AI · alternatives · 2026
24 alternatives to TorchTPU
Running PyTorch Natively on TPUs at Google Scale
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…
2024 · github.com · its alternatives →
- 2
Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems. Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made…
2025 · victorpoughon.github.io · its alternatives →
- 3
Accelerating open machine learning research with Cloud TPUs
2017 · sites.research.google · its alternatives →
- 4
Forge Agent▲113Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels
Jan 2026 · rightnowai.co · its alternatives →
- 5
The light PyTorch wrapper for high-performance AI research
2020 · pytorchlightning.ai · its alternatives →
- 6
Supporting Rapid Prototyping with a PyTorch Toolkit
2018 · github.com · its alternatives →
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- 8
Research Framework for easy and efficient training of GANs based on Pytorch - torchgan/torchgan
2018 · github.com · its alternatives →
- 9
Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation. - ymcrcat/rgpu
14d ago · github.com · its alternatives →
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- 11
We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
- 12
Build and train machine learning models with Google
2017 · blog.google · its alternatives →
- 13
If Google News had a Python library. Contribute to kotartemiy/pygooglenews development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 14
Torchium▲7Torchium is the most comprehensive PyTorch extension library
2025 · vishesh9131.github.io · its alternatives →
- 15
I integrated a remote GPU execution backend into PyTorch through the same system that custom hardware accelerators get integrated into PyTorch. You can create a remote machine and obtain its CUDA device whenever you want to create or move tensors onto the remote GPU. machine = mycelya_torch.RemoteMachine("modal", "A100") cuda_device = machine.device("cuda") x = torch.randn(1000, 1000, device=cuda_device) y = torch.randn(1000, 1000).to(cuda_device) I made it reasonably performant by having most operations dispatch asynchronously whenever possible. For cases where slow performance is…
2025 · github.com · its alternatives →
- 16GA
I'm starting to implement a barebones version of pytorch in Go. The primary motivation is: 1. I want to better learn Pytorch and how it works so what better way than to just re-implement some of its core features. 2. I write mainly in Go and haven't come across a lot of ML support in Go 3. I'd rather have a Go ML service instead of spinning up additional infrastructure to just support a python ML service in my Go projects 4. Go's static typing, native concurrency (avoid GIL problem in python), efficient memory management, single binary deployment and more make it a better interface compared…
2024 · its alternatives →
- 17
Open-source AI library for fast research and deployment
2019 · github.com · its alternatives →
- 18
Hi HN, We’re a small team of OS, virtualization, and ML engineers, and after three years of development, we’re thrilled to launch the beta of our CUDA abstraction layer! We decouple the Kernel Shader execution from applications that use CUDA into a Wooly Abstraction layer. In this abstraction layer, we compile these to a new binary, and Shaders are compiled into a Wooly Instruction Set. At runtime, Kernel Shader launch events initiate a transfer of Shader over the network from a CPU host to a GPU host, where they are recompiled. Their execution is managed by Wooly Server software to achieve…
2025 · woolyai.com · its alternatives →
- 19
Lightning▲83AI code editor for PyTorch development on GPU workspaces
Oct 2025 · lightning.ai · its alternatives →
- 20
We're a group of engineers, AI/ML enthusiasts, and author of this paper https://openreview.net/forum?id=0pxiMpCyBtr who saw a closed door in AI/ML and decided to open it. This project is a PyTorch reimagining of Google's TensorFlow Lattice models, which despite being labeled open-source, were previously open in name only (you have to be a Googler to contribute). Also, side point…TensorFlow is dying https://thenextweb.com/news/why-tensorflow-for-python-is-dyi... Here's the deal: Lattice models excel in making AI interpretable—key for sectors where…
2023 · github.com · its alternatives →
- 21
Hello HN, We are pleased to introduce you graphlearn-for-pytorch (https://github.com/alibaba/graphlearn-for-pytorch), an open-source distributed graph neural network library based on PyTorch and compatible with PyG. Our library is designed to make it easy for developers to build and train large-scale graph models in a distributed environment. With graphlearn-for-pytorch, you can leverage GPUs to accelerate graph sampling and utilize UVA to reduce the overheads of feature collection. Following a scalable design, graphlearn-for-pytorch supports training GNN models on…
2023 · github.com · its alternatives →
- 22
A fast, native app for local coding agents. Amp, Claude Code, Codex, Cursor, OpenCode, Grok, and Pi — one timeline, entirely on your machine.
Aug 2026 · waku.sh · its alternatives →
- 23
A lightweight module for Multi-Task Learning in pytorch. - chrisby/torchMTL
2020 · github.com · its alternatives →
- 24
Google colab GPU access in every language - not just Python
2024 · github.com · its alternatives →
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