Modular: Modular 26.7: Opening up MAX

Modular released version 26.7 of its MAX platform on October 22, 2026, making the MAX graph compiler, MAX runtime, and device extensibility hooks fully source-available under a new MAX License that permits use, modification, extension, and commercial products with no fees or royalties. The release also adds full eager mode support, including for custom ops, and decision model support, with source for MAX plugins for Qualcomm Dragonfly and Google TPU planned for release in the coming months. Modular said the permissive license differs from Apache 2.0 only on fragmentation, which it addresses through its alliance program for hardware vendors and partners.

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Careers 👋 We’re currently hiring Culture What we believe Contact Us Request a demo October 22, 2026 Modular Team Product The headline of Modular 26.7 is one we've wanted to write for a long time: this release opens the MAX graph compiler, MAX runtime, and device extensibility hooks for everyone. This means that MAX is now fully source-available, and can be built and modified by hardware innovators, researchers, and everyone else who loves making accelerators go "brr." This release also brings an eager mode that gets you debugging custom ops in a fraction of the time, decision model support, and the next step in Mojo's growth into a systems programming language. At our recent ModCon conference, we committed to opening up MAX, and we're delivering on that promise. The full source for MAX is now available: hardware backends, the graph compiler, the runtime, and more. Our new MAX License is intentionally permissive: you can use, modify, extend, and build commercial products with MAX, without licensing fees or royalties. If you've wanted to bring up MAX on your own accelerator, this is where to start, and you can see the existing implementation for NVIDIA, AMD, Apple Silicon, and CPUs as a reference point. We plan to release source for the MAX plugins for other chips, including Qualcomm Dragonfly and Google TPU, in the coming months. The MAX License allows nearly everything Apache 2.0 does: use, modify, extend, and build commercial products with MAX, with no fees or royalties. The difference comes down to fragmentation. We’ve spent decades maintaining major open source projects and have seen the challenges they face. MAX aims to unify the programming model across hardware, and incompatible platform-specific versions would undermine that goal. The Modular alliance program is how we solve this, giving hardware vendors and partners a shared path to build on MAX without splintering the ecosystem. As with Mojo, we expect our approach to evolve as the technology matures and we hear from the community. There's far more in the MAX source code than we can cover here, so we wrote a separate post on what's included and what you can build with it. MAX has long had an advanced graph compiler that performs automatic fusion and other optimizations for peak performance. But during development, fast iteration often matters more than peak performance. MAX now has full eager mode support, including your custom ops, and it shares a single code path with the graph compiler, so the code you run in eager mode is the same as what you compile and ship. Declare an op once, call it directly on a Tensor, then reuse it unchanged inside a compiled Module. That makes the development loop much faster: on a slice of Gemma 4 31B, eager mode reaches the first token in about 30 seconds, compared to about 110 seconds compiled. Here’s an example of how eager mode works with custom ops: n, w, c = custom.Symbols "n", "w", "c" downsample = custom.declare "downsample", inputs={"x": custom.TemplateType DType.float32, n, w, c }, outputs= custom.TemplateType DType.float32, n, w // 2, c , custom extensions= "path/to/kernels" , Eager: runs immediately. y = downsample Tensor.ones 2, 8, 3 shape 2, 4, 3 Compiled: same op inside a Module. class Encoder Module : def forward self, x: Tensor - Tensor: return downsample x 2.0 model = Encoder .compile TensorType DType.float32, "batch", 8, 3 , device=Encoder .device y = model Tensor.ones 2, 8, 3 same op, now compiled There’s been a lot of recent excitement about the new modality of System One/decision models, due to their ability to enable zero-shot classification in a very inexpensive manner. MAX has added initial support for these decision models, including Decider 2B, through the new v1/decisions and v1/systemone API endpoints. MAX has also added support for MiMo-V2.6-Flash, GLM-5.3-Flash, and Muse-Glimmer, with KDA and sparse MLA. In addition to new capabilities, we continue to improve existing model families. Several ops that used to round-trip through the CPU now run entirely on the GPU, which gives a 2.6x prefill speedup for Qwen and GLM models. With 1.0, Mojo proved itself as a language for high-performance code across heterogeneous hardware. Now we're leaning into the next phase of the Mojo roadmap: Mojo as a systems programming language. Mojo 1.2's flagship new feature is pattern matching. The match statement lets you replace long chains of conditionals with clear, structured cases, and the compiler can check that you've handled every one of them. match php def classify point p: Tuple Int, Int - String: match p: case 0, 0: return "origin" case x, 0 if x < 0: return String "negative x-axis:", x case x, 0: return String "x-axis:", x case 0, y: return String "y-axis:", y case x, y: return String "point:", x, ",", y As a bonus, it also works at compile-time: php def classify type T: AnyType - String: comptime match T: case == Int: return "integer" case == String: return "string" case : return "other" Structs can now explicitly opt out of trait conformance for example, by declaring themselves not Movable , and where clauses accept an else branch so you can state exactly why a constraint failed. Both make generic code easier to read and easier to debug. not Movable where else pip install --upgrade max With the whole stack open, we can’t wait to see what you build. Share it on the Modular forum. MAX is now source available and open to everyone October 22, 2026 Modular 26.5: Mojo 1.0 is here August 11, 2026 Modular 26.4: SOTA MoE Serving, Model Bringup via Agent Skills, Mojo 1.0 Beta 2 and More June 18, 2026 Build the future of AI with Modular Sign up today Signup to our Cloud Platform today to get started easily. Browse open models Browse our model catalog, or deploy your own custom model Get all our latest news, announcements and updates delivered directly to your inbox. Unsubscribe at anytime. ⚠️ This form requires JavaScript to function. Please enable JavaScript in your browser to continue. Your data is handled in accordance with Modular's Privacy Policy. Thanks for signing up to our newsletter 🚀 Thank you, Modular Sales Team