Simple to use vLLM Docker Container for Qwen3.6 27b with Lorbus AutoRound INT4 q

<!-- SC_OFF --><div class="md"><p>I could not find good data points on what speed one could get with a single 5090 and enough DDR4 RAM. </p> <p>My system: AMD EPYC 7532 32core

<!-- SC_OFF --><div class="md"><p>I'm using this <a href="https://huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-v2-GGUF">opus 4.6 distilled version of

<!-- SC_OFF --><div class="md"><p>I'm currently choosing between IQ3_XXS Qwen-3.8-Flash and Q8_0 27B.</p> <p>This month I don't have anything complex enough to justify either's

<!-- SC_OFF --><div class="md"><p>I'm genuinely unsure if I'm doing something wrong, or if the model is just worse, despite the community enthusiasm. I tend to use it with pi

<!-- SC_OFF --><div class="md"><p>PR #22673 (commit 4f13cb7) landed MTP speculative decoding in mainline llama.cpp on May 16. I tested it on two separate rigs.</p> <p>Qwen3.6 27B,

<!-- SC_OFF --><div class="md"><p>In case it helps anyone I'm sharing the config I am using for Qwen3-5-122B-A10B-NVFP4 deployed on a single 6000 Pro.</p> <p><a

<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1s7rcwr/qwen35_omni_qwens_latest_generation_of_fully/"> <img alt="Qwen3.5 Omni - Qwen’s latest generation

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sn3izh/qwen3635ba3b_released/"> <img alt="Qwen3.6-35B-A3B released!"