Qwen3.8 27B

User compares TensorSharp, llama.cpp, vLLM, SGLang, velox-inferer and NInfer running Qwen3.8 27B on one RTX 5090 32 GB. TensorSharp averages 234.4 t/s decode with DFlash2 speculation across code, prose and copying, against 80.0 t/s plain. Setup is TensorSharp's direct-CUDA backend with an NVFP4 GGUF target and Q4_K_M drafter, 40,960-token context, greedy decoding and thinking disabled. DFlash2 uses seven draft tokens per step. NInfer leads the speculative decode average at 280.5 t/s and four-request aggregate throughput at 488 t/s; llama.cpp has the lowest short-prompt TTFT at 27 ms plain. The author reports up to roughly 4% decode variation between runs and notes the engines used different quantized checkpoints.