Coverage shifts focus to caching as the real cost lever
6 Today 7:00 AM · 16h ago · 3 articles · 3 posts · 11 comments · 3 sources · development 6 of 6
Follow-up reporting argued that prompt-caching discounts, not headline token prices alone, are the bigger factor driving down real-world inference costs for GPT-6 Sol and Luna.
“It communicates clearly, it's cheaper per token than Opus 5.0 with the intelligence of Fable 5.1 it's very token efficient and works across every effort level.”
Thariq Shihipar, Quoted commentator · hn ↗OpenAI Developer of GPT-6 Sol and LunaAnthropic Developer of Claude Opus 5.5Simon Willison Independent AI commentator/bloggerThariq Shihipar Commentator quoted on Opus 5.5Artificial Analysis Independent AI benchmarking firm
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What was reported 1 claim about this development
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first by The New Stack, 16h ago
What people said 12 voices · verbatim
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> This year, coding agents have begun tackling tasks with more complexity, scope, and duration than ever before. At OpenAI, our internal usage has grown exponentially. Valued at API prices, daily token usage has exceeded $600 for the median researcher and $7,000 for researchers at the 90th percentile (Research acceleration: The view inside OpenAI…
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#OpenAI launches #GPT-6Sol and #Luna, boasting lower cost and fewer mistakes
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Damn, Astra-Max looks really good at first glance, it even has the legs on the correct side of the bike (z-order for chain is still wrong though).I find it really interesting how consistent the layout is for these (facing right, with the sun in the top right).Just a little more progress on physically correct z-ordering and these won't be easily…
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Looks like good one this time. Moving from fine tuned gpt-4.1-mini for structured outputs to gpt-5-mini made zero sense just because 5 was reasoning model and there was no way to disable the reasoning and it also did not have support for fine-tuning.So essentially I was not able to get nowhere close to the accuracy of previous model and it was…
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> The grid is actually really interesting, because it shows that the 5.6 family default to brighter colors than the 6 family.Could you elaborate on what it is about that observation that is "really interesting"? It is a fun detail, but does it actually mean anything for usefulness or progress or anything really beyond "gpt-6 makes darker…
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We tested this on our agentic CAD coding harness. This seems like a decent improvement vs 5.6. It's lower costs seems to be offset by more token use so those cancel themselves out, but the actual results for spacial reasoning and coding are an improvement.
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To me it's super interesting that OpenAI released GPT-6 Sol and Luna & Anthropic released Opus 5.5 within hours of each other.These models are significantly cutting down the token costs by almost 40-50% as compared to their predecessors. This is exactly what people need - cutting edge intelligence at half the cost.
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Also, Terra is gone, GPT-6 Luna is smarter than 5.6 Terra and costs *15x* less [0].[0]:
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What surprises me every time with the pelican benchmark, is that drawing style is very consistent within each model across, what I believe, are independent sessions. Same tones, similar background... Just more refined with increasing effort. I would expect much more variability.
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I'm trying to test them but the Visual Studio Codex Extension on WSL2 is not helping.It seems there's a bug, shipped together with the flag that enables the new models, that doesn't allow Codex to run properly in the WSL2 sandbox.
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Surprisingly, I am very pleased with Luna, but Sol is in terrible shape. There is a clear regression, except at Xhigh or Max effort.
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I am starting to wonder if this test is now being heavily benchmarked internally we should be using some new test?
All 6 developments of OpenAI and Anthropic trade blows in AI price war: GPT-6… →
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