<!-- SC_OFF --><div class="md"><p>doing infrastructure evaluation for inference workloads and running into the same problem everywhere: every platform publishes p50 cold start
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s6r8ro/why_the_pricing_is_so_uneven_like_for_very_small/"> <img alt="Why the pricing is so uneven? like for
<!-- SC_OFF --><div class="md"><p>I have Azure H100 quota (NC40ads_H100_v5 - 80GB HBM3) across a couple of regions that I'm not fully utilizing. Rather than let it sit idle,
<!-- SC_OFF --><div class="md"><p>Been noticing that once you use LLMs for real dev work, the cost conversation gets messy fast. It is not just raw API spend. It is retries, long
<!-- SC_OFF --><div class="md"><p>Hi everyone,</p> <p>I recently started working in controlling and I’m currently going through the typical learning curve: understanding complex
<!-- SC_OFF --><div class="md"><p>I've been reading alot about AI compute stuff lately and something keeps bothering me.</p> <p>The total power used for cryptocoin mining around
<!-- SC_OFF --><div class="md"><p>One thing we’ve been noticing lately is that a surprisingly large percentage of day-to-day AI workflows no longer seem to require frontier-scale
<!-- 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
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