Dev tools · alternatives · 2026
24 alternatives to GPUSprint
Measure GPU utilization across vendors NVIDIA, AMD, TPUs ...
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
We built installable software for Windows & Linux that makes any remote Nvidia GPU accessible to, and shareable across, any number of remote clients running local applications, all over standard networking.
2022 · github.com · its alternatives →
- 3
Accelerating open machine learning research with Cloud TPUs
2017 · sites.research.google · its alternatives →
- 4
We developed a tool to trick your computer into thinking it’s attached to a GPU which actually sits across a network. This allows you to switch the number or type of GPUs you’re using with a single command.
2024 · thundercompute.com · its alternatives →
- 5
GPU Observability with workload attribution. One OTLP agent per node ties hardware metrics (NVIDIA, AMD, Intel Gaudi) to the K8s pod or Slurm job burning the GPU. - last9/gpu-telemetry
Jul 2026 · github.com · its alternatives →
- 6
The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com · its alternatives →
- 7TC
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 →
- 8
Compare GPU rental prices across cloud providers
6d ago · gpu.context.dev · its alternatives →
- 9
Insights on GPU and AI infrastructure from Arc Compute. Read hardware deep-dives, deployment playbooks, and analysis of where the AI compute market is heading.
2021 · arccompute.com · its alternatives →
- 10
Cerebrium▲300If you haven’t noticed, GPUs are scarce right now. The global boom in inference has demand growing faster than supply can keep up, and at Cerebrium ...
2024 · cerebrium.ai · its alternatives →
- 11
The world’s most powerful chip’ for AI
2024 · nvidia.com · its alternatives →
- 12CG
vEdge is a GPU cloud compute platform making computing affordable and accessible.
2021 · gpu.land · its alternatives →
- 13
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 →
- 14
Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…
2023 · shadeform.ai · its alternatives →
- 15
- 16
Janus is a API router for AI models written in Go and has a Vulkan Model runner - Vibra-Ingenn/Janus
21d ago · github.com · its alternatives →
- 17
Supercharge gaming with DLSS 4, NVIDIA Studio, and AI
2025 · nvidia.com · its alternatives →
- 18
- 19
Accelerate Your Workloads with GPUs
2025 · cyfuture.ai · its alternatives →
- 20
Track&predict GPU power availability across cloud platforms.
2025 · gpusignals.com · its alternatives →
- 21
- 22
GPU cloud computing at unbeatable cost efficiency
2020 · genesiscloud.com · its alternatives →
- 23
- 24IM
2022 · paylesstoaws.com · its alternatives →
Also compare
- Tune LLaMa3.1 on Google Cloud TPUs alternatives
- Software for Remote GPU-over-IP alternatives
- Tensorflow Research Cloud alternatives
- Attaching to a virtual GPU over TCP alternatives
- L9gpu – GPU telemetry that ties each GPU to the K8s pod or Slurm job alternatives
- Utilyze – an open source GPU monitoring tool more accurate than nvtop alternatives
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 →