GPT-6 Sol and Luna (openai.com)

The sol max looks like it's absolutely ripped for some reason

Looking at this, AI still has a long way to go. In Sol Max, the pelican's legs are missing on one side—how can one side have two pedals and two legs...

> GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.

Is it? It was already too cheap to meter for me. Luna 6 is actually worse on some benchmarks than 5.6. I’d have loved improved performance for 2x the price than ~equal performance for 0.5x the price.

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. https://openrouter.ai/rankings?view=month#top-models 5.6 luna is already the most used model this month.

    I dont know how they make money here

Not that this benchmark is super relevant anymore but these look worse than I expected.

When the Astra one was last time run? It's probably better to run these 2-4 weeks after release when models get nerfed to get idea of performance closer to what it is.

Isn't everyone pelican-maxxing these days?

How come the pelicans get older with more reasoning? Is GPT 6 taunting us with our mortality?

Is GPT-6 50% cheaper?

> GPT‑6 Luna vs. GPT‑5.6 Luna | $0.20 → $0.10 | $1.20 → $0.50 | 50% cheaper

I can read it as follows (below), meaning that GPT-5.6 is 50% cheaper.

- GPT-6 = $0.20

- GPT-5.6 = $0.10

  +--------------+-------+--------------+--------------+--------+
  | Model        | Input | Cached input | Cache writes | Output |
  +--------------+-------+--------------+--------------+--------+
  | gpt-6-luna   | $0.10 | $0.01        | $0.125       | $0.50  |
  | gpt-5.6-luna | $0.20 | $0.02        | $0.25        | $1.20  |
  +--------------+-------+--------------+--------------+--------+

Do you have a page showing all the pelicans you've ever created? Could be fun to browse - kinda like https://progress.openai.com/ but visual. (It's a shame they don't keep it updated)

I'm so tired of looking at benchmarks. I always look fwd to the pelicans.

I find it very interesting that for both these models we such a clear progression of better images with higher thinking levels from 'hardly useful' to 'pretty nice'. I feel on many other models low and max are much closer.

If you're happy with letting Meta train on you, Muse Spark 1.3 Contributor pricing is a much better deal than Luna

Is Luna (on "low" thinking) the first left handed model?

Many of them still get the layers wrong.

They put both legs on the same side of the bike.

Even Astra max which actually put one leg on each side of the bike still somehow messed it up because when it added the bike chain, it put the left leg between the bike chain and the frame.

out of curiosity, do you retry the same model multiple times to see the range of output it comes up with? or is it purely a 1-shot test

What's with the radial spokes? When are we gonna start seeing proper cross lacing?

> GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.

good god

It's surprising but MiMo V2.6 Pro performs better and is cheaper than GPT 6 Sol on my benchmark[1]. Open weight models are really snapping at the heels of the major western models.

1 - https://bench.killswitch-lang.org

What I like about the grid of SVGs is from I can see that Astra high seems to yield similar quality and price to Sol 6 max.

And Astra medium seems to yield similar or better quality for the same price as Sol 6 xhigh.

Out of all of the benchmarks out there, pelican bicycle bench is the only one I care about. Thank you Simon.

That GPT-6 Sol max pelican looks… so old and depressed.

It's funny that even Astra doesn't know you ride a bike by straddling it between your legs. (EDIT: Oh, I guess Max gets the occlusion. But it doesn't realize it has to pick direction the knee bends in.)

Simon, love your work, one piece of minor feedback for the individual model pages is to make the font of the model name potentially bigger than (and above) the conversation id (which means nothing to the audience) "2026-09-22T18:28:00 conversation: 01m355zvyw8946qyraa8zpz6h9 id: 01m355zvyx47zxx5c6q6b3fg0m#".

I had all the tabs open individually and harder to scan which model is which... otherwise keep up the great work! I like the grid view a lot. (Also the pages have no OG images set, which impacts what the link looks like shared)...

> half the price of GPT-5.6 Luna

Half the price when it launched, or after the price dropped by 75%?

