TPUs vs. GPUs and why Google is positioned to win AI race in the long term | Hacker News
To quote The Next Platform: "An Ironwood cluster linked with Google’s absolutely unique optical circuit switch interconnect can bring to bear 9,216 Ironwood TPUs with a combined 1.77 PB of HBM memory... This makes a rackscale Nvidia system based on 144 “Blackwell” GPU chiplets with an aggregate of 20.7 TB of HBM memory look like a joke."
Understanding TPUs vs GPUs in AI: A Comprehensive Guide
Explore the differences between Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs) in AI.
Rohan Paul on Twitter / X
Google is trying to win AI by making compute cheap, not by beating Nvidia on raw speed.Nvidia sells GPUs to clouds with a big 70%+ margin that sits on top of manufacturing and R&D cost and raises cloud prices.Google builds TPUs for itself at near manufacturing cost, adds no… https://t.co/aSgWRf0HY7 pic.twitter.com/T3Fzc6czwg— Rohan Paul (@rohanpaul_ai) November 25, 2025
We're launching two specialized TPUs for the agentic era.
The eighth generation of Google’s TPU includes two specialized chips that will power the future of AI.
TPU architecture | Google Cloud Documentation
Tensor Processing Units (TPUs) are application specific integrated circuits (ASICs) designed by Google to accelerate machine learning workloads. Cloud TPU is a Google Cloud service that makes TPUs available as a scalable resource.
Our eighth generation TPUs: two chips for the agentic era
An overview of Google’s eighth generation TPUs, built for the agentic era.
Expanding our use of Google Cloud TPUs and Services
Announcing a dramatic increase in Anthropic's compute resources
GPU Pricing — Live Platform Rates | Vast.ai
Live GPU pricing on Vast.ai. Prices set by supply and demand across 40+ data centers. On-demand, interruptible, or reserved — find the right GPU at the right price.
Chris Lattner on Twitter / X
Please don’t tell anyone: we aren’t just open sourcing all the models. We are doing the unspeakable: open sourcing all the gpu kernels too. Making them run on multivendor consumer hardware, and opening the door to folks who can beat our work.Plz keep it quiet, ok? 😉— Chris Lattner (@clattner_llvm) March 24, 2026
noname on Twitter / X
Upto 1100 tps on RTX 3090x2 for Diffusion Gemma 4 26B.Unleash this mini monster on your gpus now!If you are running nvidia gpus locally, come grab the recipe at club-3090. https://t.co/qKuFcgu1llP.S. a ⭐️ on Github is much appreciated.@googlegemma @vllm_project— noname (@malikwas1f) June 11, 2026
Small Models Have Arrived
For the past few weeks, I've been playing with gpt-5.6-luna. It is shockingly capable, fast, and smart. I regularly see it do ~100 tps, and rip around my codebase, email, and knowledge base.
213 votes, 97 comments. I have been doing some research and I found out that TPUs are much cheaper than GPUs and apparently they are made for machine…