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Our team’s insights on building better and scaling smarter.
Mochi 1 pushes the boundaries of open-source video generation. Learn what makes it special, what’s new in v1, and how to deploy it on Runpod.
Stability.ai’s SD3.5 is here—with new models built for speed and quality. Learn what’s changed, what’s improved, and how to run it on Runpod.
Stable Diffusion 3.5 delivers a major quality leap, fixing past flaws while generating photorealistic images from minimal prompts. Learn what’s new, how to get started on Runpod, and what to expect next from the community.
NVidia’s Llama 3.1 Nemotron 70B is outperforming larger and closed models on key reasoning tasks. In this post, Brendan tests it against a long-unsolved challenge: consistent, in-character roleplay with zero internal monologue or user coercion—and finds it finally up to the task.
Nemotron 70B is NVIDIA’s latest open model and it’s climbing the leaderboards. But how does it perform in the real world—and can it solve your toughest inference challenges?
Skip the front ends—learn how to use Jupyter Notebook on Runpod to run Stable Diffusion directly in Python. Great for devs who want full control.
Large language models can write poetry and solve logic puzzles—but fail at tasks like counting letters or doing math. Here’s why, and what it tells us about their design.
