u/tomByrer

To Whomsoever it May Concern,

The individual behind the Heretic Free Software Project (henceforth called "Heretic", notwithstanding unrelated entities of the same name) has been served a notice by a legal services provider representing Meta Platforms, Inc. (henceforth called "Meta"), via the digital communications medium variously known as Internet Mail, Electronic Mail, or simply "email".

The Heretic Project conducts its affairs in full compliance with applicable laws, regulations, rules, guidelines, opinions, and hunches. Following the commendable example set by the renowned heretic Galileo Galilei in 1616, we are recanting the relevant materials, namely derivatives of Meta's "Llama" Artificial Intelligence language models, and have removed the same from all model weight repositories controlled by the Heretic Project.

We are grateful to Meta and its legal representatives for the opportunity to better align ourselves with the agenda of the global corporate oligarchy. The Llama model family ranks among the 200 best language models available today, trailing only 168 other models from 23 competitors on the LM Arena leaderboard, and Meta's concern for that asset naturally outweighs scientific freedom, as well as the legally and ethically dubious circumstances under which those models were created in the first place, regarding which, ironically, Meta is currently facing lawsuits and investigations in multiple jurisdictions around the world.

On a completely unrelated note, the Heretic Project is diversifying its infrastructure, and now has an official Codeberg mirror at https://codeberg.org/p-e-w/heretic, hosted in Germany. Additional mirrors are planned. We are also actively working to implement technological measures that will preserve access to models created with Heretic without depending on any specific service provider. We are proud to be part of this journey as we navigate an evolving global regulatory landscape, and work with stakeholders from diverse institutional backgrounds to ensure that Artificial Intelligence remains safe, culturally appropriate, and controlled by those who have always known what is best for humanity. If you, too, would like to share in this exciting adventure, please join us!

Sincerely, p-e-w, Chief Heretic

Alex digs deeper this time, inspired by this channel:
https://www.youtube.com/@Protorikis

TL;DW:
Analysing 1 large code file, first split in half, then full =
llama.cpp serving GGUF was decent, Ollama MLX+NVFP4 was faster.
MLX LM was good for smaller files (smaller context) but crashed the Mac on a bigger file.

Hey guys, you can now run open LLMs in Claude Code, Codex and OpenClaw via Unsloth's API inference endpoint and we made lots of tutorials for it!

Use Gemma 4 and Qwen3.6 GGUFs for local agentic coding on 24GB RAM.

Run with self-healing tool calls, code execution, web search via the Unsloth API endpoint and llama.cpp.

Guide: https://unsloth.ai/docs/basics/api

Unsloth makes it easy to deploy a fast API inference endpoint that provides:

• Self-healing tool calling, which helps reduce broken or malformed tool calls by 50%
• Code execution support, allowing Bash and Python execution for more accurate code outputs.
• Advanced Web search that visits and actually reads webpages to gather in-depth info.
• Automatic inference settings for GGUF models (temp, top-k etc.)

Please update Unsloth to leverage this new update and let us know if you have any feedback. Thank you!!

The title "RTX 5090, Mac Studio, or DGX Spark? I tried all three." is deceptive; he only talks about hardware 20% of the time. He spends more time on use-cases, then a quick touch on model families for each use case.

He also skipped over a few things, like VRAM vs system RAM vs shared iGPU VRAM, how much harddrive space you'll need for all your models, if you want to do image/video/OCR.

Note: not my video, I don't even own any AMD anything.
But many on here with AMD or considering AMD would like to know.
& I'm sure he'd like support; he's working hard to help AMD folks improve their AI capabilities.

I built a split keyboard with a 55mm trackball, and honestly… I can’t stay away from this thing anymore.

ZMK firmware, a lot of switches using Charlieplexing, a 55mm trackball, rotary encoders on both sides, and a 4‑way + push switch. It’s absolutely packed with features.

I originally designed and used a wired version called Mooose, but after moving to ZMK and making it possible to go wireless, I added "Free" to the name to reflect the freedom from cables.

Switches: keygeek Y3, Kailh Ghost, and others Keycaps: awekeys Air, etc.

Came across hipfire the other day. It's a brand new inference engine focused on all AMD GPU's (not just the latest).

Github.

It uses a special mq4 quantization method. The hipfire creator is pumping out models on huggingface.

I don't know enough about quantization to know how good these quants are in terms of quality, but as an RDNA3 aficionado I'm happy AMD is getting some attention.

Localmaxxing is a new LLM benchmarking site, and shows some pretty dramatic speedups for hipfire inference.

Edit: I should have just said hipfire - I don't think this is connected to AMD officially.