Sandeep79 articles in On-Device AI — page 2 of 4. Practical, up-to-date guides written to be found, answered, and cited.
The State of Multimodal AI in 2026: Where Things Stand — a practical 2026 guide to state of multimodal AI, core concepts, best practices, real data and FAQs.
How to Add Visual Question Answering to Your Mobile App — a practical 2026 guide to add visual question answering, for developers and founders.
Executorch vs llama.cpp: Choosing Your Mobile Inference Engine — a practical 2026 guide to executorch vs llama.cpp: choosing, for developers and founders.
What Is INT4 Quantization and Why Does Your Phone Love It — a practical 2026 guide to int4 quantization, core concepts, best practices, real data and FAQs.
How to Distill GPT-Class Reasoning Into a 3B Model — a practical 2026 guide to distill GPT class reasoning into, for developers and founders.
Best Tools for Benchmarking On-Device LLMs in 2026 — a practical 2026 guide to tools, core concepts, best practices, real data and FAQs, updated for 2026.
How Does Grouped-Query Attention Speed Up Small Models — a practical 2026 guide to grouped query attention speed up small, for developers and founders.
Vision-Language Models for Robotics: A Practical Introduction — a practical 2026 guide to vision language models, for developers and founders.
How to Build a Voice Assistant That Runs Fully On-Device — a practical 2026 guide to voice assistant, core concepts, best practices, real data and FAQs.
What Is a Mixture-of-Experts Model and Can It Run on Mobile — a practical 2026 guide to mixture of experts model, for developers and founders.
GGUF vs ONNX: Which Format Fits Your On-Device Deployment — a practical 2026 guide to gguf vs onnx:, core concepts, best practices, real data and FAQs.
How to Run a Multimodal Model in the Browser With WebGPU — a practical 2026 guide to run a multimodal model, for developers and founders, updated for 2026.
Why TinyML Is Reshaping IoT Sensors in 2026 — a practical 2026 guide to reshaping IoT sensors, core concepts, best practices, real data and FAQs.
Structured Pruning Explained: Cutting Model Size the Smart Way — a practical 2026 guide to structured pruning explained: cutting model, updated for 2026.
How to Measure Latency and Power on Edge AI Devices — a practical 2026 guide to measure latency, core concepts, best practices, real data and FAQs.
The Rise of Agentic Vision-Language Models: What to Expect — a practical 2026 guide to rise of agentic vision language models:, for developers and founders.
What Is LoRA and How Does It Enable On-Device Fine-Tuning — a practical 2026 guide to lora, core concepts, best practices, real data and FAQs.
How to Turn a Large Teacher Model Into a Tiny Student — a practical 2026 guide to turn a large teacher model, for developers and founders, updated for 2026.
Best On-Device Speech-to-Text Models You Can Ship in 2026 — a practical 2026 guide to ship, core concepts, best practices, real data and FAQs.
How Molmo and Pixtral Push Open Vision-Language Models Forward — a practical 2026 guide to molmo, core concepts, best practices, real data and FAQs.
What Is Post-Training Quantization and When Should You Use It — a practical 2026 guide to post training quantization, for developers and founders.
MediaPipe vs ONNX Runtime for Mobile AI: A 2026 Comparison — a practical 2026 guide to mediapipe vs onnx runtime, for developers and founders.
How to Build an Offline Document Scanner With a Small VLM — a practical 2026 guide to offline document scanner, for developers and founders, updated for 2026.
Why Vision-Language Models Hallucinate and How to Reduce It — a practical 2026 guide to vision language models hallucinate, for developers and founders.