Best tools for Mobile Development

Google’s app development platform for backend, auth, database, hosting, analytics, and AI features

Firebase is Google’s app development platform providing backend services including Firestore, Realtime Database, Authentication, Cloud Storage, Cloud Functions, Hosting, Analytics, messaging, and AI-connected app features. Current docs foreground Firebase AI Logic for Gemini API access, Genkit for full-stack AI and agentic apps, Firestore vector search, and SQL Connect. Spark plan is free; Blaze is pay-as-you-go.

50x faster LLM gateway with MCP support, built in Go

Bifrost is a high-performance open-source AI gateway built from scratch in Go. Unifies access to 15+ providers and 1,000+ models through a single OpenAI-compatible API with only 11 microsecond overhead per request at 5K RPS — 50x faster than LiteLLM. Features automatic failover, load balancing, semantic caching, and functions as both MCP client and MCP server. Apache 2.0 licensed.

On-device AI inference engine for mobile and wearable applications

Cactus is a YC-backed low-latency AI engine for mobile and wearable devices that runs LLMs, transcription, embedding, and TTS models locally. It achieves 16-20 tok/sec on older devices and 70+ tok/sec on flagships with ARM SIMD kernels optimized for Snapdragon, Apple, and MediaTek processors. Supports Qwen, Gemma, Llama, DeepSeek with Flutter, React Native, and Kotlin SDKs.

AI coding agent for embedded systems and firmware engineering

Embedder is a specialized AI coding agent for firmware and embedded systems development. It supports 400+ MCU variants including STM32 and ESP32, parses hardware datasheets to understand register maps and pin configurations, and verifies generated code by interacting with physical boards via serial console. YC S25 participant currently in beta.

PyTorch on-device AI for mobile and edge devices

ExecuTorch is PyTorch's official solution for deploying AI models on mobile, embedded, and edge devices. It features a 50KB base runtime, 12+ hardware backends including Apple CoreML, Qualcomm QNN, ARM, and Vulkan, and native PyTorch export without format conversions. Powers Meta's on-device AI across Instagram, WhatsApp, Quest 3, and Ray-Ban Smart Glasses, supporting LLMs, vision, speech, and multimodal models.

Run open-source LLMs on your phone, fully offline and private

Google AI Edge Gallery is an open-source mobile app that lets you download and run large language models like Gemma directly on Android and iOS devices with zero cloud dependency. Built on MediaPipe and LiteRT, it features AI chat with reasoning mode, multimodal image analysis, real-time audio transcription, and autonomous agent skills—all running entirely on-device for complete privacy. A reference implementation for developers building offline-first AI experiences.

Lightweight mobile and edge AI inference engine

MNN is a lightweight, high-performance deep learning inference engine developed by Alibaba and battle-tested across 30+ Alibaba apps including Taobao, DingTalk, and Youku. It supports TensorFlow, ONNX, PyTorch, and Caffe models with optimized backends for CPU, GPU, and NPU on mobile and edge devices. MNN includes on-device LLM inference, an OpenCV-like image processing library, and Python bindings for rapid prototyping. Apache 2.0 licensed with 15K+ stars.

On-device ML solutions for mobile and edge AI

MediaPipe is Google's open-source framework for building on-device machine learning pipelines across mobile, web, desktop, and edge platforms. It provides pre-built solutions for face detection, hand tracking, pose estimation, object detection, image classification, text classification, and on-device LLM inference. MediaPipe runs entirely locally without cloud dependencies, supporting Android, iOS, Python, and web browsers.

AI-powered vision-driven UI automation for web, Android, and iOS

Midscene.js is an open-source UI automation framework from ByteDance's Web Infra team that uses vision-based AI models to understand and interact with interfaces. It replaces fragile CSS selectors with natural language descriptions, supporting web browsers via Playwright and Puppeteer, Android via ADB, and iOS via WebDriverAgent from a unified JavaScript SDK.

MCP server for mobile device automation and testing

Mobile MCP is an open-source MCP server that enables AI agents to automate Android and iOS devices — navigating apps, tapping elements, extracting screen content, and running tests on simulators, emulators, and physical devices. It brings agentic mobile engineering to any MCP-compatible AI assistant.

High-performance mobile neural network inference

NCNN is Tencent's high-performance neural network inference framework optimized for mobile and embedded platforms. It features pure C++ with zero dependencies, ARM NEON assembly optimization, Vulkan GPU acceleration, and sophisticated memory management for minimal footprint. Supports importing models from PyTorch, ONNX, Caffe, TensorFlow, and Keras with 8-bit quantization and half-precision storage for efficient on-device deployment across Android, iOS, and Linux.

