Applications & models#
Explore the latest blogs about applications and models in the ROCm ecosystem, including machine learning frameworks, AI models, and application case studies.
Introducing Instella-Math: Fully Open Language Model with Reasoning Capability
Instella-Math is AMD’s 3B reasoning model, trained on 32 MI300X GPUs with open weights, optimized for logic, math, and chain-of-thought tasks.
AMD Hummingbird Image to Video: A Lightweight Feedback-Driven Model for Efficient Image-to-Video Generation
We present AMD Hummingbird, offering a two-stage distillation framework for efficient, high-quality text-to-video generation using compact models.
Accelerating Parallel Programming in Python with Taichi Lang on AMD GPUs
This blog provides a how-to guide on installing and programming with Taichi Lang on AMD Instinct GPUs.
Graph Neural Networks at Scale: DGL with ROCm on AMD Hardware
Accelerate Graph Deep Learning on AMD GPUs with DGL and ROCm—scale efficiently with open tools and optimized performance.
Benchmarking Reasoning Models: From Tokens to Answers
Learn how to benchmark reasoning tasks. Use Qwen3 and vLLM to test true reasoning performance, not just how fast words are generated.
Vibe Coding Pac-Man Inspired Game with DeepSeek-R1 and AMD Instinct MI300X
Learn LLM-powered game dev using DeepSeek-R1 on AMD MI300X GPUs with iterative prompting, procedural generation, and VS Code AI tools
Instella-T2I: Open-Source Text-to-Image with 1D Tokenizer and 32× Token Reduction on AMD GPUs
Explore Instella-T2I: AMD’s open-source text-to-image model, built on MI300X GPUs with novel tokenizer and LLM-based encoder for scalable image generation.
Fine-tuning Robotics Vision Language Action Models with AMD ROCm and LeRobot
Speed up robotics AI with AMD ROCm and LeRobot: fine-tune VLAs on Instinct GPUs and deploy on Ryzen AI. Follow the tutorial to get started.
Accelerating Video Generation on ROCm with Unified Sequence Parallelism: A Practical Guide
A practical guide for accelerating video generation with HunyuanVideo and Wan 2.1 using Unified Sequence Parallelism on AMD GPUs.
Nitro-T: Training a Text-to-Image Diffusion Model from Scratch in 1 Day
Nitro-T is a family of text-to-image diffusion models developed by AMD to demonstrate efficient large-scale training on Instinct™ MI300X GPUs. Trained from scratch in under 24 hours
Enabling Real-Time Context for LLMs: Model Context Protocol (MCP) on AMD GPUs
Learn how to leverage Model Context Protocol (MCP) servers to provide real time context information to LLMs through a chatbot example on AMD GPUs
Continued Pretraining: A Practical Playbook for Language-Specific LLM Adaptation
A step by step guide to adapting LLMs to new languages via continued pretraining, with Poro 2 boosting Finnish performance using Llama 3.1 and AMD GPUs