My new sub-benchmark is which combinations achieve the hook at the end of the upper beak. Right now just 4: Astra Max, XHigh and Medium; GPT 6 Sol Max

I've been sharing that pelican grid in my circles a whole bunch, it's great! I think only one data point is missing, generation speed. Would be interesting to see how the reasoning level/token counts relate to speed.

> Error: Gist API returned 403

Is what I'm getting on the top two links.

Wow I cannot believe Luna is getting even cheaper. IMO this is the model that is going to change the world.

Everyone said tokens were too expensive but these are getting close to free while still having fantastic performance.

looks like they're positioning luna to tackle the low-cost cn models

What I overwhelmingly love about that Pelican grid is the two best ones, they've put a neck scarf on to show speed and wind.

Here are some somehow standardized pelican tests but for 3d scenes in threejs at threejseval.com

GPT-6 Luna High: https://threejseval.com/models/gpt-6-luna-high

GPT-6 Sol coming soon on the site.

You can compare any other model on the same prompt. Gallery unlocks after 4 votes: https://threejseval.com

I dunno about Codex-the-application itself, but you can definitely use e.g. Pi with the larger context windows with a Codex login. It puts a pretty large multiplier on credit usage, however.

> It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems

As far as I know Codex (at least the GUI) can automatically call the ChatGPT Chat models (including Astra 6 Pro), you just need to @ a ChatGPT Chat conversation from within Codex and tell it when to use it.

> There used to be a toml file workaround for Codex to extend the GPT context window to 1m, but this stopped working on the plans and only on per-token billing

Not true, it works again[1]. I confirm that it works both on 5.6 Sol and Astra 6, possibly other models too.

[1] https://x.com/thsottiaux/status/2089082893804896524

In my personal experience I currently get a lot, lot more usage on the 5x Claude plan than the 5x Codex plan.

Having limitless webUI ChatGPT usage is much better user experience, though. I'll give them that.

(edit: Sol-6 is half the price, so maybe the usage limits are going to be way better.)

> Winner right now is Codex by a mile

Opposite in my experience. I need to limit codex to 500k on medium/low, still run out in 2-3 days with 1 CLI window. CC gives me 4-5 medium/high days with 2-3 CLI windows, and Opus is still great for other regular dumb engineering/refactoring.

On the other hand my head starts to hurt if I read Opus for too long, hopefully they fixed it with 5.5.

What are you talking about? ChatGPT unmetered? No way! That was 2 months ago perhaps and it’s possible your account still hasn’t gotten the new limits. I noticed around 1 month ago I was still going full throttle on my codex subscription and my limits were barely budging, and then all of sudden people around me started to complain about limits. I thought they’re crazy, but then my account go the hammer, and that was it. If I have the same pattern of usage like I did before, basically having an agent working continuously on a coding take, my weekly limit goes in 2 days.

Codex/ChatGPT Pro 20x isn't really a thing now, they have disabled it a week or two ago.

Not that I disagree that Codex wins out, but the deciding factor actually is - Codex Pro 20x is not available for purchase, indefinitely. So, what's the point of this discussion? People who already have the 20x sub are unlikely to cancel, and the rest of us can't access it.

theres a popular thread on claudecode or claudai subreddit that proves 20x isnt really 20x. apparently its a marketing gimmick and the recommended solution is two 5x plans > 20x at greater than half the cost of the 20x

> Usage limits [...] Winner right now is Codex by a mile

This hasn't been the case since around July. If you measure usage in raw api costs, Anthropic is actually giving more on $200 than OpenAI now. This includes resets. Usage allocation difference would be humiliating for codex subs were it not for resets. But fixing usage limits with resets is ugly, and they're not good for your mental well-being.

> Context window in the harness

Codex now allows 1M for subs with config params. But generally speaking, you shouldn't really be using 1M context. If you accidentally send a request with say, ~700k context already accumulated in a session which is outside cache TTL, you're paying full cost of these 700k tokens.

> I've subscription hopped a bunch

OpenAI actually has a new strategy to prevent subscription hopping after their 2-3 month-long marketing push to get claude-folks to switch over:

you can't buy a $200 sub anymore. So if you cancel, you won't be able to get back in. Hostage situation, essentially.