Cross-platform on-device AI model runtime

Nexa SDK enables running frontier LLMs and multimodal models locally across PC, mobile, IoT, and wearables with automatic hardware acceleration for GPU, NPU, and CPU. It supports Qwen, Gemma, Llama, DeepSeek models with Python/C++ desktop SDKs, Android/iOS mobile SDKs, and Docker for edge deployment. Includes an OpenAI-compatible API server with chat and function calling support.

Optimize and deploy AI models on Snapdragon devices

Qualcomm AI Hub is a platform for optimizing and deploying AI models on Snapdragon-powered devices with NPU acceleration. It provides pre-optimized models, profiling tools, and the SNPE SDK for compiling models to run efficiently on Qualcomm's Hexagon DSP and AI Engine. Supports hundreds of model architectures with on-device benchmarking across real Snapdragon chipsets for mobile, IoT, and XR applications.

On-device AI inference for React Native apps

Declarative framework for running AI models on-device in React Native applications, powered by Meta ExecuTorch runtime. Supports LLMs including Llama 3.2, computer vision, OCR, embeddings, and vision-language models on iOS 17+ and Android 13+. Developed by Software Mansion with pre-built optimized models, custom model export support, and privacy-first inference without any cloud dependency for mobile AI development.

Cross-platform on-device AI inference SDK

RunAnywhere SDK is a production-ready toolkit for running AI models entirely on-device across iOS, macOS, Android, Web, React Native, and Flutter. It provides a unified C++ core with platform-specific bindings for LLM text generation via llama.cpp, vision-language models, Whisper speech-to-text, Piper text-to-speech, and on-device image generation. All processing stays local with zero cloud dependency, ensuring privacy and low latency for mobile and edge AI applications.

Visual agent builder with 1000+ integrations

Sim is an open-source platform for building, deploying, and orchestrating AI agents with a visual workflow editor. Connects 1,000+ integrations and LLMs with drag-and-drop canvas design, AI-assisted Copilot for generating nodes from natural language, and built-in knowledge base for RAG. Trusted by 100K+ builders. Includes 11 pre-built workflow templates for quick deployment.

Build smaller, faster desktop apps with Rust and web tech

Tauri is a Rust-based framework for building desktop applications using web technologies like HTML, CSS, and JavaScript—without bundling Chromium. By leveraging the system's native WebView, Tauri apps ship as tiny installers under 10MB and use 30-50MB RAM at idle, a fraction of Electron's footprint. It supports Windows, macOS, and Linux with any frontend framework (React, Vue, Svelte, etc.) and provides a secure Rust backend for system-level operations with fine-grained permission controls.

Google's lightweight ML framework for mobile and embedded

TensorFlow Lite is Google's lightweight ML framework for deploying models on mobile and embedded devices. It supports quantization, GPU/NPU delegation, and runs on Android, iOS, Linux, and microcontrollers. Provides pre-trained models, model conversion tools from TensorFlow and JAX, and hardware acceleration via GPU, Hexagon DSP, and CoreML delegates. Powers on-device ML in billions of Google app installations.

Headless rich text editor framework with real-time collaboration

Tiptap is a headless rich text editor toolkit for building Notion-like collaborative content experiences in web applications. Built on ProseMirror, it provides a modular extension system for formatting, mentions, tables, drag-and-drop blocks, slash commands, and custom node types. The open-source core is framework-agnostic with official bindings for React, Vue, and vanilla JavaScript. Cloud extensions add real-time collaboration, AI content generation, and document management.

Offline speech recognition for 20+ languages

Vosk is an offline speech recognition toolkit supporting 20+ languages with compact 50MB models that run on Raspberry Pi, Android, iOS, and servers. It provides streaming API with zero-latency response, speaker identification, and reconfigurable vocabulary. Vosk offers bindings for Python, Java, Node.js, C#, Go, and Rust. Unlike cloud-based alternatives, all processing happens locally with no internet required. Apache 2.0 licensed with 14K+ GitHub stars.

Sentry-maintained MCP server and CLI for Xcode builds, simulators, and tests

XcodeBuildMCP is a Sentry-maintained, MIT-licensed MCP server and CLI for agent-assisted iOS and macOS development. It lets MCP-compatible coding agents run Xcode build and test workflows, manage simulators, inspect failures, and work through Homebrew, npm, or on-demand client configuration, with documented Sentry telemetry controls for teams that need an opt-out.

Lightweight C++ inference for Google Gemma models

gemma.cpp is Google's standalone C++ inference engine built specifically for running Gemma language models without Python or CUDA dependencies. It provides optimized CPU inference using SIMD instructions and Highway library, supports Gemma 2 and Gemma 3 models, and runs on x86 and ARM architectures. Designed for embedded systems, edge devices, and server deployments needing minimal overhead.