Cached Read: ~6,500M
Input: ~150M
Output: ~20M
Approx $40 worth of usage across DeepSeek V4 Flash + MuseSpark Contributor 1.3. And a bit of both the GLM models. This is covered in a $10 subscription.
If I were to use Luna's API pricing:
$0.02 x 6,500 = $130
$0.20 x 150 = $30
$1.20 x 20 = $24
So $184. And this is assuming smaller coding sessions (<272K) beyond which Luna pricing doubles.
--
Cost wise, these models are nice for small stuff. Translations etc. Any model that does not provide multiple Mtoks of cached reads per cent is not very useful to me for coding workflows.
Given how subscription models work (not every one uses every last $ of their plan), they should achieve breakeven soon enough I guess.
I dont know how they make money here
Snark aside, Luna 5.6 was (is) an incredible game-changer.
perhaps it then does mean - squeeze as much as you can get off this actual free usage.
And info from the help page with message limits suggests the 50% price cut does not apply to the subscription, where they applied only a 1/3 price cut instead.
I'm not thrilled with this release.
Opus 5.5, which matches GPT-6 Astra performance at a cheaper price, is much more interesting.
When I ask for an explanation it adds the right amount of detail. Of course, some of the material is new to me so subtle errors are hard to spot. But at least I’ve caught Terra and Sol on inconsistent messaging.
Also I’ve found 3.8 flash to circle back to root issues even at the conceptual level like problem fit and conceptual solution direction or architecture when I wasn’t achieving my goals. It flat out said I was attempting to use the wrong tool. Whereas Sol and Astra kept rabbit holing and looking for tiny implementation errors. Even after prompting them specifically to look at it broader.
By raising it from investors.
I assume it's a subsidy to get more training data.
EDIT: Okay downvoters, what's your take on why they're giving away Luna for so cheap?
I had all the tabs open individually and harder to scan which model is which... otherwise keep up the great work! I like the grid view a lot. (Also the pages have no OG images set, which impacts what the link looks like shared)...
OG images will require me to move away from publishing in a Gist and linking to from a JavaScript page that loads the Gist. Probably worthwhile though.
I got it working in a quick local test (grid of all the reasoning efforts, cached per Gist, loads from the raw Gist URL so it doesn't hit the GitHub API rate limit).
Code + prompt + notes here: https://gist.github.com/matznerd/ece297107bd99ac028c7962c217...
Basic concept is to:
1. Put a Worker on the /markdown-svg-renderer route. Normal visitors get your page exactly as it is now.
2. When a link has ?url=<gist>, the Worker reads the Gist and adds og:title, og:description and og:image to the page's HTML. Link previewers like Slack and iMessage don't run JS, so this is the only way they see them.
3. og:image points to a second Worker URL (og.png?url=<gist>). It takes the SVGs from the Gist, puts them in a grid, and converts it to a PNG, since previewers won't show SVGs.
4. Both results get cached per Gist, so each Gist is only fetched and rendered once, even with a lot of traffic.
Things to customize:
- Title and description (mine: "gpt-6-luna SVG of a pelican riding a bicycle" / "6 runs, reasoning effort none to max")
- Grid of all runs vs just one image, plus layout, labels and font
- How long to cache (I used a day, but edited Gists keep the old preview until it expires)
Luna 6 High: https://threejseval.com/models/gpt-6-luna-high
Sol 6 High: https://threejseval.com/models/gpt-6-sol-high
You can compare any other model on the same prompt. Gallery unlocks after 4 votes: https://threejseval.com
Everyone said tokens were too expensive but these are getting close to free while still having fantastic performance.
Is it? It was already too cheap to meter for me. Luna 6 is actually worse on some benchmarks than 5.6. I’d have loved improved performance for 2x the price than ~equal performance for 0.5x the price.
I expected a Fable 5 -> Opus 5 situation, where GPT 6 Sol would perform on par with GPT 6 Astra.
Instead it's more like a price cut on GPT 5.6 Sol, and I'll have to stick with Astra for my work.
The only thing I can hope for is that more users switching to the GPT 6 Sol model frees capacity, allowing OpenAI to hand out some usage resets.
They put both legs on the same side of the bike.
Even Astra max which actually put one leg on each side of the bike still somehow messed it up because when it added the bike chain, it put the left leg between the bike chain and the frame.
Is what I'm getting on the top two links.
Half the price when it launched, or after the price dropped by 75%?
> GPT‑6 Luna vs. GPT‑5.6 Luna | $0.20 → $0.10 | $1.20 → $0.50 | 50% cheaper
I can read it as follows (below), meaning that GPT-5.6 is 50% cheaper.
- GPT-6 = $0.20
- GPT-5.6 = $0.10
+--------------+-------+--------------+--------------+--------+
| Model | Input | Cached input | Cache writes | Output |
+--------------+-------+--------------+--------------+--------+
| gpt-6-luna | $0.10 | $0.01 | $0.125 | $0.50 |
| gpt-5.6-luna | $0.20 | $0.02 | $0.25 | $1.20 |
+--------------+-------+--------------+--------------+--------+good god
I'm so tired of looking at benchmarks. I always look fwd to the pelicans.
And Astra medium seems to yield similar or better quality for the same price as Sol 6 xhigh.