Sascha @Garage2Code
Mechanic by trade, builder by choice. Learning to code, building apps and games with AI. Joined October 2026-
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Same laptop, same model, no new parts. Qwen3.8-Flash-Next via Colibri, CPU only, measured: FP8 (8k ctx): 1.47 tok/s / int4 (32k ctx): 2.08 tok/s / int4 + Windows SSD fix: 2.80 tok/s. Almost 2x, even with 4x the context. Tuning beats buying.
New week, new goals: 1. Finish my next Python module on Coursera 2. Test 6 new versions of my fitness app on a real phone, not just the browser 3. Add micronutrients to the app Friday I'll post what actually got done.
My takeaway: no high-end GPU doesn’t mean no local AI. It means picking a model that fits your hardware, not your ego. What do you run on mid-range hardware?
So I tried a smaller model on the same laptop. Qwen3.8-Flash-Next, same tool (coli tune), measured: GLM-5.2: 0.375 tok/s Qwen3.8 int4: 3.15 tok/s That’s ~8x faster (calculated). A paragraph in ~1 min instead of ~9
Remember my Colibri test? A 744B AI model on my gaming laptop. No new GPU. No four-figure upgrade. I just added a second NVMe SSD. Result: +81% tokens per second. Sounds great. How much that helps in practice is another story.
First result is in: 0.21 tokens per second. That's about 5 seconds per token. A short answer takes around 4 minutes. 🐌 It runs, but slowly. The bottleneck isn't the CPU or GPU, it's the SSD. I have an idea how to fix that. 🔧
First result is in: 0.21 tokens per second. That's about 5 seconds per token. A short answer takes around 4 minutes. 🐌 It runs, but slowly. The bottleneck isn't the CPU or GPU, it's the SSD. I have an idea how to fix that. 🔧
✅ Colibri is now running its tuning step, measuring how to squeeze the most tokens per second out of my laptop. GLM-5.2, 744B parameters, on a gaming laptop. Fingers crossed. 🤞
There’s a tiny open-source engine called Colibri that claims to run 700B+ AI models on hardware you already own. I’m testing it on my gaming laptop: Ryzen 7 8845HS, 32 GB DDR5, RTX 4060 with 8 GB. Sharing everything: setup, speed, fails. Let’s see if it melts 🔥
@miaferrariii Couples therapy. Two sessions a week.
This account is my public logbook. I'll share progress on my apps, what I learn while coding, and how I actually use AI day to day, the wins and the mistakes. Career changer, indie dev or just curious about AI? Follow along, and feel free to say hi
Right now I'm learning Python on Coursera, so I can actually read and understand the code AI writes for me. Next step: building things on my own.
I spent years fixing cars. Now I'm building apps with AI. No CS degree, just curiosity and a lot of trial and error. Here's my story 🧵
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