Thread

GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price

1066 points · 953 comments · crorella

minimaxir · 1790702170 · focus · HN ↗
> Cached input costs just $0.10 per million tokens—95% less than standard input pricing and 50% less than GPT‑6 Sol’s cached input pricing
This is the actual big announcement. 50% cheaper cache than GPT-6 Sol will get you far more mileage on Codex.
1. joshstrange · 1790703602 · focus · HN ↗
  > 50% cheaper cache than GPT-6 Sol will get you far more mileage on Codex.
  Cache doesn't help you much when you are compacting every 5 minutes...
  I was shocked at how quickly I ran out my $100/mo subscription with a single agent (sol medium).
  1. onlyrealcuzzo · 1790710720 · focus · HN ↗
    If you're compacting every 5 minutes, you have a workflow problem - period.
    No LLM will be cost effective if it's compacting this often. You have to find a way around it.
    ngruhn · 1790711655 · focus · HN ↗
    Context window is only 275k or something. And honestly compaction is not that bad in Codex. I often don't even notice I went through 5 compactions in a session.
    SyneRyder · 1790717378 · focus · HN ↗
    Sounds like that's the problem then, 275k is a tiny context window. I regularly have sessions that go to 450k or even up to 700k for an unattended overnight Claude Opus session.
    Apparently OpenAI makes you manually setup their 1 Million context window, and it seems to be only documented on X:
    <a href="https://x.com/thsottiaux/status/2089082893804896524" rel="nofollow">https://x.com/thsottiaux/status/2089082893804896524
    There's at least a forum thread about it here:
    <a href="https://community.openai.com/t/why-does-codex-report-a-258-400-token-context-window-for-gpt-5-6-sol/1394346/5" rel="nofollow">https://community.openai.com/t/why-does-codex-report-a-258-4...
    bjord · 1790763006 · focus · HN ↗
    > unattended overnight claude opus session
    yes, exactly
    SyneRyder · 1790763872 · focus · HN ↗
    Not sure I understand if this was meant as a slight against Claude? Or agreement?
    These are often my best sessions - they're unattended overnight, because by then we have the specification figured out, and I can just leave Claude to build out the rest, making good choices if it does find gaps in the spec. I regularly go to sleep & wake up to an entirely new application completed. Claude never uses compacting in my sessions.
    I haven't used GPT as much as I should have, so I'm prepared to be incorrect & out of date. It just intuitively feels like I wouldn't get the same from a 275K context window - maybe it uses lots of subagents? Even Deepseek & GLM have 1 Million context windows now, so it "feels" strange for people to actually prefer the 275K window. But that's just my intuition.
    bjord · 1790796534 · focus · HN ↗
    neither, actually, just that unattended "oneshot" sessions are incredibly token inefficient
    if you talk about them (in which you lean on an LLM as a sort-of independent employee) and conservative, chunk-based usage (in which you use the LLM as more of an extension of yourself), you're comparing apples to oranges
    a predefined spec obviously reduces that gap but how much is highly dependent on the level of detail

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