Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundation
Joined September 2016
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PyTorch retweeted
Day-0 support for Muse Spark Open on TokenSpeed.
190 output tokens/s per user on NVIDIA B300 — and that’s without speculative decoding.
Also supported on AMD Instinct MI355X.
👉 github.com/lightseekorg/toke…
Today we’re releasing Muse Spark Open, the most capable US open-weight model to date.
Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning.
Key Model Specs:
→ 816B total / 42B active parameters
→ 1M token context window
→ Natively multimodal across text, image, video, audio
PyTorch retweeted
🎉 Day-0 support for Meta's open-weight Muse Spark Open is
live on vLLM, verified on NVIDIA and AMD GPUs as well as on TPUs!
816B parameters, 42B active per token, a 1M-token image, video and audio inputs, built for long-horizon agentic coding.
We’re excited to have worked with Meta Superintelligence Labs to bring Muse Spark Open to vLLM from day one as the most capable US open-weight model.
✨ 1M context for large, complex codebases
👀 Native image, video, audio & document understanding
⚡ BF16, NVFP4 & MXFP4 support
🚀 DSpark speculative decoding on both CUDA and ROCm
1/6
PyTorch retweeted
At our first #PyTorchMadrid meetup, @SergioPaniego explored TRL + OpenEnv for agent post-training!
Made me think of @goose_oss from @AgenticAIFdn 👀 Open source agent harnesses can also play a role in RL training helping models learn from tool use 💡
PyTorch retweeted
1/ 🚀 New on the vLLM blog: Finish RL Training Faster — Bitwise-Consistent, High-Performance, Agent-Driven
Same weights don't guarantee the same policy: inference optimizations can change the logprobs that training recomputes.
We make rollout and training bitwise identical while retaining high-performance inference paths. Here's how 🧵
vllm.ai/blog/2026-10-14-trai…
PyTorch retweeted
First @PyTorch Madrid meetup! On to many more!
madrid.pytorch.es
At our first #PyTorchMadrid meetup, @SergioPaniego explored TRL + OpenEnv for agent post-training!
Made me think of @goose_oss from @AgenticAIFdn 👀 Open source agent harnesses can also play a role in RL training helping models learn from tool use 💡
PyTorch retweeted
Join me at the @PyTorch Conference in San Jose next week Oct 20-21 hubs.la/Q04y-n1M0. Use promo code PCINVITE to get 50% off your ticket!
PyTorch retweeted
See you at PyTorch Conference NA in San Jose, October 20–21!
Get 50% off tickets with code PCINVITE: events.linuxfoundation.org/p…
PyTorch Ambassador and #PyTorchCon North America 2026 program committee member Masahiro Hiramori (@mshrh3), @ME_JP_official, will be following work across on-device AI, efficient inference, voice agents, and machine learning compilers at this year’s conference.
He's also looking forward to exchanging ideas with other developers and seeing what the broader PyTorch community is building.
Register for PyTorch Conference North America 2026: hubs.la/Q04v4SL60
PyTorch retweeted
We’ll be in San Jose for @PyTorch Conference North America Oct 20 - 21.
🎤 Talks on Triton, MoE fine-tuning + model customization
🤖 Booth demos + challenges
🍻 AI Infra Night with @dstackai, @SGLang (@lmsysorg)
Register: 🔗 luma.com/6j69xyal
#PyTorchCon #PyTorchFoundation
PyTorch retweeted
Enabling PyTorch to train any model on any chip in any cloud for any agent is a ridiculously ambitious goal, and these open source community efforts to build CI for testing accelerators are key.
Open source is not only the best way to solve this problem, it’s the only way.
Keeping out-of-tree accelerators aligned with a fast-moving ecosystem is no small task.
In a new community blog, contributors from @IBM and @RedHat share how they built Torch Spyre on top of PyTorch's Cross-Repository CI Relay (CRCR) to tackle compatibility testing at scale. In the blog they also share testing and workflow patterns that could benefit accelerator developers across the ecosystem.
