The launch of MAX 24.3 marks an exciting milestone, featuring a preview of the new MAX Engine Extensibility API. This API empowers developers to unify, program, and compose their AI pipelines using our next-generation compiler and runtime stack, ensuring top-notch performance. MAX 24.3 is only the initial step in a series of remarkable updates outlined in our MAX roadmap. Stay tuned for upcoming support for MacOS and Quantization, with GPUs slated for release this summer.
MAX Engine is a next-generation compiler and runtime library for running AI inference. With support for PyTorch (TorchScript), ONNX, and native Mojo models, it delivers low-latency, high-throughput inference on a wide range of hardware to accelerate your entire AI workload. Furthermore, the MAX platform empowers you to harness the full potential of the MAX Engine through the creation of bespoke inference models using our MAX Graph APIs.
In this release, we continue to build on our incredible technology foundation to improve programmability of MAX for your workloads with 24.3 features including:
- Custom Operator Extensibility: Write custom operators for MAX models using the Mojo programming language for intuitive and performant extensibility.
- Mojo 🔥 Improvements: The Mojo language and standard library continues to mature, with key improvements that will be welcomed by Python experts. This includes enhancements to built-in types like Tuple and support for in function types for both optional and variadic arguments. Read the What’s New in Mojo 24.3 blog post and check out the complete list of changes in the Mojo 24.3 changelog.
- Less Dependencies and Smaller Package Size: TensorFlow support has been removed from the standard MAX package, making it 60% smaller, resulting in faster download times and fewer dependencies. TensorFlow is still available for enterprise users. Contact us for more information.
- Community-Driven Innovation: Following on open sourcing the Mojo standard library, this release includes the first community-submitted PRs to the Mojo standard library – featuring 32 significant community contributions, improving on the built-in types and usability of the Mojo standard library. Together with our amazing community, we’re shaping the future of AI development!