Neurox – GPU Observability for AI Infra
Neurox control helm chart details. Contribute to neuroxhq/helm-chart-neurox-control development by creating an account on GitHub.
Neurox – GPU Observability for AI Infra launched on April 29, 2025 with 25 votes, #802 of 7,818 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Neurox is a GPU observability platform designed for AI infrastructure teams. It provides monitoring and visibility into GPU performance and usage across AI systems. The tool is built for engineers managing AI infrastructure who need to track GPU behavior, diagnose issues, and optimize resource allocation. Its primary function is to surface real-time data about GPU operations to help teams understand and improve their infrastructure performance.
written from the facts on this page · September 2026
From the sources
This Helm chart is designed to install Neurox. Neurox helps monitor your AI workloads running on your Kubernetes GPU cluster. Purpose-built dashboards and reports combine metrics and live Kubernetes runtime state data to help admins, developers, researchers, and finance auditors surface relevant insights. Visit our main website for information. To get started, follow the instructions on the Neurox Install page . It will guide you step-by-step to a working deployment on your Kubernetes GPU cluster. The instructions will install a free, self-hosted deployment of a single, combined Neurox Control + Workload cluster. It will contain both Control plane components as well as Workload management…from github.com
Does a similar job
all alternatives →
Cerebrium2024 · cerebrium.ai · ▲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 ...


Netmind Power2023 · netmind.ai · ▲272Hi HN, We just opened public access to Qwen3‑Coder‑480B‑A35B‑Instruct via a REST/SDK API. Why it might be interesting: - Fully open-source (Apache‑2.0): https://github.com/QwenLM/Qwen3-Coder - 480B params (35B active MoE), long context up to 1M tokens with YaRN - Matches Claude Sonnet/GPT‑4o on SWE-Bench Verified (81.6%) - Free tier: 100K tokens/month

NeuroBlockFeb 2026 · neuro-block.com · ▲120No-code AI Lab: Train models, access datasets, run inference
More ai this month
the category →



Paintings by AI models: programs run through a simulation of oil paint.
AI · 21d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 30d ago · world.pixverse.video

Source: Show HN post ↗
Launched alongside, April 2025
the whole month →
Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
Dev tools · 2025 · runpyxl.com

The Unsure Calculator is an online tool that lets you calculate with numbers you’re not sure about.
Life & fun · 2025 · filiph.github.io

https://the-pocket.github.io/Tutorial-Codebase-Knowledge/
AI · 2025 · github.com


