How does an LLM inference engine work under the hood?
I wrote an article on my Qwen 3.5/3.8 engine for Apple GPUs: KV/prefix caches, DFlash/MTP speculative decoding, and deferred linear attention state commits. It achieves a 1.25× speedup over llama.cpp.
I have been working with cerebras inference running qwen 3.8 27b and the first issue I see is reviewing…
I have been working with cerebras inference running qwen 3.8 27b and the first issue I see is reviewing the wall of output this thing puts out in seconds.
Many big guys are asking today, can one of your computing cabins run Qwen 3.8 Flash Next + Blender?
Of course you can, but my modeling skills are relatively poor, so the build is ugly 😂 If this AI solution is handed over to professional design engineers, it should be very beautiful.
Updated the VR game I tried my best to create a voxel stage with Codex, but it didn't go well. Changed my way of thinking.
Qwen 3.8 27B lets you create a miniature garden using vibe coding, which is implemented by Codex. The game system also implements Gradius' power-up system and Afterburner rolling.
You have reached the end of the archive
All of qwen38