851–860 of 1001 posts
CEOs should really watch what they say in public. Anyway, this is all just my opinion.
Still worth it, but that’s a big jump.
You can get your HN profile analyzed by it and it's pretty funny :) https://hn-wrapped.kadoa.com/ I'm using this to test the humor of new models.
I chuckled.
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Thank you to the Kagi team for such fast turn around on new LLMs being accessible via the Assistant! The value of Kagi Assistant has been a no-brainer for me.
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Not everything is a tactical operation to get more subscription purchases - sometimes people like the things they use and want to say thanks and let others know.
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I like to make up my own tests, that way you know it is actually thinking. Tests that require thinking about the physical world are the most revealing. My new favourite is: You have 2 minutes to cool down a cup of coffee to the lowest temp you can. You have two options: 1. Add cold milk immediately, then let it sit for 2 mins. 2. Let it sit for 2 mins, then add cold milk. Which one cools the coffee to the lowest temp…
> I like to make up my own tests You just ruined your own test by publishing it on the internets
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Paul, I saw in the notes that using claude with thinking mode requires yml config updates -- any pointers here? I was parsing some commits, and I couldn't tell if you only added architect support through openrouter. Thanks!
Here are the current docs for changing the thinking token limits. https://aider.chat/docs/llms/anthropic.html#thinking-tokens I'll make this less clunky soon.
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Neither a statement for or against Grok or Anthropic: I've now just taken to seeing benchmarks as pretty lines or bars on a chart that are in no way reflective of actual ability for my use cases. Claude has consistently scored lower on some benchmarks for me, but when I use it in a real-world codebase, it's consistently been the only one that doesn't veer off course or "feel wrong". The others do. I can't quantify it…
O1 pro is excellent at figuring out complex stuff that Claude misses. It’s my go to mid level debug assistant when Claude spins
Kagi LLM benchmark updated with general purpose and thinking mode for Sonnet 3.7. https://help.kagi.com/kagi/ai/llm-benchmark.html Appears to be second most capable general purpose LLM we tried (second to gemini 2.0 pro, in front of gpt-4o). Less impressive in thinking mode, about at the same level as o1-mini and o3-mini (with 8192 token thinking budget). Overall a very nice update, you get higher quality and higher…
How did you chose the 8192 token thinking budget? I've often seen Deepseek R1 use way more than that.
Kagi LLM benchmark updated with general purpose and thinking mode for Sonnet 3.7. https://help.kagi.com/kagi/ai/llm-benchmark.html Appears to be second most capable general purpose LLM we tried (second to gemini 2.0 pro, in front of gpt-4o). Less impressive in thinking mode, about at the same level as o1-mini and o3-mini (with 8192 token thinking budget). Overall a very nice update, you get higher quality and higher…
Do you think kagi is the right Eval tool? If so,why?