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Advancing the price-performance frontier with GPT‑5.6

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Re: Advancing the price-performance frontier with GPT‑5.6

#201

Post by computerex »

ignoramous wrote: post #178
foobar_______ wrote: post #45

Earlier quoted context omitted.

Hard to believe numbers. I don't mean that as a critique, but literally I am so impressed. Even if the model is a few percent lower for performance but is 80+% cheaper than competitors and is a US company hosted on US based hyperscaler clouds this is kind of a no brainer. Hard for most businesses to justify otherwise.

DeepSeek v4 Pro & MiMo v2.5 Pro (Opus 4.6 quality models for code) are insanely cheap for agent-driven work due to their super low cached-input prices ($0.0036/mtok) [0]. For Luna, the cached-input price drop isn't disclosed in TFA, but the pricing page puts it at $0.02/mtok, & that's 5x more expensive. [0] I am constantly surprised how much work pay-as-you-go with DeepSeek / MiMo will get done. I've barely crossed $…

Absolutely. Although DeepSeek started announcing "Peak valley" pricing which started making me nervous. I have spent $50 usd in July on deepseek and for that much spend I got SO MUCH mileage.

I feel perfectly content in using pay as you go pricing with deepseek. On the other hand, although Anthropic's models used to be my bread and butter for personal work, they are simply too expensive to reach for these days.

Re: Advancing the price-performance frontier with GPT‑5.6

#203

Post by satvikpendem »

pimeys wrote: post #199
GodelNumbering wrote: post #44

"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).

If you have agents and users, you can run evals and see how far the models go. Luna is not greatest in tool calls, but if you define your problem well and the tools well, it is comparable to Gemini 4 Flash with much lower price tag.

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.

Re: Advancing the price-performance frontier with GPT‑5.6

#204

Post by otherme123 »

msejas wrote: post #169

Isn't OpenAI burning billions and have billions more spending commitments? If they managed to downsize so much the cost they should have kept the price the same and become profitable, really weird move, unsure what led to this.

Slower grow, or even shrink in usage? Right now, the promise of a future "everyone will use our models and pay whatever we ask" is what keeps $$ flowing towards OpenAI.

Re: Advancing the price-performance frontier with GPT‑5.6

#205

Post by ElijahLynn »

8cvor6j844qw_d6 wrote: post #166
iamjackg wrote: post #137

Earlier 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.

I'd like to imagine the things that can be done with this speed and the current frontier models.

Truth, it feels like we're in the dial-up age of LLMs right now. And this Jimmy AI is fiber.

Re: Advancing the price-performance frontier with GPT‑5.6

#206

Post by paxys »

dgellow wrote: post #198
paxys wrote: post #194

Earlier quoted context omitted.

Supply demand curve is a thing. Cutting price on something does not mean you are going to make less money.

But they still have to cover compute cost, and they already committed to more than $650B in infra expenses for 2035

Why assume they are not already making up the compute costs for smaller models?

Re: Advancing the price-performance frontier with GPT‑5.6

#207

Post by bob1029 »

coffeebeqn wrote: post #184
jrflo wrote: post #115

Earlier 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

What does that mean though? Like some kind of a ROM memory ?

Stacked ROM can, in theory, be a lot denser than anything that depends on a capacitor and refresh cycle.

I don't think it would be that difficult to manufacture compared to other process tech. HBM is really hard to do compared to other memory types.

Re: Advancing the price-performance frontier with GPT‑5.6

#209

Post by simianwords »

There were people on HN who still thought that the API prices were being subsidised. The level of conspiracy theory was off the charts on this topic. You would get these price reductions month over month you would still have people believing in crazy stuff.

Re: Advancing the price-performance frontier with GPT‑5.6

#210

Post by steveklabnik »

baalimago wrote: post #111
gbnwl wrote: post #92

Earlier quoted context omitted.

Experienced similar between 5.4-mini vs 5.6-luna in our own pipelines but after spending some time on prompt optimization and testing out various reasoning effort levels 5.6-luna was well worth it. Did you just replace model selection while keeping everything else in place or spend some time on evaling with newer prompts etc?

No we kept prompts as is, just swapped model. The prompt is already quite optimized for the task. How would updating it possibly make a more intelligent model spend less tokens than a less intelligent model? Care to elaborate?

Here is an example of a guide from OpenAI on how you should prompt 5.6 differently than their previous models.

https://developers.openai.com/api/docs/guides/latest-model#p...

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