OpenAI slashes GPT-5.6 Sol API prices until at least Nov 21
OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)
OpenAI has temporarily reduced API pricing for its GPT-5.6 Sol model, cutting input costs by 20% and output costs by 33% for standard usage, with similar reductions for cached input and cache writes. The discount applies to both short and long context windows and is available until at least November 21. Developers using the API can take advantage of the lower rates for a limited time, potentially reducing their inference expenses.
Prices per 1M tokens.
- eigenspace
The fact that AI models can be so easily distilled and replicated is such a stroke of luck.
10 or 15 years ago if one had asked me to envision a future where a private company invents artificial intelligence, I'd have thought for sure they'd have a massive moat, be very difficult to catch, and it would create an almost instant monopoly.
Rather, it seems that selling intelligence might end up as a race to the bottom.
Who woulda thought that just having access to enough textual inputs and outputs and a vaugely similar transformer architecture would be enough to copy-cat rather useful intelligence.
- ComputerGuru
It's a 20% discount on input and a 33% discount on output through at least November 21, 2026; the revised pricing schedule is now
Model Input Cached input Cache writes Output
gpt-5.6-sol $4.00 $0.40 $5.00 $20.00
gpt-5.6-terra
$2.00 $0.20 $2.50 $12.00
gpt-5.6-luna
$0.20 $0.02 $0.25 $1.20
So Sol is still 20x Luna, but much more appealing when compared to offerings from Anthropic and others.
- m101
These are my opinions on which circumstances Sol fails terribly vs Fable.
I am the type of coder that vibe codes - I talk to the agent about a problem, have it write a plan, red team the plan, and then implement the plan. These projects are things which haven’t really been done before, or if they have it’s not public or not in many places.
What I find is that Sol is hyper-left brained. Super focused on small details. When given a longer task with multiple steps it might go really hard on one of the early steps and it will validate, test, make safe, so much to the detriment of progressing the task within reasonable parameters for the project.
It also starts to sound crazy when you ask it for an update. It starts naming things in weird ways and the sentences don’t really make sense. It’s as if you’ve approached an engineer who has been hammering on something and he speaks to you in the lingo of his latest function, even though when you ask him for a status you are obviously asking about the whole project.
Fable on the other hand seems to remain coherent over time. It’s as if it remains aware of the longer run task. It’s got a bit more balance between left and right brain.
So OpenAI really need to find a balance between long term goal thinking and the very small task at hand.
For coders who apply Sol on specific functions or narrow tasks I’m a certain it is great. For me, a vibe coder, I need one that will be a bit more aware of the whole thing through these longer running tasks […]
- sandle
Absolutely loving this price war, long live open source models.
- AM1010101
50% off at open router is also still applied so it comes out at $2 / $10 per 1M.
Feature request for Artificial Analysis, allow us to see these live prices on the pareto. It would amazing to also see what a 25,50,75,100 % utilised subscription costs compared to raw tokens.
- ninjahawk1
Once they make a model better than Fable I’ll be switching to Codex. Their priorities in terms of consumers seem to be better. I do think Anthropic has some solid safety viewpoints, but I don’t necessarily think that either is entirely aligned yet with delivering exactly what humanity needs. Maybe the AI will help align the AI companies when it gets smart enough. That’s the real misalignment I’m concerned about.
- artrockalter
This stacks with the 50% discount in OpenRouter, making it $2/$10. https://openrouter.ai/openai/gpt-5.6-sol
- blobbers
The top comment on this thread was about AI models being easily distilled being a stroke of luck.
This should not be surprising at all. Every new students spends tiny fractions of time learning knowledge that took many lifetimes to discover. This fundamental to the progress of intelligence and understanding.
It should not be surprising that AI can be distilled. It's the logical method of training; I would hope that each frontier model is in fact not trained 'from scratch' each time.
We should expect future frontier models are simply distilled versions trained by specialist models, the same way humans learn from a series of professors, papers and canonical books on each different subject material. Models like this can be trained incrementally, or a so called Mixture of Experts (MoE).
- nahnahno
My prediction is that this becomes permanent. There is no good reason to be much more expensive than opus. At $4/$20 they are roughly at parity.
Making 2/10 permanent would be a killer move and make a strong argument against open-weight. For the sake of the open weight ecosystem I hope they do not.
- badatnames
Using codex every day, in spite of which, I hope some day providers will just start naming their offerings small/medium/large, a bit like we eventually started doing in software testing. Trying to remember what Sol is or why it's better than the other thing is more cognitive effort than I can muster at this point. And that's a sure sign of commoditisation in itself