Projects done with substantial help of AI tools have "Slop" in their name. Other projects never touched by AI.
Of course "AI" is a great to get stuff done fast, but it's quite dumb and have to be very carefully guided.
Some people compare it to a parrot facerolling on the keyboard.
LLM is not even a neural network, it's an autocomplete dictionary for T9 text predictions just like in old phones.
Repeatedly tap on your phone's text predictions - this is the current state of "AI".
Now with proper expectations you're ready to start building.
BTW, if you don't want to feed money to cloud services - start with your own local LMStudio/ComfyUI machine.
All you need is 16GB GPU and 32GB RAM to start. CPU doesn't matter, it's really that cheap.
Setup takes 3 weeks of pure suffering and you're ready for a true AI future, it'll pay off in less than a year.
Our videocards now can not only run games, but write somewhat useful code. That's pretty cool right?
And if part of your job or pipeline can actually be replaced by a parrot, maybe it should be replaced.
Think of writing and updating tests. If you're blank-staring at the wall right now, you get it.
But don't let LLMs think for you or build an architecture - it's all random bloated garbage.
Sweet spot: 32-40GB GPU VRAM + 64GB RAM
Qwen 3.8 27B ~250k - unsloth/qwen3.8-27b@q4_k_s (temp 0.1, top k 40, no rep penalty)
Gemma 4 31B ~100k - unsloth/gemma-4-31b-it@q5_k_xl (temp 0.3, top k 40, rep penalty 1.1)
Xortron ~200k - xortron.criminalcomputing.2026.27b.next@q6_k (temp 0.3, top k 40, rep penalty 1.1)
Mostly usable: 24GB GPU VRAM + 64GB RAM
Qwen 3.8 27B 100k - unsloth/qwen3.8-27b@iq3_s (temp 0.1, top k 40, no rep penalty)
Gemma 4 31B QAT 32k - unsloth/gemma-4-31b-it-qat@q4_k_xl (temp 0.3, top k 40, rep penalty 1.1)
Xortron 40k - xortron.criminalcomputing.2026.27b.next@q5_k_m (temp 0.3, top k 40, rep penalty 1.1)
Barely usable: 16GB GPU VRAM + 32GB RAM
Qwen 3.8 27B 32k - unsloth/qwen3.8-27b@iq3_xxs (temp 0.1, top k 40, no rep penalty)
Xortron 32k - xortron.criminalcomputing.2026.27b.next@iq3_xs (2 layers on CPU, Q8 KVCache, temp 0.3, top k 40)
Old videocard or laptop option, pure suffering: 8-12GB GPU VRAM + 32GB RAM
Gemma 4 12B QAT ~80k - unsloth/gemma-4-12b-it-qat@q4_k_xl (temp 0.1, top k 40, rep penalty 1.1)
--
Global settings: Min P Sampling 0.05, Top P Sampling 0.95.
This is how these settings work (yeah I know, pretty much every IT video).
Model developers put default settings tailored for high scores in benchmarks. Those are really bad for actual work.
I use very low temperatures to avoid tool use typos/screwups, since I use LLMs mostly for routine like refactoring.
To avoid Gemma 4 thinking bugs, use "<|channel>" as your reasoning start string, not "<|channel>thought".
Disable Unified KV Cache and set Max Concurrent Prediction to 1 to save memory.
If you can get anything done on a small model, get a dual-16GB-GPU setup. I use dual RTX 4000 Ada for 40GB VRAM.
Every 8GB extra VRAM is an astronomic leap in quality. 12GB model is not even close to other models.
Use OpenAI-compatible API to connect to LM Studio. The https://zed.dev/ seems to be best open-source agentic IDE.
Here are jinja templates for LM Studio and Zed. Very tedious to get right.
Put Responses MUST be terse and short. in a rule or system prompt, or use my PortableAgent ruleset.
Vision consumes a lot. Use Q8_0 or BF16 .mmproj files so you don't have to blind the model completely.
- com.bananaparty.arch - Architecture alternative to Singletons and DI Containers.
- com.bananaparty.unislop - Minimalistic portable Unity MCP server designed for coding.
- com.bananaparty.touchinput - Comfortable abstraction with gesture support for unity's touches.
- com.bananaparty.input.tvremote - Fully cross-platform input library for TV remotes.
- ComfyUI-Enhancement-Utils - PC resource monitor and execution follower.
- ComfyUI-SloppyAudio - Audio editing tools based on SoX and BS-RoFormer.
- PortableAgent - Rule prompt for local LLMs like Gemma and Qwen. Read less slop and get much better results.
- ComfyUI-SloppyInstall.bat - Simplified pip install -r "requirements.txt" for custom nodes in portable ComfyUI.
- SloppyServer.bat - Single file local/Wi-Fi server for debugging multithreaded mobile Unity WebGL builds.