EDIT: re: usage limits, oh-my-pi maintainer has been tracking this - https://nitter.xitter.cc/_can1357/status/2090075496948060372

Maybe it's due to 20x / 5x != 4 but I have the $200/mo Claude and $100/mo Codex and I get _way_ less usage on Codex, well under 1/4th the usage. In 1-2 days of semi-heavy _single_ agent usage with Sol High I can burn through my whole week of Codex. Again, this is not running multiple agents, just 1 at a time.

Compare that to Claude and I can run multiple agents on Opus almost indefinitely. YMMV of course but I was shocked at how quickly I burned through Codex usage.

On the context window, I feel so cramped on Codex, compacting happening every time I turn around is annoying. I didn't realize how much I enjoyed the Claude context window size.

> Claude Code 20x and Codex Pro 20x

That isn't a valid comparison, since Codex 20x is closed. So we should be comparing Claud 20x to Codex 5x + credits.

Also in Codex, even though you can increase the context window to 1m so its on par with Claude, exceeding the default is billed at 2x.

Also, OpenAI is just a company I'd rather support than Anthropic.

While you're understandably not including the values of the $20 standard plans on both, I find the generosity of then token limits on ChatGPT plus vs Claude Pro (it's a huge difference) to be good representation of their respective attitudes towards the average user. You literally cannot use Claude pro to build real software, unless you're extremely frugal with your prompts and don't try anything even a little ambitious.

Also, Anthropic has zero models comparable to Luna.

Astra planner/designer with Sol+Luna subagents has worked well for me to improve context continuity. Luna generates code, Sol reviews code and runs/monitors integration/E2E tests. It's about 20% more usage efficient and 20% faster to finish tasks. I've been very subagent-skeptic for a while but the economics of codegen with Luna have made it click. This just works in Codex with a single-line AGENTS.md instruction.

> Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.

I'm quite puzzled about why Anthropic is so hellbent on blocking other coding agents. It's not like Claude Code has any secret sauce, right? And doesn't Anthropic make monkey off API usage, and their magic is on the model side anyway?

Usage is actually Claude now because of Opus 5.5 since it a better model that Astra. I maxed out my 200$ Claude plan with 10b token on Opus 5 and 5.5 is cheaper. I maxed out two Codex accounts with like not even 5b tokens.

It's extremely variable because the products are roughly equivelant, and a lot of the quality of service depends on their inference capacity at any given hour/day.

> especially when you factor in ChatGPT usage (even 6 Astra Pro) is essentially unmetered on the 20x plan.

I’m currently on the 5x plan and burned through 5% today on a difficult task in 15 minutes so I doubt that. If you got the wrong kind of tasks that you work on, it can go fast.

cool! for me its company ethics

OpenAI have seemed compute-constrained recently, leading to their subscriptions actually being less generous than Claude as of late. OpenAI even paused purchases of 20x plans.

> that ChatGPT usage (even 6 Astra Pro) is essentially unmetered on the 20x plan

LMAO, I wish this were true, I hit limits (and the "we are disabling access to protect your data" warnings) all the time, or have chats just...fuck off and get into weird/invalid states (interrupted chats, chats that are spinning and stuck, returning "/mnt/" paths instead of images/md files, file links being returned with no file backing them, image classifier firing...and then returning the image anyway (though now I know that GPT-Image-X really really wants to generate NSFW even when that isn't the request)).

Though I am probably an outlier, I have both 20x Claude/ChatGPT plans and max both out every week, so... (in my defense I am a hobbyist and this is out-of-pocket)

> "Codex's compaction is very good, fwiw, but it happens so frequently that..."

I appreciate and follow Matt Pocock's advice: avoid autocompaction. Compaction is lossy, which is ok when you're managing it at phase boundaries, but autocompact is lossy at the most inopportune times, firing mid-task and leading to agents going off the rails.

Codex used to rule in the usage limit front, but GPT-6-Astra eats up quota like crazy.

Same. In fact I found 6 Astra to be a downgrade in situations where I didn't need the extra intelligence.

