Our local LLMs in action
These are the local open-source models we currently rely on – all running on our own infrastructure, in our office basement.
Reasoning & coding
The thinkers: complex analysis, business logic and help with programming.
deepseek-v4:flash
Flagship: analysis, booking logic, complex coding
DeepSeek AI (CN)
~102 GB RAM
MIT
kimi-linear:48b
Everyday sprinter, long documents & context understanding
Moonshot AI (CN)
30 GB RAM
MIT
qwen3-coder:30b
Coding specialist for fast iterations & agent tasks
Alibaba / Qwen (CN)
18 GB RAM
Apache 2.0
qwen3.6:35b
Mid-range reserve
Alibaba / Qwen (CN)
23 GB RAM
Apache 2.0
Vision & documents
The eyes: understanding images and turning scans into usable text.
qwen3-vl:32b
Detailed image understanding: screenshots, diagrams, receipts
Alibaba / Qwen (CN)
20 GB RAM
Apache 2.0
qwen3-vl:8b
Fast vision variant for simple image tasks
Alibaba / Qwen (CN)
6,1 GB RAM
Apache 2.0
gemma4:31b
Image input + polished writing
Google
19 GB RAM
Gemma license
deepseek-ocr
PDF/scan → Markdown
DeepSeek AI (CN)
6,7 GB RAM
MIT
Retrieval & search
The memory: finds the right content in large data sets.
qwen3-embedding:8b
Vectors for similarity search
Alibaba / Qwen (CN)
4,7 GB RAM
Apache 2.0
Our infrastructure
This is where our local models run.
Hardware
MacBook Pro 16" M5 Max, 128 GB RAM.
Access & security
Cloudflare Tunnel to the local MacBook.
Power
UPS Ubiquiti UniFi.
Usage
How intensively our models are currently in use.
21'243
Tokens this month
Input
21'243
Output
0
18
Requests this month
Archive
Models we've replaced – for the record.
Reasoning & coding
| Old model | Replaced by |
|---|---|
| qwen3.5:122b | deepseek-v4:flash |
| qwen3.6:35b-a3b | kimi-linear:48b |
| qwen3.6:27b | qwen3.6:35b |
| qwen3.5:9b | kimi-linear:48b |
| qwen3.5:4b | kimi-linear:48b |
Vision & documents
| Old model | Replaced by |
|---|---|
| gemma4:12b | qwen3-vl:8b |
| gemma4:e4b | qwen3-vl:8b |
Retrieval & search
| Old model | Replaced by |
|---|---|
| qwen3-embedding:4b | qwen3-embedding:8b |
| qwen3-reranker:8b | — |