Qwen3.8 125B (6B active) Flash-Next

User compares Ninfer6000, vLLM and llama.cpp running Qwen3.8-Flash-Next on an RTX Pro 6000 Blackwell 96GB. Ninfer6000 reaches 232 t/s decode at ~1k prompt versus 159 t/s for vLLM NVFP4 and 138 t/s for llama.cpp Q4_K_XL, with a mean decode of 238 t/s across prompts up to 114k. Setup is Ninfer6000 with an NVFP4 conversion, vLLM with nvidia/Qwen3.8-Flash-Next-NVFP4 and llama.cpp with unsloth UD-Q4_K_XL, all on one RTX Pro 6000 Blackwell at 600W with a Ryzen 5 5600X and 96GB DDR4-3000. Prefill trails vLLM (4,315 t/s vs 6,944 t/s at ~1k) but beats llama.cpp. Accuracy benchmarks are close across all three, with Ninfer6000 ahead on BFCL v4 tool calling (76.67 vs 74.56 and 73.00). User reports a crippling tool-calling formatting issue with Ninfer6000 in real-world use in Open-WebUI and Cline, and will keep using vLLM until it is resolved.