Completely agree. I've been using 5.6 still even with Astra available to me for most tasks. It's funny how much of this is just "vibes" because I cannot quantify what it is. Astra is definitely better when I have an ambitious feature, but in like 9/10 tasks I prefer working with 5.6 Sol. A few weeks ago when the limits were seemingly higher, having 5.6 on fast mode was a good time.

This is 100% my experience. I rarely reach for Astra as we speak.

It's a shame the labs don't open source their models after deprecating them. I get why, but, it's a piece of internet history I hope is preserved.

I agree. Sol followed my instructions well and wrote good code.

This has been my experience for a year. Same with Opus models. This is how I think this tech will be best used in the long term - finding the one you vibe with most. Much like IDEs!

Not only was 6 worse the 5.6 Sol for my me, but it went through my Plus usage in minutes, while I could cruise for hours with 5.6. It would churn on a basic prompt for minutes and then just give up on usage limits.

Highlight and lowlight of my week was successfully convincing the OpenAI support chat robot to give me a refund for the month for my issues with 6 chewing threw my usage with no output.

I had this experience as well, but after rewriting my agent instructions it has been far better. I believe Astra’s “token efficiency” translates to “don’t research as much” which caused it to make poorly informed architectural decisions.

Similar for me. gpt-5.6-sol high has been my go-to for months. One of the reasons I'm pushing myself to try open models more is because it lends some level of guarantee I can continue to use the same tool as long as I want to. And I think we may just be getting to the point the open models are >= 5.6 Sol for coding.

Agree as well and I had a much worse experience with GPT 6 Astra for some reason.

I felt that was about 5.5. IMO 5.6 Sol was overindexed: more verbose, prone to overengineering.

Yeah 5.6 Sol is what got me to switch from Anthropic. I couldn't deal with Claude's Ted Talk responses to literally everything. Sol has been nice and concise and just stays out of the way.

Same. The way I would describe it is that I can mostly leave 5.6 Sol overnight and trust that it makes good progress, maybe stumbling a bit and needing some correction for the remaining 20%.

If I leave Astra overnight, I'll wake up with three new different projects, each of them 20% done and having nothing to do with my original goal.

Agreed! I found it excellent: - Relatively fast (especially compared to Opus 5) - Non-verbose prose, both in interaction and as code comments - Good code quality

Like you said, it felt very natural to work with. Opus 5 is way too slow and verbose for me, I find I get distracted and annoyed with it.

Opus 5.5 seems a LOT closer so far to what I liked about 5.6 Sol but we'll see

You can get a lot of Codex usage out of that same sub on top of ChatGPT usage. Its a really good value and you can use that sub in any harness. In OMP I have Sol high as the orchestrator, Sol max as Planner & Reviewer, Luna max as task/coder. Very good setup. I'm on pro now and there are weekends when I use half a week's usage but I'll have 5 or 6 sessions going at once for many hours each day.

> ignoring the initially terrible Codex app

Still needs a LOT of work IMO.

Not even for the average person. Luna is an amazing model for most coding tasks.

These don’t necessarily reflect actual costs, OpenAI is not profitable and nowhere near. They’ve lost their market lead and Sam may feel they need to get it back with any means necessary.

The last time I gave GPT a shot, it ate all my tokens and got nothing meaningful done.

A vs B

Should be B vs A correct?

Else it's confusing

GPT would charge more if they could. Both companies need way way more revenue. GPT simply made a calculation that they can earn more money by charging less than their competitors.

Opus 5.5 is incredible so far, its going to get used. Fable is much better than Astra for me in practice, and Sol is not marketed as better.

Its a great release, I will use both heavily.

For API usage, sure. But plenty of people have subscriptions where these differences effectively don’t matter.

Also, batch processing prices are still 50% off, which put GPT-6 Sol and GPT-6 Luna at $5 and $0.25 for output.

https://developers.openai.com/api/docs/pricing?latest-pricin...

I could already run Sol High on 3 concurrent side projects 24/7 and not run out of quota.

This is great, but practically, I'm not going to start working on more side projects.

Perhaps in another 6-12 months I'll be fine to drop down to $20/m instead of $200.

>> GPT‑6 Sol vs. GPT‑5.6 Sol

>> $4 → $2

>> $20 → $10

Do you mean 100% more expensive? GPT 6 is 100% more expensive than 5.6 per your post.

You also need to compare allowances on Codex vs. Claude Code

Wtf is GPT-6 Sol, I though GPT-6 is Astra?

Disagree. I would never use OpenAI cause they're probably just going to steal whatever I'm working on.

These are the pre rug pull prices. They'll increase prices 10x and nerf the models after they IPO.

Not that anthropic models are very good at this, but due to the changes in tokenizers and thinking tokens: cost per token is not as helpful anymore as cost / task.

As someone who has used Claude Code and Codex the prices don't matter in the same way but I found that I burned through my usage way faster on Codex even though I regularly hear that the Codex plans go further. That was not my experience and the intelligence was comparable to what I was getting in Claude.

If these price changes mean that coding plans have effectively more usage then that's great, but Codex is surviving on resets from my own experience using it. I was glad to go back to Claude.

I mainly use Codex/Sol to review my plans drafted by Fable. But beyond that, Astra blows through usage limits too fast to be a daily driver and writes weird code despite what my "house style" is, and Codex is behind Claude Code in terms of critical features like seeing what's going on in subagents.

The parent + subagent workflow has become critical for keeping the reasoning agent (parent) context-lean while also letting me chat to the main agent while work is getting done.

My main process is to use Fable to reason and then spawn Opus subagents, and I get amazing results, and I'm always looking into what the subagents are doing.

> 50% cheaper

Cache read/write decrease by 50% or similar? That's where most (95%+) of the cost is for agentic coding workloads.

I legit question if these prices are still inference-profitable for OpenAI. They likely didn't have 100% profit margin.

> it's pretty incredible what the OpenAI team is doing

We don't know how much they are bleeding financially, it might just be a front

The major difference being the 1M token context window. Once you exceed 272K input tokens, Codex Sol is roughly the same price as Opus; and Astra similar to Fable.

>I don't see how anyone can be using Claude with prices like this

One potential deciding point is that Claude still has a $200/mo 20x plan, where, since Sept 11, OpenAI does not and has no ETA for the return.

I downgraded my OpenAI plan 2 months ago to the $100/mo, but my usage has gone way up, but now I can no longer upgrade to the $200/mo plan ("This option is temporarily unavailable"). Thankfully I have 2 usage resets available, but I'll probably be switching back to Claude; I was super happy with Astra but I'm burning through tokens and have 4 days before my next reset.

Astra 6 was a huge improvement over Sol 5.6 for UI work. I haven't tried Sol 6 yet for it (it's only been a few minutes).

The GPT / Codex models have always been "overengineer" personalities. I prefer that to "I left a pile of race conditions lying around and big gaps in testing" though, which is what I was getting from Opus at times.

But yes both Astra and Sol veer on the side of paranoid. And honestly that's better for team work. For solo work where you just want to yeet something, it can be tiring.

You learn to tame the GPT "personality" on this front by combing over once a week and asking it to find and exterminate pointless tests, clean abstractions etc.

The UI design gap is something I’ve noticed as well, in things as simple as ASCII diagrams. Claude has a more human touch. All the diagrams GPT 5.6 generated for me were dressed up lists with too many pipe symbols.

have you tried using lower efforts?

> design

I force OpenAI models to use image generation for design, then an iteration loop until it matches the image gen.

This is frustratingly manual and takes many more repetitions compared to Claude (and especially Claude Design) which "just work", but it's a big step change over the default.

We’re all gonna be meat proxies

Take solace remembering that we are all in the same boat.

In 1840 ~70% of the population was in agriculture. That is now ~2%. Things change.

If you were alive right before industrialization, you probably would’ve been one of the people wishing that would stop too.

That depression tells me you do.

price discrimination. They want to capture low and high cost agent requests, and different workflows.