Read the full technical deep dive here: bit.ly/46XkjGi
@mehant1
PyTorch retweeted
We're excited to have a strong vLLM presence at #PyTorchCon North America this year.
🔷 @simon_mo_ , vLLM core maintainer and Co-founder / CEO of @inferact, will give the keynote on scaling open frontier inference infrastructure
🔷 vLLM core maintainer @nickhill33 and George Novack will be at the "Meet the Developers of vLLM"
🔷 vLLM maintainers @tms_jr, Lucas Wilkinson, and Joseph Groenenboom from @RedHat_AI will be giving talks on Agentic Inference and Attention in vLLM.
Thank you to @PyTorch for highlighting the community's work!
vLLM (@vllm_project) is a high-throughput, memory-efficient inference and serving engine for LLMs. At #PyTorchCon North America, you’ll find vLLM-related work throughout the program, from Simon Mo’s keynote to technical sessions and posters covering LLM inference and serving.
@simon_mo_ will present the keynote “vLLM Update: Scaling Open Frontier Inference Infrastructure,” covering improvements to vLLM’s core architecture and major optimizations in KV cache management and GPU kernels.
Across #PyTorchCon, technical sessions dig into vLLM-related inference, including attention, KV cache management and transfer, disaggregated serving, elastic expert parallelism, scaling across hardware without forks, and more.
"Meet the Developers of vLLM" will feature George Novack and Nick Hill. Posters cover additional vLLM-related work on custom accelerators, Trainium, expert parallelism and RDMA KV-cache transfer, multi-chip KV-cache transfer, tier-aware routing, and more.
Explore the vLLM sessions: events.linuxfoundation.org/p…
PyTorch conferences are the open source AI community’s town square, where what’s next gets decided. Register for PyTorch Conference North America, October 20–21 in San Jose: hubs.la/Q04vK-VQ0
PyTorch retweeted
Join the PyTorch Community at San Jose Convention Center this October 20th and 21st!
At #PyTorchCon North America 2026, Sudhanshu Shrivastava, Graduate Student Researcher, Electrical and Computer Engineering, @ucdavis, will present a federated learning case study in glaucoma imaging using 5,550 color fundus photographs from nine datasets across seven countries.
Sudhanshu will discuss how federated learning enables collaborative medical imaging research without data centralization, with practical lessons on site-specific fine-tuning, cross-site generalizability, and multi-site learning.
Join us in San Jose on October 20-21: hubs.la/Q04v4SL60
#PyTorchCon
PyTorch retweeted
PyTorch is making agent brains and that includes 🤖 of course
Hardware-Aware AI: Building Agentic Systems from Cloud to Edge with PyTorch, ExecuTorch
AI agents are moving beyond chat interfaces and onto physical devices. In her upcoming session on Hardware-Aware AI at PyTorch Conference North America 2026, Kavya Sri Chennoju from @Arm will demonstrate how PyTorch, ExecuTorch, and Arm Device Connect work together to deploy AI agents safely onto edge hardware such as robot arms and wearables.
Join the open source AI community in San Jose, October 20-21: hubs.la/Q04v4SL60
#PyTorchCon
PyTorch retweeted
We’ve taught a generation of students how to use AI. Now we need to teach the next generation how to engineer it.
That means understanding what’s underneath the abstractions, not just calling the APIs.
That’s why we built Tiny🔥Torch.
Don’t just import PyTorch. Build it. 🔥
We’re excited to be working toward bringing TinyTorch into the PyTorch ecosystem. More to come! 🚀
Every mature systems project eventually needs a teaching version.
TinyTorch is a free, open source curriculum where you build a working machine learning framework from scratch, tensors through transformers, using PyTorch’s own API in pure Python.
It requires no GPU, runs on a 4 GB laptop, and covers 20 hands-on modules designed to give developers, students, and engineers a complete mental model of PyTorch internals.
