GLM 5.2 orchestrates, DeepSeek V4 Flash executes
How to design multi-model systems where one open LLM plans, another executes, and the context they hand each other stays efficient.
All Posts
15 articles
GLM 5.2 is now available on Helmcode
GLM 5.2, the 744B MIT open model, now runs on Helmcode's European infrastructure with zero logs and a flat rate of 150 euros a month.
The AI Act explained: what actually applies in August
The calm version of the AI Act: which obligations really apply to you from 2 August, which ones the Omnibus moved, and what to have ready.
Talk to any document: how Knowledge works in Helmcode
Upload your documentation once or connect a Git repository, then ask it from the chat. Every answer cites the document it came from.
Which GPU do you need to serve AI models
FP8, NVFP4, H200, B200: what each NVIDIA generation accelerates in hardware, how much VRAM your model needs, and which GPU to buy. With real production data.
How to Generate Professional Images in Helmcode: The Complete Prompting Guide
The difference between an image that screams 'AI' and a professional one isn't the model, it's the prompt. The complete guide to generating great images in Helmcode.
hello, world: borja pérez here_
New hire at Helmcode: communication, marketing and community. Who I am, what I'm here to do, and what we're planning for the NaN community.
Qwen3.6 on an RTX PRO 6000 at full scale
How we moved Qwen3.6-35B to NVFP4 on a single RTX PRO 6000, why it kept crashing, and the one-line fix that turned out to be a cuDNN bug, not a vLLM bug.
NaN: the community's first month in numbers
117 billion tokens, 3.68 million requests, 21 countries, and 99.98% uptime. NaN is a community of builders with its own inference infrastructure and a private platform to deploy apps and agents.
AI for Dummies - Part 1
In this post we'll learn what parameters and quantization are, so we can figure out how much space AI models take up.
How to set up an inference server to serve AI models
In this post I'll walk you through how the community's inference servers are set up: the hardware we use, the stack we run, and the models we serve.
Claude Code for DevOps
I've spent several hours over several days documenting and optimizing my entire local environment so I can "mechanize" the work I do every day managing infrastructure for multiple startups.
Clawd/Molbot/OpenClaw: Reflections and lessons learned
This post isn't meant to be a guide on how to use Clawd, but rather a look at how we're rolling it out at Helmcode to have an AI Agent that helps us with our day-to-day work managing the Cloud infrastructure of multiple startups.
Kubernetes for devs (1/2)
Kubernetes is one of the most widely used infrastructure tools among companies, and it has become the standard for running containerized applications at scale all over the world.
Moving Down from Serverless to Kubernetes
Before we start, a bit of context. The infrastructure is hosted on AWS and the architecture was based on Serverless services: