AI · alternatives · 2026
24 alternatives to L9gpu – GPU telemetry that ties each GPU to the K8s pod or Slurm job
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
L9gpu is a GPU telemetry tool that connects GPU usage data directly to the Kubernetes pods or Slurm jobs running on those GPUs. It is designed for teams managing GPU infrastructure who need visibility into which… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
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 →
- 2
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 →
- 3
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 →
- 4CG
vEdge is a GPU cloud compute platform making computing affordable and accessible.
2021 · gpu.land · its alternatives →
- 5
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 →
- 6
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 →
- 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
dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters.
2024 · dstack.ai · its alternatives →
- 9
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 →
- 10
A pipeline that translates Rust GPU code into formal Coq models, as a foundation for memory model proofs - neelsomani/vericuda
2025 · github.com · its alternatives →
- 11GA
2016 · erkaman.github.io · its alternatives →
- 12IM
2023 · vram.asmirnov.xyz · its alternatives →
- 13
Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization - RahulSChand/gpu_poor
2023 · github.com · its alternatives →
- 14
Manage your GPUs across NVIDIA, AMD, Intel, and Apple Silicon systems. - treadiehq/gpu-kill
2025 · github.com · its alternatives →
- 15
This is a GPU "software" raytracer (i.e. using manual ray-scene intersections and not RTX) written using the WebGPU API that renders glTF scenes. It supports many materials, textures, material & normal mapping, and heavily relies on multiple importance sampling to speed up convergence.
2024 · github.com · its alternatives →
- 16
An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
- 17
GPU Raytracer from scratch in C++/CUDA. Contribute to jan-van-bergen/GPU-Raytracer development by creating an account on GitHub.
2021 · github.com · its alternatives →
- 18
Compare GPU rental prices across cloud providers
7d ago · gpu.context.dev · its alternatives →
- 19
Janus is a API router for AI models written in Go and has a Vulkan Model runner - Vibra-Ingenn/Janus
22d ago · github.com · its alternatives →
- 20
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 →
- 21
cuTile Rust provides a safe, tile-based kernel programming DSL for the Rust programming language. It features a safe host-side API for passing tensors to asynchronously executed kernel functions. - NVlabs/cutile-rs
Jun 2026 · github.com · its alternatives →
- 22
Simple scheduler for running jobs on GPUs. Contribute to ExpectationMax/simple_gpu_scheduler development by creating an account on GitHub.
2019 · github.com · its alternatives →
- 23
100% bootstrapped new startup. It lets you fine tune Mistral-7B and SDXL. In particular, for the LLM fine tuning we implemented a dataprep pipeline that turns websites/pdfs/doc files into question-answer pairs for training the small LLM using an big LLM. It includes a GPU scheduler that can do finegrained GPU memory scheduling (Kubernetes can only do whole-GPU, we do it per-GB of GPU memory to pack both inference and fine tuning jobs into the same fleet) to fit model instances into GPU memory to optimally trade off user facing latency with GPU memory utilization It's a pretty…
2023 · docs.helix.ml · its alternatives →
- 24
Hi HN, I built PantheonGPU because I wanted a better way to answer a simple question: is this GPU actually healthy and performing the way it should? A GPU can show normal temperatures and utilization and still be underperforming, unstable under certain workloads, or have memory, PCIe, or configuration issues. PantheonGPU actively tests the GPU instead of only monitoring telemetry. It currently includes 45+ tests covering compute, tensor workloads, memory, cache, PCIe, thermals, stability, and AI/LLM inference. It supports both NVIDIA CUDA and AMD ROCm. I’m also exploring a larger use…
Aug 2026 · pantheongpu.com · its alternatives →
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- Attaching to a virtual GPU over TCP alternatives
- Utilyze – an open source GPU monitoring tool more accurate than nvtop alternatives
- Cloud GPUs for Deep Learning – At 1/3 the Cost of AWS/GCP alternatives
- Oblivus GPU Cloud – Affordable and scalable GPU servers from $0.29/hr alternatives
- Cerebrium 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 →