DeepSeek V4.1 Flash and the 890 bytes that matter for agents
Live on Helmcode, replacing V4 Flash at no extra cost. It redesigns inference for a workload that keeps growing: agents that read far more than they write.
Architecture
7 posts
Build your own Granola with open models
Record and transcribe your meetings with open models, turn them into structured data, and build a searchable memory of every conversation you have had.
Does building your own infrastructure to run open models pay off? We did the maths
An 8x H200 node serving GLM-5.2 costs €25,250 a month before it serves a single token. The full numbers, the break-even, and when owning the hardware wins.
Cordis: the paper behind the DeepSeek Harness architecture
The five theorems in the Cordis paper, the plugin framework behind DeepSeek Harness, explained in plain language and with what already runs in production.
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.
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.
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: