<story><title>GPT-4o mini: advancing cost-efficient intelligence</title><url>https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/</url></story><parent_chain></parent_chain><comment><author>ChrisArchitect</author><text>[dupe]&lt;p&gt;Some more discussion: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;news.ycombinator.com&amp;#x2F;item?id=40996248&quot;&gt;https:&amp;#x2F;&amp;#x2F;news.ycombinator.com&amp;#x2F;item?id=40996248&lt;/a&gt;</text></comment>
<story><title>GPT-4o mini: advancing cost-efficient intelligence</title><url>https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/</url></story><parent_chain></parent_chain><comment><author>wrs</author><text>The big news for me here is the 16k output token limit. The models keep increasing the input limit to outrageous amounts, but output has been stuck at 4k.&lt;p&gt;I did a project to summarize complex PDF invoices (not “unstructured” data, but “idiosyncratically structured” data, as each vendor has a completely different format). GPT-4o did an &lt;i&gt;amazing&lt;/i&gt; job at the extraction of line items, but I had to do a heuristic layer on top to break up the PDFs into small chunks so the output didn’t overflow.</text></comment>