What I
use.

Updated 14 September 2026

Below is the hardware and software I use. For local model tests, I use the DGX Spark; how I run local LLMs on it

Local model tests

DGX Spark

Memory
128 GB unified
Compute
Grace Blackwell
Purpose
Local models + evals
Location
Hoorn
Models
Gemma-4 · Nemotron-3
On the go

MacBook Air M3

Memory
8 GB
OS
macOS
Use
Web work + writing
Vibe
Light and quiet
At home

Mac mini M2

Memory
16 GB
Screens
2× 4K
Keyboard
Apple Magic Keyboard
Mouse
Apple Magic Mouse
Desk
Sit-stand
Audio

For calls and recordings

Microphone
Rode PodMic
Setup
Desk mat + arm
Status
Works fine
Coding

Editor & terminal

Editor
VS Code (→ Cursor todo)
Terminal
Apple Terminal
AI pair
Claude Code · Opus 4.8
Plan
Anthropic Max
Theme
Default, no time for it
AI / ML

Models & stack

Hosted
Anthropic Claude
Daily
ChatGPT for simple work
Local
Gemma-4-26-4b-it
Embeddings
Qwen-Embedding-4B
Search
PGVector
Tools
MCP servers where they fit
Development

Languages & frameworks

Backend
Python (pip + uv)
Ruby
Frontend
TypeScript (npm)
Frameworks
Next.js · Vue · Astro
Ruby on Rails
Data
Supabase · Prisma
React stack
Remix / RR v7
Namesake
Django (yes, literally too)
Infra

Hosting & ops

Apps
Vercel · Fly.io
Domains
TransIP
Edge
Vercel + Supabase
This blog
TransIP + GHA
Side bot
Pi 5 with OpenClaw
Dropped

Cloud GPUs for benchmarks

With cloud GPUs, I saw too much variation between runs. Since getting the Spark, I run benchmarks on the same machine to make conditions easier to compare.

Dropped

Tooling chase

I spend less time comparing editors, adjusting themes and maintaining dotfiles. I change my tools when something gets in the way of my work.

Dropped

Notion and heavy doc tools

I keep notes in Markdown in a repository, so the text and its version history stay together.

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