We’ve gone from a few solid options (vLLM, llama.cpp, TensorRT-LLM) to a constant stream of specialized engines and forks : Strata, Radiance, various Flash-Next / DeepSeek-Flash optimized builds, megakernel stuff, etc. Performance gains are real, especially on specific models (Qwen Flash Next, DeepSeek variants) or hardware. ROCm has improved a lot and AMD is no longer the clear second-class citizen it used to be, but the overall landscape still feels fragmented. Model support is uneven and picking the “best” engine often means testing several options every time something new drops. Is this healthy competition that will eventually settle, or are we just making the ecosystem more fragmented and annoying? I m puzzled on this : on one hand specialised inference engines are fast and on the other hand : Now it feels like you need to pick ONE model and it's engine. I miss the LM Studio simplicity. What do you think?   submitted by   /u/Anstellos [link]   [comments]