Earlier quoted context omitted.
> Let's suppose each models was subsidized at 70%, so that we only pay 30% of the cost. why on earth would you suppose that?
Because their leaked financials point that way.
Source?
Advancing the price-performance frontier with GPT‑5.6
351–360 of 424 posts
Re: Advancing the price-performance frontier with GPT‑5.6
#352What are your use case for these? I’m manly interested in coding where more capability is better - give me a 10x model at 10x the price and I’ll take it. A worse model at very low cost has no appeal to me. At-least not for coding. Translation maybe? OCR?
Dinky stuff I want to be fast like “update the PR with this other JIRA ticket”
Re: Advancing the price-performance frontier with GPT‑5.6
#353Earlier quoted context omitted.
I don't see why it should be all that difficult. All you have to do is first find a library that implements a decent solution to the halting problem and you're off to the races.
Its funny because you can write a halting problem oracle by calling out to an LLM and have it return yes / no / not sure and get it to work reliably for almost all real code, like that is an entirely practical thing to do in 2026. All we need now is some sort of program to evaluate halting problem oracles...
[deleted]
Re: Advancing the price-performance frontier with GPT‑5.6
#354What are your use case for these? I’m manly interested in coding where more capability is better - give me a 10x model at 10x the price and I’ll take it. A worse model at very low cost has no appeal to me. At-least not for coding. Translation maybe? OCR?
Summarization of datasets, categorization
Re: Advancing the price-performance frontier with GPT‑5.6
#355Earlier quoted context omitted.
Burning the weights into silicon would be many orders of magnitude increase, not just 10x. It's kind of crazy that this hockey stick the AI hype bros talk about seems more and more every day like it might be real
https://taalas.com/ has done it already for a wildly obsolete model. 14000 tokens per second. https://chatjimmy.ai/ is their interactive. Tiny context, very dumb, but absurdly fast. Imagine this as a tool call for claude code for trivial changes - the tool call from the harness takes longer than the execution.
hugged?
Re: Advancing the price-performance frontier with GPT‑5.6
#356Earlier quoted context omitted.
Luna is meant to compete with Haiku. What tasks are you seeing it equal Opus on?
Per Artificial Analysis: - Haiku: 30 points - Luna Medium/High/Xhigh/Max: 38/46/49/51 points That's a massive difference: - 30 points is Gemma 4 31B territory - 50 points is GLM-5.2 (744B) territory.
Could OpenAI be running a different model for high+max?
Re: Advancing the price-performance frontier with GPT‑5.6
#357Earlier quoted context omitted.
At some point I imagine you’d add a software layer on top that holds more current training and can be called as needed trading off for slower responses. There’s already work out there splitting models across networks. You could have the base on silicon, some stuff in memory on the machine, and another frontier tool in the cloud.
Taalas actually already support LoRA, basically doing exactly what you say. The other thing that I think is really interesting about all of this, is that LLMs are already perforce behind the times with their knowledge cutoff, so adding an additional ~3 months for bake into silicon isn't such a huge deal, I think, for the ~10x more efficient and faster you get.
Yeah, really a fascinating time in computing. Once these chips start to become more common I'll be curious how people find ways to use them. One can imagine a world where really simple inference is available on dirt cheap chips found in toys and other low cost consumer electronics.
Re: Advancing the price-performance frontier with GPT‑5.6
#358Earlier quoted context omitted.
It's marketing hyperbole, but Luna is more intelligent per dollar than deepseek-v4 pro. Cost means nothing without the associated capability
is it? i don't know how we measure these things, but here's one measurement that says v4 pro is better than luna: https://artificialanalysis.ai/models/comparisons/gpt-5-6-lun... presumably it's a much bigger model
That’s comparing Luna on medium thinking with Deepseek on max. If you switch Luna to xhigh in that comparison it’s considerably more capable while still also cheaper.
Re: Advancing the price-performance frontier with GPT‑5.6
#359Earlier quoted context omitted.
It's marketing hyperbole, but Luna is more intelligent per dollar than deepseek-v4 pro. Cost means nothing without the associated capability
is it? i don't know how we measure these things, but here's one measurement that says v4 pro is better than luna: https://artificialanalysis.ai/models/comparisons/gpt-5-6-lun... presumably it's a much bigger model
You are comparing Luna medium to Deepseek Max, when you switch to Luna high it's cheaper per task than DS and has a better intelligence score, which goes higher yet on xhigh and max reasoning levels.
https://artificialanalysis.ai/models/comparisons/gpt-5-6-lun...
Re: Advancing the price-performance frontier with GPT‑5.6
#360We swapped an internal system from gpt-5-mini to gpt-5.6-luna and saw no benefit but 4x cost. Sufficed to say: we swapped back to gpt-5-mini.
5.6 class models have a brand new caching architecture. Make sure you were using the prompt cache breakpoints and cache keys correctly - it's much different than < 5.5 and makes a huge difference for many production workloads.