VACE introduces a powerful all-in-one framework for AI video generation and editing, combining text-to-video, reference-based creation, and precise editing in a single open-source model. It outperforms alternatives like AnimateDiff and SVD in resolution, flexibility, and controllability — though character consistency and memory usage remain key challenges.

Runpod has a new look — and a sharper focus. Explore the redesigned site, refreshed brand, and the platform powering real-time inference, custom LLMs, and open-source AI workflows.

Learn how to build ethical AI—from bias and privacy to transparency and sustainability — using tools and infrastructure that support responsible development.

A deep technical dive into how the Runpod Hub streamlines serverless AI deployment with a GitHub-native, release-triggered model. Learn how hub.json and tests.json files define infrastructure, deployment presets, and validation tests for reproducible AI workloads.

The Runpod Hub is here—a creator-powered marketplace for open source AI. Browse, fork, and deploy prebuilt repos for LLMs, image models, video generation, and more. Instant infrastructure, zero setup.

From brainstorming essays to auto-tagging lecture notes, students are using AI in surprising and creative ways. This post dives into the real habits, hacks, and ethical questions shaping AI’s role in modern education.

vLLM is fast—but SGLang might be faster for multi-turn conversations. This post breaks down the trade-offs between SGLang and vLLM, focusing on KV cache reuse, conversational speed, and real-world use cases.