# Modular 26.3: Mojo 1.0 beta, mojolang.org, MAX video gen, and more

**URL:** <https://forum.modular.com/t/modular-26-3-mojo-1-0-beta-mojolang-org-max-video-gen-and-more/3038>\
**Category:** Official Announcements\
**Created:** [May 7, 2026, 7:12pm UTC](https://forum.modular.com/t/modular-26-3-mojo-1-0-beta-mojolang-org-max-video-gen-and-more/3038 "2026-05-07T19:12:55Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![Modular](https://sea1.discourse-cdn.com/flex001/user_avatar/forum.modular.com/modular/32/17_2.png) [@Modular](https://forum.modular.com/u/Modular)\
**Post date:** [May 7, 2026, 7:12pm UTC](https://forum.modular.com/t/modular-26-3-mojo-1-0-beta-mojolang-org-max-video-gen-and-more/3038/1 "2026-05-07T19:12:55Z")

</div>

Modular 26.3 is out! Here’s what’s new.

 ![26.3CoverImg (2)](https://us1.discourse-cdn.com/flex001/uploads/modular/original/2X/2/2eb473b9bfa6190bb288dc1f4abf67da3ea3be21.jpeg)

### **Mojo 1.0 is in beta!**

Beta 1 is the first step toward finalizing 1.0 later this year. The beta is what we believe is a feature-complete Mojo 1.0 language, with polishing still ahead before final release.

In 26.3, we’re shipping safe closures with new capturing syntax, conditional conformance to traits, and major improvements to variadics. Full details in the [Mojo changelog](https://mojolang.org/releases/v1.0.0b1).

Mojo also has a new dedicated home at [mojolang.org](http://mojolang.org), consolidating all language docs in one place.

### **Video generation in MAX**

Wan 2.2 support is coming soon for enterprise workloads on Modular Cloud. Text, audio, image, video: one platform, every modality. [Request a demo](https://www.modular.com/request-demo).

### **Unified, distributed-aware tensor**

Writing tensor-parallel code gets a lot easier in 26.3. `max.experimental` now ships a distributed-aware Tensor type, multi-device compilation, and the collective ops needed for tensor-parallel code. The API maps cleanly to both PyTorch DTensor and JAX NamedSharding patterns. We’ve already built a multi-GPU Gemma3 pipeline on top of it. [Docs](https://docs.modular.com/max/api/python/experimental.tensor/).

**Get started**

```auto
uv pip install --upgrade modular

```

[MAX changelog](https://docs.modular.com/stable/max/changelog/) | [Mojo changelog](https://mojolang.org/releases/v1.0.0b1)

**[Read the full release blog post here.](https://www.modular.com/blog/modular-26-3-mojo-1-0-beta-max-video-gen-and-more?utm_source=forum&utm_campaign=26_3)**

We’d love to hear what you build with 26.3. Drop your questions, feedback, and projects in the replies.

---

<div class="post-metadata">

**Author:** ![forfudan](https://sea1.discourse-cdn.com/flex001/user_avatar/forum.modular.com/forfudan/32/925_2.png) [@forfudan](https://forum.modular.com/u/forfudan)\
**Post date:** [May 7, 2026, 7:39pm UTC](https://forum.modular.com/t/modular-26-3-mojo-1-0-beta-mojolang-org-max-video-gen-and-more/3038/2 "2026-05-07T19:39:20Z")

</div>

It is a great milestone! 🥳

---

<div class="post-metadata">

**Author:** ![ulmentflam](https://sea1.discourse-cdn.com/flex001/user_avatar/forum.modular.com/ulmentflam/32/1136_2.png) [@ulmentflam](https://forum.modular.com/u/ulmentflam)\
**Post date:** [July 8, 2026, 6:23pm UTC](https://forum.modular.com/t/modular-26-3-mojo-1-0-beta-mojolang-org-max-video-gen-and-more/3038/3 "2026-07-08T18:23:34Z")

</div>

I built something on 1.0.0b3 for the occasion: a port of Karpathy’s llm.c that extends @dorjeduck’s llm.🔥 with hand-written CUDA and Metal GPU kernels, training GPT-2 124M end to end in pure Mojo. On an M4 Max the Metal path runs at 498.92 ms/step in bf16, 1.72x faster than PyTorch MPS (llm.c has no Metal port, so MPS is the baseline there). On a GB10 it reached bf16 parity with llm.c CUDA. Comptime vendor dispatch and MAX’s `linalg.matmul` did a lot of heavy lifting; the main thing I hit was a SHARED-to-GENERIC address-space cast that silently reads zeros on Metal AIR (details and a probe in the repo). Full writeup: [Llm.🔥: GPT-2 training in pure Mojo, with hand-written CUDA and Metal GPU kernels](https://forum.modular.com/t/llm-gpt-2-training-in-pure-mojo-with-hand-written-cuda-and-metal-gpu-kernels/3304). Correctness is gated against PyTorch gradients.
