Alternatives
Products that do what Utilyze – an open source GPU monitoring tool more accurate than nvtop does
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…
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Jun 2026 · github.com
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Jul 2026 · github.com
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Lightweight system monitor for Linux VPS. Contribute to leodeim/vpsmon development by creating an account on GitHub.
12d ago · github.com
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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…
19d ago · pantheongpu.com
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2021 · github.com
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We built, saga[1] a layer that lets smaller teams access enterprise GPU discounts through collective buying power. How it works: 1. Aggregate GPU spend across hundreds of ML teams 2. Get enterprise rates through combined volume 3. Pass savings to users, monetize via provider partnerships Technical notes: - Works at billing layer only (no access to code/data) - Supports existing cloud setups or managed GPUs - Private beta running since January, opening more spots for March - Currently seeing ~50% savings on H100s/A100s [1] https://trysaga.ai
2025 · trysaga.ai
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2021 · vktracer.com
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2016 · github.com
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Jun 2026 · github.com
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2015 · github.com
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runNburn is an Apache-2.0 Rust inference engine for quantized GGUF models that are too big for your fast memory. The core idea: weights stay file-backed (mmap), host residency stays under an explicit byte budget (--ram-budget), and GPU caches are sized from detected free/total VRAM — never from device-name presets. There is no conversion step, no sidecar cache files, no silent requantization. The GGUF on disk is the single source of truth. The result that made me want to post this: Tencent's Hy3 (295B total / 21B active sparse MoE, a single 97.8 GiB Q2_K GGUF) runs on my desktop…
Jul 2026 · github.com
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2018 · github.com
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Jun 2026 · github.com
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Sep 2025 · github.com
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Frustrated by the complexity and resource drain of multi service monitoring stacks, I built Simon. I wanted a single, lightweight dashboard to replace the heavy stack and the constant need for an SSH client for routine tasks. The result is a resource efficient dashboard in a single Rust binary, just a couple of megabytes in size. Its support for various architectures on Linux also makes it ideal for embedded systems and lightweight SBCs. It integrates: Comprehensive Monitoring: Realtime and historical metrics for the host system and Docker containers (CPU, memory, disk usage, and network…
Nov 2025 · github.com
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Hi everyone — looking for feedback on a new infrastructure project we launched called vMetal. It's a bare metal management platform for GPU clusters that handles machine discovery, PXE booting, and lifecycle management, without the OpenStack complexity. Built around Kubernetes-native workflows so you can hand it off to teams or drop it into an existing platform. A lot of the infra platforms used for this today were designed 20 years ago (VMware, OpenStack, NVIDIA BCM, MAAS, etc.), while newer tools usually solve only a small piece of the stack. Neither were built with modern GPU cluster ops…
Mar 2026 · vmetal.ai
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Out of curiosity, I put together a simple website which tracks the prices for a few variations of A100/H100 GPUs by hour broken out between spot/ondemand, form factor and provider. Specifically I was tailoring the tool towards the smaller, emerging providers like runpod, gpulist.ai, lambda labs etc. Anyone have any ideas to expand/refine it?
2024 · computeindex.michaelgiba.com
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I've made a GPU comparison site: https://gpu-prices.com/US/ Yes, there was one yesterday - I got beaten to it. This one is different in that I've put a lot of work into categorisation, so you can filter down quite precisely. For example, VRAM-per-dollar, limiting to Nvidia, and a minimum performance score allow you to find good ML GPUs. It currently supports Australia, Canada, Ireland, the UK, and the US. The tech stack is Python for data pull and static site generation then Cloudflare Pages for actually serving the site. It updates three times a day, but I could increase…
2024 · gpu-prices.com
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I wanted to share something I've been working on recently: Statum, a handy web analytics tool. https://github.com/extractumio/statum The journey began when I found myself frequently needing simple web analytics for my projects. I tried Google Analytics, especially GA4, and realized it was quite complex and, at times, not very accurate, especially when I wanted to view stats for the current day or recent hours. Then I tested a few fancy startup solution but ended up with way too expensive plans the expect me to subscribe (I'm not that rich to pay $99/month for every…
2023 · github.com
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Posted before, but wanted to share if you want an open source alternative to OpenAI fine-tuning, give Unsloth a try! Phi 3.5 was just released, and is distilled from GPT4. Unsloth makes finetuning 2x faster, uses 70% less VRAM + has no accuracy degradations. We rewrite all backprop steps and reduce FLOPs and write everything in Triton (JIT low level CUDA). If you want to own the weights after fine-tuning, give Unsloth a spin! I have free Colabs and Kaggle notebooks as well at https://github.com/unslothai/unsloth
2024 · colab.research.google.com
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