Life & fun · alternatives · 2026
24 alternatives to Running Jupyter Notebooks on a GPU on AWS or Google Cloud
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Running Jupyter Notebooks on a GPU on AWS or Google Cloud launched in 2023; newer entries below may have overtaken it.
- 1
Jupyter notebooks you can run on free cloud GPUs
2019 · its alternatives →
- 2
Compare GPU rental prices across cloud providers
7d ago · gpu.context.dev · its alternatives →
- 3
crunr ▲106Launch and run any compute job on AWS with 1 command
May 2026 · crunr.com · its alternatives →
- 4
2020 · starboard.gg · its alternatives →
- 5TC
Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
2022 · tensordock.com · its alternatives →
- 6FH
Hi, This is Dan and Genevieve from Burstable AI. We've iterated and made a 45 degree pivot, taking what we learned from developing burst (https://news.ycombinator.com/item?id=28191459) to introduce a cloud service that provides access to a GPU-enabled machine using Jupyterlab to provide notebooks, shell access, and a code/text editor. GPU access is measured and the first 50 hours are free. This is *not* a platform to do crypto mining or run weeks of model training for free. We are focused on the R & D phase of modern AI/ML, where developers/scientists are…
2022 · cloudburst.host · its alternatives →
- 7
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 →
- 8
Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://oblivus.com/cloud - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be…
2023 · oblivus.com · its alternatives →
- 9
Modal Notebooks▲140High-performance, collaborative GPU notebooks in the cloud
2025 · modal.com · its alternatives →
- 10
Hi HN! Last year, we shared marimo [1], an open-source reactive notebook for Python with support for execution through WebAssembly [2]. We wanted to share something new: you can now run marimo and Jupyter notebooks directly from GitHub in a Wasm-powered, codespace-like environment. What makes this powerful is that we mount the GitHub repository's contents as a filesystem in the notebook, making it really easy to share notebooks with data. All you need to do is prepend 'marimo.app' to any Python notebook on GitHub. Some examples: - Jupyter Notebook:…
2025 · docs.marimo.io · its alternatives →
- 11
Contribute to Mega4alik/ollm development by creating an account on GitHub.
2025 · github.com · its alternatives →
- 12
Self-host AI/ML with the world's cheapest GPU cloud
2025 · thundercompute.com · its alternatives →
- 13
TensorFlow for AWS. Contribute to dsys/tensorflow development by creating an account on GitHub.
2015 · github.com · its alternatives →
- 14
Run your Jupyter notebooks on a schedule with three clicks
2019 · chromewebstore.google.com · its alternatives →
- 15
iwant▲70Find available GPUs and host open models in one command
15d ago · github.com · its alternatives →
- 16IM
2022 · paylesstoaws.com · its alternatives →
- 17
Build your own cloud in just 20 seconds while avoiding bugs
2015 · its alternatives →
- 18AC
2021 · id.rsa.pub · its alternatives →
- 19KG
Borrow GPU compute from another device, with permission
Sep 2026 · kanverse-borrow.kanthrfp.workers.dev · its alternatives →
- 20SJ
We get asked whether we support Notebooks on Unweave all the time. So, we put together a serverless Jupyter Lab Portal built on top of Unweave. You can choose from 5 different GPUs or use CPU only. The lab comes with an `uwstore` folder at the root of the repository. Any files you add there will be persisted across multiple sessions. We've pre-loaded all labs with a set of commonly used ML dependencies. If you'd like to add additional dependencies, you can install them directly in the Jupyter Lab and save them to a `requirements.txt` or `environment.yml` file. Unweave will automatically…
2022 · playground.unweave.io · its alternatives →
- 21
massively parallel experimentation with Jupyter and AWS Lambda 🐑🌩📒 - antimatter15/eigensheep
2019 · github.com · its alternatives →
- 22
I'm continuing to improve my RunsOn tool for launching self-hosted runners for GitHub Action on AWS, this time with support for any GPU-enabled instance type from EC2, and using the official Deep Learning AMIs as the runner image. Much cheaper than the official GitHub Actions runners, and accessible on any GitHub plan.
2024 · runs-on.com · its alternatives →
- 23PC
2023 · docs.cloud.ploomber.io · its alternatives →
- 24
Jun 2026 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →