Cost vs performance of open weight models according to arena

<!-- 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

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1st8l2u/kimi_k26_takes_1st_overall_of_open_weights_models/"> <img alt="Kimi K2.6 takes 1st overall of open

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sskmhv/recent_open_models_from_last_6_months_nov_2025/"> <img alt="Recent Open models from last 6 Months -

<!-- SC_OFF --><div class="md"><p>Hi everyone </p> <p>I’m new to this community and just starting out with local LLMs. I’m using a MacBook M4 Air, so my hardware is somewhat

<!-- SC_OFF --><div class="md"><p>After burning way too much money on GPT-4 API calls, I finally went all-in on local models with Ollama. The progress in 2026 is insane

<!-- SC_OFF --><div class="md"><p>Benchmark: 58.4 vs 56.7 (beats GPT-5.4)</p> <p>License: Fully open (Apache 2.0) </p> <p>What it actually does: Runs 8-hour fully autonomous agent

<!-- SC_OFF --><div class="md"><p>Wrote a deep dive on <strong>FlashAttention-4 (03/05/2026)</strong> that's relevant for anyone thinking about inference performance.</p>

<!-- SC_OFF --><div class="md"><p>Hello,</p> <p>A non technical client discussed the possibility of having an SLM to reduce inference costs per user for the product we're using