131–140 of 285 posts
Okay this is a nitpick but why wouldn't you increment a part of the version number to signify that there is an improvement? These releases are confusing.
I wouldn't call that a nitpick, it's a major annoyance. Version numbers become useless with that kind of policy.
Non-AI Summary: Both models have improved intelligence on Artificial Analysis index with lower end-to-end response time. Also 24% to 50% improved output token efficiency (resulting in lower cost). Gemini 2.5 Flash-Lite improvements include better instruction following, reduced verbosity, stronger multimodal & translation capabilities. Gemini 2.5 Flash improvements include better agentic tool use and more token-effici…
2.5 Flash is the first time I've felt AI has become truly useful to me. I was #1 AI hater but now find myself going to the Gemini app instead of Google search. It's just better in every way and no ads. The info it provides is usually always right and it feels like I have the whole generalized and accurate knowledge of the internet at my fingertips in the app. It's more intimate, less distractions. Just me and the Gem…
Disclaimer: I recently joined this team. But I like the product!
This really captures something I've been experiencing with Gemini lately. The models are genuinely capable when they work properly, but there's this persistent truncation issue that makes them unreliable in practice. I've been running into it consistently, responses that just stop mid-sentence, not because of token limits or content filters, but what appears to be a bug in how the model signals completion. It's been…
Unfortunately Gemini isn't the only culprit here. I've had major problems with ChatGPT reliability myself.
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Yeah, that's my use case. When you want to test some program / script that utilizes an llm in the middle and you just want to make sure everything non-llm related is working. It's free! just try again and again till it "compiles" and then switch to 2.5
wow this would be great for a webapp/site that just needs a basic/performant LLM for some basic tasks.
It might not be OK for that kind of usecase, or might breach ToS.
But it's still great. Even my premium Perplexity account doesn't give me free API access.
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If anyone from OpenAI is reading this, I have two complaints: 1. Using the "Projects" thing (Folder organization) makes my browser tab (on Firefox) become unusably slow after a while. I'm basically forced to use the default chats organization, even though I would like to organize my chats in folders. 2. After editing a message that you already sent,you get to select between the different branches of the chat (1/2, an…
It would also be nice if ChatGPT could move chats between projects. My sidebar is a nightmare.
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Can't agree with that. Gemini doesn't lead just on price/performance - ironically it's the best "normie" model most of the time, despite it's lack of popularity with them until very recent. It's bad at agentic stuff, especially coding. Incomparably so compared to Claude and now GPT-5. But if it's just about asking it random stuff, and especially going on for very long in the same conversation - which non-tech users h…
My pet theory without any strong foundation is because OpenAI and Anthropic have trained their models really hard to fit the sycophantic mold of: =============================== Got it — *compliment on the info you've shared*, *informal summary of task*. *Another compliment*, but *downside of question*. ---------- (relevant emoji) Bla bla bla 1. Aspect 1 2. Aspect 2 ---------- *Actual answer* ----------- (checkmark e…
Google seems to be the main foundation model provider that's really focusing on the latency/TPS/cost dimensions. Anthropic/OpenAI are really making strides in model intelligence, but underneath some critical threshold of performance, the really long thinking times make workflows feel a lot worse in collaboration-style tools, vs a much snappier but slightly less intelligent model. It's a delicate balance, because thes…
Okay this is a nitpick but why wouldn't you increment a part of the version number to signify that there is an improvement? These releases are confusing.
This really captures something I've been experiencing with Gemini lately. The models are genuinely capable when they work properly, but there's this persistent truncation issue that makes them unreliable in practice. I've been running into it consistently, responses that just stop mid-sentence, not because of token limits or content filters, but what appears to be a bug in how the model signals completion. It's been…