Training models is gonna become the new learn to code and will be automated to a high degree Novel research is another thing and has already been automated to some extent Synthetic data might be the only thing yet to crack, matter of time Compute is the ONLY TRUE moat
@theahmadosman
-
Current SoTA LLM Ranking as of May 2026
By
–
Current SoTA LLMs Ranking GPT 5.5 > Kimi K2.6 > GLM 5.1 > Qwen 3.6 397B > MiniMax M2.7 And yes, Opus 4.7 is slop, I left Claude models out intentionally
-
Cloning Sglang Mini and using Codex with GPT-5.5 to learn inference engines
By
–
There’s too much alpha in cloning Sglang Mini and asking Codex Cli w/ GPT 5.5 to teach you how Inference Engines work through that cloned repo
-
LLM pricing per token mirrors SaaS era, buy a GPU
By
–
Charging $ per 1M tokens
Is basically the SaaS era of LLMs That’s why I keep saying Buy a GPU -
Choose Hardware First, Then the Inference Engine Follows
By
–
You don’t pick an Inference Engine You pick a Hardware Strategy Then the Engine follows Inference Engines Breakdown (Cheat Sheet at the bottom) > llama.cpp
runs anywhere
CPU, GPU, Mac, weird edge boxes
best when VRAM is tight and RAM is plenty
hybrid offload, GGUF, -
Free Hugging Face Mirror Offered If Platform Goes Down
By
–
If @huggingface gets taken down I got your back for free
-
Local LLMs Web Stack Setup With SearXNG Firecrawl and Camofox
By
–
PRO TIP Using local LLMs? Give them a web stack My setup: – SearXNG: candidate source discovery – Firecrawl: known-URL scraping and crawling – Camofox: browser fallback when JS/interaction gets annoying Search → Extract → Interact Tell your favorite agent to set this up,
-
MLX vs llama.cpp for Inference on Apple Silicon
By
–
MLX is often better on Apple Silicon from my experience llama.cpp is my fallback method
-
Run Local AI Easily Using Codex CLI and Optimized Inference
By
–
Let me make local AI easy for you Give Codex Cli the tweet below & tell it: – Infer the right Inference Engine from your hardware + tweet content below
– Use uv+venv
– Pick the right kernels
– Tune flags, batching, KVCache, etc
– Optimize for your hardware & chosen model Enjoy -
LTX 2.3 Ready to Run on RTX PRO 6000 GPUs
By
–
Time to put LTX 2.3 on your RTX PRO 6000s and get them to work 😀