Earlier quoted context omitted.
Luna is good as an end user model for simple tasks like classification, but not as a coding model. Also do you mean Gemini 3.6 Flash? 4 doesn't exist, and Gemma 4 exists but doesn't have a Flash option.
Not my experience at all. I've been driving Luna xhigh in CoPilot CLI since it was released as my daily driver. Good reasoning, no problems with tool calls.
Advancing the price-performance frontier with GPT‑5.6
341–350 of 424 posts
Re: Advancing the price-performance frontier with GPT‑5.6
#342Earlier quoted context omitted.
Holy crap, I was not prepared for how fast it responded. I just wrote "Just wanted to see how fast you are! Can you write me a quick story about a tiger who lives inside a block of cheese the size of a house?" I pressed Enter, and the response was instant . > Generated in 0.037s • 14,205 tok/s This is unbelievable.
It's crazy. Are they doing any precomputing as you type, I wonder if you paste a block of text is it the same speed.
Re: Advancing the price-performance frontier with GPT‑5.6
#343Earlier quoted context omitted.
Wow! You weren't kidding, I just tried it too and 14,098 tokens in .05 seconds, I barely blinked and it was done. There was no typing at all appearing on the screen. It just showed up. https://chatjimmy.ai/chats/01dc66a4-4b1b-4dea-bb5f-926855e37...
That link isn't bringing up your chat, FYI. It just shows the default new chat state.
Here's a copy and paste prompt if somebody wants to just test it real quick to see what I saw:
Write a story about the fastest monkey who ever lived, his name is Jimmy and he is an AI superbot monkey that is part cyborg primate. He can travel through time and is psychic.
Re: Advancing the price-performance frontier with GPT‑5.6
#344"Half the money I spend on advertising is wasted; the trouble is I don't know which half." -John Wanamaker This applies even more strongly to model choosing. I know for a fact that majority of my work doesn't require a very strong model, but separating the trivial and non-trivial tasks is a famously hard problem (if at all decidable).
I remember bugs always end up being more expensive then the first time I implemented the feature… so for me always sol always max… I don’t want to pay for a bug later
Re: Advancing the price-performance frontier with GPT‑5.6
#345Earlier quoted context omitted.
Hasn't OpenRouter had Luna and Terra on 50% off sale since they launched? I wonder what will happen to that.
It's still 50% off apparently. Listed as $0.10 for input (original price was $1.0 without this reduction or sale)
Re: Advancing the price-performance frontier with GPT‑5.6
#346Just imagine how much the same level of intelligence cost only a few months ago.
Re: Advancing the price-performance frontier with GPT‑5.6
#347Earlier quoted context omitted.
How do you run 'deep research'?
Deep research is basically a LLM with web search, and a "work really hard" goal-orientated prompt, and some output formatting suggestions.
Re: Advancing the price-performance frontier with GPT‑5.6
#348Re: Advancing the price-performance frontier with GPT‑5.6
#349Re: Advancing the price-performance frontier with GPT‑5.6
#350Earlier quoted context omitted.
Wasn't the original proof something like "a program that loops indefinitely when the oracle says it will halt, and stops immediately if an oracle says it will not stop"? The whole point was the you can construct a contradictory program that cannot be decided by any oracle by its very nature. ```python source_code = open(__file__, 'rt').read() response = ask_llm("will this program halt, only answer 'yes' or 'no'?\n" +…
You're right of course, LLMs provide a partial, unsound oracle. The "halting problem is unsolvable" argument relies on the oracle not being able to output "not sure". But adding that option admits trivial oracles, like ones which output "not sure" for everything, so some are better than others. The "real world" use most people have for halting oracles is as part of software safety, where if the checker outputs "not s…
Knowing that functions terminate is important for proof languages like Lean, where you often want to prove things without running the code at all. You're proving that one could, theoretically, calculate an answer, without actually calculating it.