potentially stupid problem trying to llama-bench Qwen3.6-27B across two V100s in

<!-- 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>b9095 finally makes -sm tensor work on dual consumer Blackwell PCIe GPUs without NCCL</p> <p>If youre on dual Blackwell gpus this look like it

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1t4uj9h/mtp_on_strix_halo_with_llamacpp_pr_22673/"> <img alt="MTP on strix halo with llama.cpp (PR #22673)"

<!-- SC_OFF --><div class="md"><p>So i recently updated LMstudio after a long pause and updated my llama.cpp runtimes too.. i was shocked.. i thought maybe something like

<!-- SC_OFF --><div class="md"><p>I have been using llama.cpp to run some models recently. For example, I've been running GLM-4.7-Flash with this command <code>.\llama-server.exe

<!-- SC_OFF --><div class="md"><p>Hi,</p> <p>I taught Computer Science for 30 years in a French School of Electrical Engineering, Computer Science Department.</p> <p>I recently

<!-- SC_OFF --><div class="md"><p>Hi,</p> <p>I'm running a local server with three AMD MI50. Tensor parallelism is not an option since it's very slow with PCIe 3.0 and those cards

<!-- SC_OFF --><div class="md"><p>Is there an easy way to know if a model is using CPU/RAM (and not only GPU/VRAM)?<br /> (I think standard verbose output, which got shorter, says