<!-- SC_OFF --><div class="md"><p>Laguna s2.1 launched about <strong>a week ago</strong>, the benchmark's that they advertised were <strong>crazy good</strong>. But <strong>It was
<!-- SC_OFF --><div class="md"><p>Tested Laguna S 2.1 (118B MoE with 8B active parameters) by Poolside on frontend and backend coding tasks and the results are nowhere near what
<!-- SC_OFF --><div class="md"><p>I can fit the whole thing in RAM in Q8, and it seems to be outperforming qwen 3.5 122B-A10B Q8 for some things. I've been seeing reports for the
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sy6oxr/introducing_laguna_xs2_and_laguna_m1/"> <img alt="Introducing Laguna XS.2 and Laguna M.1"
<!-- SC_OFF --><div class="md"><p>Been building and testing LLM workflows for a bit and started digging into logs more closely.</p> <p>Lo and behold!</p> <p>a pretty large chunk
<!-- SC_OFF --><div class="md"><p>I’ve been exploring how to build a fully on-prem document AI pipeline for handling confidential data — no cloud APIs, no external processing.</p>
<!-- SC_OFF --><div class="md"><p>So this is probably a pretty common thing, but I just want to ask in case am not missing something. I have pretty much no knowledge but trying to
<!-- SC_OFF --><div class="md"><p>I’ve been testing LM Studio on my RTX 5070 Ti (16GB) and Ryzen 9800X3D, running Unsloth Qwen3.5 35B (UD Q4_K_XL).</p> <p>Initially, I thought LM
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