs are available for Python, JavaScript/TypeScript, Go, Java, and C#, with installation through standard package managers such as pip install google-genai, npm install google/genai, Maven dependencies for google genai, and dotnet add package Google GenAI. They provide access to the latest Gemini API features and are designed to offer the best performance when working with Gemini models. Google strongly recommends migrating from legacy libraries to the new Google GenAI SDK because the legacy libraries are not actively maintained.
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