Read the full technical breakdown here: bit.ly/4ArNTRO
@profvjreddi
PyTorch retweeted
Going to @PyTorch Conference in San Jose next month? @CrusoeAI and we are hosting an evening on day one, October 20, 6:30 PM, right after the sessions.
We're gathering GPU experts, AI researchers, AI infra engineers, and anyone into AI infra and heterogeneous AI compute.
Space is limited: luma.com/6j69xyal
PyTorch retweeted
Join us at Graphcore London for the London PyTorch Meetup!
📅 16 Sept, 6–9pm
🎤 Talks from Arsalan Uddin, Andrew Fitzgibbon and the wider PyTorch community
🍕 Food, drinks and networking
Register: luma.com/e999291v
#PyTorch #LondonTech
PyTorch retweeted
Accelerating Open Intelligence is the theme of #PyTorchCon in San Jose this year and we’ve got the speakers lined up to talk about it
From research prototypes to production serving across heterogeneous hardware, PyTorch Conference North America 2026 brings the core developer community together this October 20-21 in San Jose.
Sessions will cover native PyTorch hardware integrations, agentic workflows, dynamic shape dynamic compiler optimization, high-performance kernel design and more.
Featured speakers include:
@AWS: Maen Suleiman
@AMD: Liz Li, Xiaohu Guo, Shekhar Pandey
@googlecloud /@Google : Bill Jia, Qi Zhou
@Huawei: Jing Li, Qi Guo
@huggingface: Sayak Paul
@intel: Whitney Tsang, Artur Fierka
@Meta: Oguz Ulgen, Dunfan Lu, Jason Ansel, Elias Ellison, Driss Guessous, Colin Taylor, Angela Yi, Jane Xu, Simon Layton, Angel Li, Richard Zou, Yidi Wu, Laith Sakka
@nvidia: Michael Goldfarb, Guray Ozen, Daniel Galvez
Rebellions: Minwook Ahn
@RedHat: Sean McGovern, Chris Leonard
Core Automation: Mark Saroufim
@CrusoeAI: Suman Debnath, JanakiRam Goteti
d-Matrix: Tristan Webb
Lemurian Labs: Jay Dawani
@Modular: Stefan Lindall
Today is the last chance to register for a standard ticket - join us for PyTorch Conference North America 2026 and stay for AGNTCon + MCPCon that same week: bit.ly/464FTbp
Read the Hardware Acceleration & Compute Infrastructure Sessions guide: bit.ly/4yoK5z2
#PyTorchCon
PyTorch retweeted
Open source powers every layer of the AI software stack—from agents and models to inference, training and cloud infrastructure.
At #OSSummit Korea, Linux Foundation CEO Jim Zemlin explains how open collaboration is making AI faster, more affordable and more accessible.
Watch: youtube.com/watch?v=7Y7HuOzw…
PyTorch retweeted
Naturally @tobi @ShopifyEng @MParakhin are leading the way, but every company will do this:
1) take open weight models like @Alibaba_Qwen from @AlibabaGroup (trained with @PyTorch)
2) fine tune to make small specialized intelligence models for company specific work
3) Profit
PyTorch retweeted
If you like GPU kernels you’re going to love #PyTorchCon
And don’t miss @marksaroufim of @GPU_MODE fame who will be giving a keynote!
⚙️ Performance starts here. The Kernel Engineering Track at #PyTorchCon North America (Oct 20-21 in San Jose) explores compilers, custom kernels, optimization, and the low-level technologies that make AI run faster.
Learn more: bit.ly/4ybNelt
📅 Full Schedule: bit.ly/3Ra1oUx
🎟️ Join us! bit.ly/4sh3DSw
PyTorch retweeted
Can’t wait to kick off PyTorch Conference North America keynotes on October 20th in San Jose!
Keynote line up: hubs.la/Q04v5n1j0
Register: hubs.la/Q04v4SL60
#PyTorchCon