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Advancing the price-performance frontier with GPT‑5.6

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71–80 of 424 posts

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

#71
post #14

> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.

it's 80% less cost, not 80% in efficiency gains, could be that Luna was overpriced to begin with, we don't have much info on the models themselves. Assuming the efficiency gains are real, I feel like something has to give, maybe worse quality due to aggressive quantization/kv cache compression?

Been using OpenAI models since ada/babbage/curie/davinci and at least from my own experience, their APIs feel the same.

If you use Codex it's different, the harness has a lot to do with it and there's definitely been changes including recently.

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

#72
post #49

What 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?

Translation, moderation, classification, guardrails, etc..

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

#73
post #50
post #35

This feels like the dialup->broadband transition to me. I was already a huge proponent of Luna for things like deep research. Being able to run 5x more for the same cost is simply bananas. We are already running 10 parallel agents for hypothesis generation. I cannot imagine 50. The statistics become much more interesting & powerful when you can run so many samples of the exact same prompt+model without breaking the b…

Do you have a sense of which tasks benefit from more agents and which don't?

Anything related to reading and interpreting the environment seems to always benefit from the addition of more agents to the search party, assuming you have some rational way to synthesize their results.

Taking actions that mutate the environment is a different story. I think this is where you run into diminishing returns very quickly. You generally want one strong agent to act given the results of all the searching that was done. If the plan is clear, you don't need a genius model to execute it.

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

#74
post #51

Earlier quoted context omitted.

This is gonna put Sonnet 5 in a really awkward spot.

Sonnet and Haiku were already in an awkward spot, likely by design. Anthropic's big marketing push this year has been entirely focused on getting people to use Opus via a Claude Code subscription, to the point that Sonnet is almost viewed as the poor man's alternative, and from what I've seen, almost nobody uses it. Actually, here's an interesting project for all the vibe coders looking for their next front page post…

>figure out what the percentage split between Opus/Fable/Sonnet is.

This may be misleading, since I suspect many are using a blend through sub-agents. I tend to bias for Fable to orchestrate and Opus for implementation via sub-agents.

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

#75
post #14

> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.

this type of thing usually means you are the product

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

#76
post #14

> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.

This is gonna put Sonnet 5 in a really awkward spot.

Luna is comparable to Haiku, not Sonnet.

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

#77
post #14

> Starting today, GPT‑5.6 Luna, our fastest and most affordable model, will cost 80% less, I don't have the words. I genuinely thought we were in a stage where we were plateauing and going in for 5-10% improvements over months. Seeing spikes like this makes me question about where the floor really is.

Vera Rubin will be hitting racks very soon, and this is purported to have a 10x improvement in token throughput per megawatt. Of course, old chips don't get replaced with new chips overnight, but I don't think we're anywhere near the floor yet.

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

#78
While I can't deny this is a huge technological result, and it's laudable they reduced the price because of it, 80% is really a lot. I can't help but wonder, is this because of the model's capabilities, or was the initial system just really sloppy? The public will probably never know the details

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

#79
post #48

Making Luna, which was already very cheap and extremely capable, 5x cheaper is crazy. I use Sol at work but Luna at home, and while there's definitely a difference, it doesn't feel like night-and-day. After a year of ever-increasing prices it suddenly feels (between this, Kimi K3, GLM 5.2) that prices are falling again.

is kimi that cheap? it's a very expensive model

It's cheaper currently on many of the inference providers.

Personally, I'm having surprisingly good results with DeepSeek 4 Pro at home, which is very good value for money: it's not as good as Claude / GPT 5.6 (I have Co-pilot license at work), but it's still really useful for code reviews, validating thoughts, and especially designing / writing unit tests for new (and old before refactoring) functionality.

And it's very cheap per task. (Flash is even cheaper, but I've had issues with that on more complex tasks where it starts forgetting things and arguing with itself "but wait, let me read the function again").

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

#80

"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).

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