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Discussion summary

GPT 6.1 Sol is priced significantly lower than competitors like Opus 5.5, but faces mixed reviews regarding its performance. Some users see it as a cost-effective option for hobby projects, while others criticize its output quality.

What the discussion says

  • Some users praise the lower price and potential for hobby use.
  • Critics point out the model's inaccuracies and limitations.
  • The market is experiencing a race to the bottom in model pricing.
“Shots fired, half the price of Opus 5.5.”
— aaronbrethorst
“Near-Astra intelligence? More like near-miss on JSON schema output.”
— barrenko

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  • Hacker News
  • I love free market competition. We're getting insane advancements every day. I remember when llms used to cost an arm and a leg for decent intelligence
    by Nevin1901
  • There was a model called Astra-Minor, found in the files a few days ago. I assume Sol 6.1 is this, as a last minute panic rename due to Sol 6 being underwhelming while Opus 5.5 turned out really strong. I can't really explain releasing Sol 6 in any other way, especially mere days ago.
    by revolvingthrow
  • The GPT 6 release was ... not great.

    Sol 6 was so bad that I switched over to Opus 5.5 exclusively.

    Huge regression compared to Sol 5.6, often doing really dumb things. Same for Luna.

    Even Astra is very unreliable for coding. Brilliant for vision, sometimes just great, but it also often does very stupid things.

    I'm a bit sour on OpenAI right now and skeptical that 6.1 will be much different.

    (Note: this is after preferring and shilling Codex/OpenAI models for the last half year)

    by the_duke
  • We tested it across 100 unsaturated coding and engineering environments. Both Astra and 6.1-Sol are pretty comfortably ahead of Opus 5.5 in these types of evaluations, and both end up being cheaper than Opus via API usage. 6.1-Sol is also cheaper than Sonnet 5.5 and much smarter. The only verifiable domain Anthropic seems to be clearly ahead is chemistry (and perhaps also some unverifiable domains like being pleasant to work with, since GPT-6 models have a tendency to be low initiative beyond what the prompt tells them). Highly recommend using the OpenAI Flex endpoint for any API work.

    Data at https://gertlabs.com/rankings

    by gertlabs
  • Ominous for the industry and investors that token price is becoming the main battleground. Could be Anthropic's rationale for IPOing this year.
    by gradus_ad
  • I must say that this AI thing is going more or less as I felt it would back about a year ago. I think there is no real moat in AI models. It's a commodity and the big labs have predictably been caught in a race to the bottom. Not sure if this is going to turn better or worse for all of us common folks. I must say I'm a bit happy though in the sense that "intelligence" is not going to be controlled and be rented out by a small minority.
    by whatifitoldyou
  • > 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.

    by minimaxir
  • I'm a bit late with the pelicans because I was live-blogging the keynote: https://simonwillison.net/2026/Sep/29/openai-devday-2026-liv...

    Here they are for GPT-6.1-Sol: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

    They're not notably different from the GPT-6 family pelicans: https://static.simonwillison.net/static/2026/gpt-pelicans-gr...

    by simonw

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