Blog

At Modular, we’re always experimenting with the latest agentic programming tools, integrating the best ones into our workflows, and learning quite a few lessons along the way. One thing we realized is that the Mojo language is ideally suited to the needs of modern AI coding agents.

Inkwell is a web app that lets users create interactive storybooks with a custom character along infinite branching paths. When the user opens a story, the first page of text and image art streams in - text appears character-by-character via WebSocket within the first second, the illustration paints in as you read, and by the time you tap a choice, the next page is already written and illustrated. Creating a user experience around the seamless generation of new content requires an inference layer that can perform at scale.

Surprise: Mojo 1.0 is officially in beta! Modular’s 26.3 release includes new features and modalities, but the headline is that we’ve officially hit beta for Mojo 1.0, with a clear plan to finalize Mojo 1.0 in the coming months. We share details below, alongside other key announcements in our 26.3 release including video generation in MAX with Wan 2.2 and MAX framework updates.

Our benchmarks show 15% higher throughput when compared to vLLM on NVIDIA B200.

Today’s 26.2 release expands the Modular Platform’s modality support to include image generation and image editing workflows. This extends our existing support for text and audio generation. In the 26.2 version Black Forest Labs' FLUX.2 model variants are supported with over a 4x speedup over state-of-the-art.

Today we’re releasing Modular 26.1, a major step toward making high-performance AI computing easier to build, debug, and deploy across heterogeneous hardware. This release is focused squarely on developer velocity and programmability—helping advanced AI teams reduce time to market for their most important innovations.

While we are excited about this milestone, this of course won’t be the end of Mojo development! Some commonly requested capabilities for more general systems programming won’t be completed for 1.0, such as a robust async programming model and support for private members. Read below for more information on that!

Today, we’re excited to release Modular Platform 25.7, an update that deepens our vision of a unified, high-performance compute layer for AI. With a fully open MAX Python API, an experimental next-generation modeling API, expanded hardware support for NVIDIA Grace superchips, and a safer, more capable Mojo GPU programming experience, this release moves us closer to an ecosystem where developers spend less time fighting infrastructure and more time advancing what AI can do.

We’re excited to announce Modular Platform 25.6 – a major milestone in our mission to build AI’s unified compute layer. With 25.6, we’re delivering the clearest proof yet of our mission: a unified compute layer that spans from laptops to the world’s most powerful datacenter GPUs. The platform now delivers:

Modular Platform 25.5 is here, and introduces Large Scale Batch Inference: a highly asynchronous, at-scale batch API built on open standards and powered by Mammoth. We're launching this new capability through our partner SF Compute, enabling high-volume AI performance with a fast, accurate, and efficient platform that seamlessly scales workloads across any hardware.