A recent pull request (PR #21845) in llama.cpp ports the multi-column MMVQ optimization from CUDA to SYCL, achieving a...

A recent pull request (PR #21845) in llama.cpp ports the multi-column MMVQ optimization from CUDA to SYCL, achieving a ~45% speculative decoding speedup on Intel Arc GPUs (source). This demonstrates that a key CUDA performance feature can be effectively replicated on non-NVIDIA hardware via SYCL, potentially eroding CUDA's historical performance advantage. While CUDA remains dominant in the developer ecosystem, as evidenced by active local LLM runs on RTX 4060 and RTX 5080 (source 2, source 3), the ability to port CUDA-optimized kernels to SYCL reduces barriers for alternative GPU vendors. This comes alongside a Manifold Markets prediction indicating a ~43% chance CUDA will lose its monopoly by 2027 (source). Although the current impact is modest, the trend of porting CUDA features to open frameworks may accelerate CUDA ecosystem drift and weaken NVIDIA's software moat over the medium term.