Building AI’s unified compute layer. We are hiring → modular.com/careers 🚀
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ModCon 2026 x.lingyaoai.com/i/broadcasts/1NGarozOn…
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.@dMatrix_AI had matrix multiplication running in Mojo on their Corsair accelerator 6 days after getting access to the Mojo compiler.
At ModCon 2026, our Chief Scientist Abdul Dakkak walked through why this was possible with the Modular stack: piped.video/watch?v=hYjKbTAG…
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Are models commoditizing? We asked four panelists at ModCon, from Google DeepMind, MiniMax, Poolside, and Reflection AI, and asked where they see innovation coming from, whether that's data, post-training, or somewhere else: piped.video/GZ_oM-nLGO0
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We spent 90 minutes at Monday's community meeting watching developers demo the impressive projects they've built with Mojo, including work supported by the Modular Community Grant Program:
1. Floki (Mikhail) is an HTTP client built on libcurl. Its API is close to Python's requests, so most existing code ports over with small edits.
2. Noira (Denis) covers reinforcement learning, a physics engine, and robot deployment. On an M1 Pro it solves LunarLander in 39 seconds. PyTorch + CleanRL takes 235.
3. Thyn (Angel) packages 6,000+ Mojo kernels as Python and TypeScript SDKs.
4. Warp (Alex) is an async runtime that works out when the CPU and GPU need to sync, which lets kernels run concurrently.
Check out the recording: piped.video/watch?v=gvDEC5_i…
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Our cofounder and CEO @clattner_llvm takes the keynote stage at The AI Conference @AIconference tomorrow at 10:05 AM in Theater 1.
His talk, "Opening the AI Compute Stack with MAX and Mojo," covers why the software layer will decide the future of AI compute. He'll introduce Mojo 1.0, now fully open source under Apache 2.0, explain how MAX delivers portable performance across hardware, and cover how you can get involved to build a more open future for AI: agenda.45-77-127-32.nip.io/?…
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Monday's community meeting showcases several standout community projects, including:
• floki: an HTTP client for Mojo that works like Python's requests library, supported by the Modular Community Grant Program
• noeira: an end-to-end physical AI stack in Mojo - physics, learning, perception and deployment, from simulator to robot, supported by the Modular Community Grant Program
• warp: a look at building an async runtime to manage GPU synchronization calls across coroutines in Mojo
Join us via Zoom at 10 AM PT: luma.com/sep-modular
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This week in Chicago, Mojo found The Bean, ate a pretzel half its size, and got to hang out with the whole Modular team at our off-site.
Want to come to the next one? We're hiring across Engineering, Product Management, Customer Engineering, and Developer Relations: modular.com/company/careers
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Modular retweeted
.@clattner_llvm takes the #SnapdragonSummit stage for the first time as EVP Advanced AI Software @Qualcomm following the @Modular acquisition.
Introducing the audience to the stack and it's role in the broader ecosystem.
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Modular retweeted
GPU architecture | LLM Inference Handbook
handbook.modular.com/kernel-…
Add this to your LLM learning resource bundle.
"Before writing or tuning GPU kernels, you need a working model of how a GPU runs code. Without it, suggestions like “increase occupancy” or "reduce shared memory bank conflicts" are just a set of rules to memorize. You don't fully understand when they apply and when they don't.
This section explains modern GPU architecture at the level needed for kernel work. The details lean toward NVIDIA hardware because CUDA dominates much of the LLM inference ecosystem today. However, the core concepts apply broadly to AMD GPUs and other parallel accelerators as well."
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Optimizing large scale inference systems is what we do, so we decided to write down what we know.
Our LLM Inference Handbook is a free reference covering TTFT, TPOT, goodput, continuous batching, chunked prefill, prefix caching, KV cache math, prefill-decode disaggregation, quantization, and more.
It includes 20+ interactive visualizations, is updated continuously, and is open to PRs.
handbook.modular.com
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Modular retweeted
My personal favourites :
1. handbook.modular.com/
2. jax-ml.github.io/scaling-boo…
3. baseten.co/inference-enginee…
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Looking to get started with MAX?
At ModCon 2026, Ehsan M. Kermani @ehsanmok and Bingfeng Xia went layer by layer through the stack: MAX Serve, the framework, and the Mojo kernel library, ending with a live agent bringing up a new model end to end.
Start here: piped.video/watch?v=3H8Orjaa…
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On the MAX side, audio joins text, vision, and image generation. The new audio_generation pipeline launches with MiniMax-Music3, producing 44.1 kHz stereo music from a style prompt and lyrics.
MAX performance improved, too: up to 4.8x faster Gemma 4 decode attention and 7.9x faster MoE routing on NVIDIA B200, and up to 6.6x faster decode attention projections on AMD MI355.
MAX changelog: max.modular.com/releases/v26…
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Contributing guide, changelogs, and open issues are linked in the release post. If 26.6 breaks something for you, please let us know in GitHub Issues.
Read the full blog: modular.com/blog/modular-26-…
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Modular 26.6 is here. Mojo 1.1 opens the compiler to external contributions and adds developer experience improvements, while MAX 26.6 brings audio generation, new model architectures, and faster performance.
Release blog: modular.com/blog/modular-26-…
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We open sourced the Mojo compiler under Apache 2.0 at ModCon last month. Opening it to contributions was the top request we heard afterward, and it took some time to get the infrastructure right. It's ready now. We also migrated our internal issues to public GitHub issues, so you can read what the compiler team is working on this week.
Mojo changelog: mojolang.org/releases/v1.1.0…
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At ModCon this year, we asked five investors where the next wave of AI infrastructure capital is going: training, inference, or silicon? Five different answers, and one panelist said it's the wrong question to be asking.
The discussion also covered whether chipmakers absorbing AI software means the infrastructure is maturing or getting ahead of itself, and what open weight models do to the valuation of a compute-heavy startup.
Michelle Gonzalez (@M12vc), Liz Stein (@USITfund), Sam Fort (@dfjgrowth), Quentin Clark (@generalcatalyst) and Dave Munichiello (@GVteam) each closed with what they think founders should build right now.
Full recording: piped.video/watch?v=5igY763x…
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At #ModCon2026, Qualcomm CEO @Cristianoamon shared a bold vision for the future of AI infrastructure—and why our acquisition of @Modular is a massive win for the global developer ecosystem.
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Fragmentation creates a tax across the entire AI ecosystem. At @PyTorch Conference this year, @clattner_llvm presents an alternative: one software stack to unite heterogeneous hardware.
Join us in San Jose on October 20-21: hubs.la/Q04v4SL60 #PyTorchCon
New chips are shipping faster than ever before, but the ecosystem is being held back by having to rewrite and then re-debug the same code over & over again.
@clattner_llvm CEO and Co-founder at @Modular and EVP of Advanced AI Software & Platforms at @Qualcomm, will deliver a keynote at PyTorch Conference North America about an open software platform for heterogeneous compute powered by Mojo and MAX.
PyTorch has always been the place where the best models come together, and now there's a way to get those models onto all kinds of hardware.
If you're interested in Al and compute, join us at the PyTorch Conference in San Jose, CA. Register now: hubs.la/Q04v4SL60
#PyTorchCon
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Headed to Santa Clara today for #AIInfraSummit?
Don’t miss @alisterburt's talk at 10:30 AM PT in Expo Theater 2: "Modular: Open Source, Open Cloud, Open Silicon."
Stop by the Qualcomm booth (#206) anytime this week during expo hall hours to chat with the Modular team and catch a Modular Cloud demo.
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