<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM on Zachary Loeber's Blog</title><link>https://blog.zacharyloeber.com/categories/llm/</link><description>Recent content in LLM on Zachary Loeber's Blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 05 Jan 2026 09:21:07 -0600</lastBuildDate><atom:link href="https://blog.zacharyloeber.com/categories/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>LLM Underdogs of 2025</title><link>https://blog.zacharyloeber.com/article/llm-underdogs-of-2025/</link><pubDate>Mon, 05 Jan 2026 09:21:07 -0600</pubDate><guid>https://blog.zacharyloeber.com/article/llm-underdogs-of-2025/</guid><description>&lt;h1 id="llm-underdogs-of-2025">LLM Underdogs of 2025&lt;/h1>
&lt;p>2025 has been a flurry of AI madness that has been hard to keep up with. I&amp;rsquo;ve been deep in learning and experimenting in the AI space and noticed that while everyone&amp;rsquo;s hyping up the latest GPT variant or Claude release, there are some genuinely impressive open-source models that feel like they just flew under the radar in 2025. These aren&amp;rsquo;t just &amp;ldquo;good for their size&amp;rdquo;, they&amp;rsquo;re legit excellent models that you can run locally, for free, and deserve more attention.&lt;/p></description></item><item><title>Free Tokens for AI Exploration</title><link>https://blog.zacharyloeber.com/article/free-tokens-for-ai-exploration/</link><pubDate>Fri, 16 May 2025 13:28:23 -0500</pubDate><guid>https://blog.zacharyloeber.com/article/free-tokens-for-ai-exploration/</guid><description>&lt;p>Using ChatGPT, Gemini, Grok, or any of the other chat based LLM service is a great way to start with AI. But in order to bring things to the next level you will either need some beefy hardware to run models locally or access to an online API with models you can use. This article will walk you through how to do the later of these two options for free.&lt;/p></description></item></channel></rss>