I'm seeing very low quality results on LMStudio with this model. Worse than Gemma 3 12B.
It is getting questions like "David has 18 apples and Ivan has 7 apples. How many apples do they have together?" wrong half the time, while Gemma3 12B could very consistently answer that. Other smoke tests (like Chinese translation, and the infamous "Rs in Strawberry" test) also show poor results.
I don't know if it is a quantization/release issue, if the parameters needed for accurate responses have changed (i.e. it needs "thinking" tokens to handle its base error rate), or if the model has been so focused on audio/video that the text processing is bad.
He (or ChatGPT) is throwing spaghetti at the wall. Not having the standard API key be able to delete the database (and backups) in one call makes sense. "Wanting a human to type DELETE as part of a delete API call" does not.
I'm not sure they've found/understand it yet. My two main theories:
1. A bunch of people with new Claude Code codebases in December now are working with a larger codebase, causing more context. Claude reads a lot of code files, and doesn't effectively prune from the context as far as I can tell. I find myself having to hint Claude regularly about what files to read (and not read) to avoid having 75k of unrelated files in the context window.
2. Claude Code tries to do more now, for the benefit of people who don't know exactly what they want. The trade-off is that it's worse at doing exactly what people want, when they do know. The "small fix" becomes a large endeavor for Claude.
Wikinews never worked; the principle of "verifiability" that Wikipedia was based on simply doesn't work for news-collection, which requires trusted first-party accounts.
The project was also already dead; the English Wikinews has had 10 "articles" posted in the last 3 weeks, two of which were trivial sports stories (a second-division Queensland football match, and the retirement of a pitcher whose last substantial year in MLB was 2019). The most recent story is that an amateur jazz group recently played at a library.
It will no longer be an attractive nuisance to the few who stumble across it. Rest in peace.
So far on my (simple) benchmarks, GPT-5.4-mini is looking very good. GPT-5.4-mini is about 30% faster than GPT-5-mini. GPT-5.4-mini gets 80% on the "how many Rs in Strawberry" test, and nearly perfect scores on everything else I threw at it.
GPT-5.4-nano is less impressive. I would stick to gpt-5.4-mini where precise data is a requirement. But it is fast, and probably cheaper and better quality than an 8-20B parameter local model would be.
( https://encyclopedia.foundation/benchmarks/dashboard/ for details - the data is moderately blurry - some outlier (15s) calls are included, a few benchmark questions are ambiguous, and some prices shown are very rough estimates ).
Between this and 4.6's tendency to do so much more "exploratory" work, I am back to using ChatGPT Codex for some tasks.
Two months ago, Claude was great for "here is a specific task I want you to do to this file". Today, they seem to be pivoting towards "I don't know how to code but want this feature" usage. Which might be a good product decision, but makes it worse as a substitute for writing the code myself.
I've been working on a similar app called Trakaido. (Yes, it's also AI generated content).
The demo leans heavily on "choose the words for the sentence", which avoids spelling/keyboard issues, and maybe generalizes around the problems of N->N language maps better. The "decoy selection" for multiple choice answers also isn't great - I am getting sentences mixed with numbers for the translation of "three".
It also has the Duolingo-esque audio "reward" sounds. I personally hate them, but a lot of people feel otherwise.
There's a difference between the chatbot "advertising" something and an hour-long manipulative conversation getting the chatbot to make up a fake discount code. Based on the OP's comments, if it was a human employee who gave the fake code they could plausibly claim duress.
This seems to have a fundamental misunderstanding of Hacker News's front page. The goal is to have posts only show up for at most a day or two. I would expect 100% to be gone in a week.
The "outliers" are posts that were deleted and re-submitted, or possibly boosted by the moderators. The "visible for 44 days" post was only submitted 14 days ago; either it was deleted or it is a glitch in this guy's script.
Magical thinking about "the internet eliminates censorship" cannot and must-not override the very real fact that Kiwifarms is awful and no business that is aware of what goes on there wants to associate with them.