GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.
Here's GPT-6 Luna pelicans: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F40d129fc140faca378b9c9f4f16c6ec2" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
And GPT-6 Sol: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Fbe7ae25af2634b68bc34b7b7aaf02cb2" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Scroll to the bottom for the GPT-6 Sol max one: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Fbe7ae25af2634b68bc34b7b7aaf02cb2#response-5" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
For comparison, here are the pelicans I got for GPT-6 Astra: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Ff789d2784fc6c5b870cc80f0b7cd9d01" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - I still like the Astra Max one best.
Here's a comparison grid showing all of the GPT-6 and GPT-5.6 pelicans at all effort levels: <a href="https://static.simonwillison.net/static/2026/gpt-6-and-5.6.html" rel="nofollow">https://static.simonwillison.net/static/2026/gpt-6-and-5.6.h...
The grid is actually really interesting, because it shows that the 5.6 family default to brighter colors than the 6 family.
6-luna is at the pareto for most of the tasks! I dont know how they make money here but its insane value from a closed source model. I'd go further and say it makes no sense (privacy, sovereignty etc aside) to use many other models as its not only expensive but also many providers don't have that much GPUs to serve at a significant volume. <a href="https://openrouter.ai/rankings?view=month#top-models" rel="nofollow">https://openrouter.ai/rankings?view=month#top-models 5.6 luna is already the most used model this month.
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.
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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.
This isn't right. You're comparing cost per token, but DeepSeek V4 Flash uses more tokens. Artificial Analysis found GPT 6 Luna to be significantly cheaper than DeepSeek: <a href="https://artificialanalysis.ai/models/comparisons?compare=deepseek-v4-1-flash%2Cgpt-6-luna" rel="nofollow">https://artificialanalysis.ai/models/comparisons?compare=dee...
Artificialanalysis benchmark is a combination of a several benchmarks which might or might not represent realistic coding:
"Artificial Analysis Intelligence Index combines performance across 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, and AA-LCR v1.1."
Not saying it doesnt have any value but it's probably irrelevant if you use these AIs for a specific use case. Like for example Humanity Last Exam tests general knowledge, which is not very useful for coding.
It's best to go to the specific coding benchmarks and compare there.
I had a favorite benchmark, SWE-rebench, but sadly it's no longer maintained.
But yeah, I'll just take these benchmarks with a grain of salt. Only hands-on experience matters in the end, and these days it's very easy to switch models.
simonw · · focus · HN ↗
Here's GPT-6 Luna pelicans: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F40d129fc140faca378b9c9f4f16c6ec2" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
And GPT-6 Sol: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Fbe7ae25af2634b68bc34b7b7aaf02cb2" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Scroll to the bottom for the GPT-6 Sol max one: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Fbe7ae25af2634b68bc34b7b7aaf02cb2#response-5" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
For comparison, here are the pelicans I got for GPT-6 Astra: <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Ff789d2784fc6c5b870cc80f0b7cd9d01" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - I still like the Astra Max one best.
Here's a comparison grid showing all of the GPT-6 and GPT-5.6 pelicans at all effort levels: <a href="https://static.simonwillison.net/static/2026/gpt-6-and-5.6.html" rel="nofollow">https://static.simonwillison.net/static/2026/gpt-6-and-5.6.h...
The grid is actually really interesting, because it shows that the 5.6 family default to brighter colors than the 6 family.
gizmodo59 · · focus · HN ↗
sieve · · focus · HN ↗
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.
nearbuy · · focus · HN ↗
dudisubekti · · focus · HN ↗
"Artificial Analysis Intelligence Index combines performance across 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, and AA-LCR v1.1."
Not saying it doesnt have any value but it's probably irrelevant if you use these AIs for a specific use case. Like for example Humanity Last Exam tests general knowledge, which is not very useful for coding.
It's best to go to the specific coding benchmarks and compare there.
aucisson_masque · · focus · HN ↗
dudisubekti · · focus · HN ↗
But yeah, I'll just take these benchmarks with a grain of salt. Only hands-on experience matters in the end, and these days it's very easy to switch models.