Seriously! Though I prefer GPT models to other frontier models, this shit is confusing. They keep changing the names of these models and they often don't communicate anything meaningful about the model itself, especially with these latest iterations. At least with "mini" and "nano" you understood they generally had differing speeds and "reasoning" capability, but what the hell do "Terra", "Sol", and "Astra" really mean? Which one of them is the effective successor to gpt-5.4-mini? It's hard to tell since the only objective information you'll get is token pricing. Is Terra less capable than Luna because it makes me think of dirt and grass? Or is Luna less powerful because the Earth is bigger than the Moon? Apparently that's the real answer. And why do I even have to think about this? And what comes after Astra? Galactica? Or will they start naming the succeeding models after different candy bars? Should I even care since a new model will get farted out mere days after I figured out what differentiated the last one?

What's unclear to me is who OpenAI thinks they're marketing to with this form of branding. These different models don't really mean all that much to the vast majority of people using their products who aren't developers, and developers aren't helped at all by the way they've been naming said models. Are they merely scared that they'll become irrelevant because Anthropic decided to give their models quirky names like "Opus" and "Fable"?

If OpenAI really wants to give their models names, they should name the generation of model and then have the different sub-models named by purpose or capability level. After all, I wouldn't use Mini for a job that Nano could easily do, and I wouldn't use Nano for a job that the full version of GPT-* necessitates. Similarly, I've had to discover exactly how Luna, Terra, and Sol are appropriate for different complexities and task types. OpenAI could help me skip a lot of those steps and just tell me what each model distillation is good for without causing me to look through their pricing page and make educated guesses. After all, shouldn't they not want me to pay attention to how much they're charging me?

All of this makes the days of frontend framework churn seem quaint and actually preferable.

Ya it’s annoying to have to manage this.

But effort is basically how much extra internal scratchpad to use and how much extra questions to ask and answer before producing a result, Exploring more hypotheses, validating consistencies, calling more tools.

If you’re happy with your token spend on Astra then keep doing what you’re doing. but if you feel the need to conserve tokens, then you can do that by switching to smaller models like Luna when the task is straight forward.

For easy problems, just use Luna on max level. It has so much token mileage you can go forever.

I would describe it as "fidelity" and "verbosity" (or just amount of token generation to complete the task, sometimes that works out to scratch space, or literally how large the "solution" is).

If you have something that needs to be done right, might be a bit complicated, up the model size.

You can see this in the pelicans. Big model pelicans are pretty accurate by default. Up the reasoning and only more so, but with more detail. For Astra, it is 105 lines for low, 250 lines for max reasoning.

Small model pelicans will lack the fidelity of a large model. Bits will be out of place etc. For luna, it's 90 lines for low, 150 lines for xhigh.

Additionally the amount of time taken is increased for the larger models. Luna takes 11 seconds on low, and 1:33 for xhigh. Astra is 33 seconds on low, 4 minutes on max.

And naturally, there is the cost. There's some overlap in functionality between luna xhigh and Astra low in the sense that luna really can do quite a suitable job for some tasks. But there are just some tasks that just don't make sense for Luna, even at high reasoning.

The other thing to remember is that sometimes high fidelity isn't ideal. It can lead to overdesigning. My recommendation is to commit early, commit often, and review everything you do, which we've all been doing since before LLMs right?

there is no correct answer for that. One is the difference in size/params. The other is the amount of "rounds" of reasoning generating and reviewing what is generated before the model decides it is good.

This is explained a bit in the API docs but you also have to adjust it based on your own tasks.

https://developers.openai.com/api/docs/guides/reasoning?api-...

I mostly just use frontier models as well. Except for one case: when I let the cache expire (I think 5+ mins of inactivity) I'll switch to one of the cheaper models to summarize and write a handoff note, then pick that up with the better model. Picking up a session whose cache expired with something like 200k tokens with the frontier model reflects really poorly on your usage.

Does API price cut translate into higher allowance on the subscription? Do we know?

I’d rather keep 5.6 Sol, and get that even more optimized. I’m not sure I’ll like 6 Sol if it’s anything like Astra.

they're already on bedrock

already at azure foundry and copilot

Per the benchmarks in the post, Luna 6 is at best a couple points superior to Luna 5.6 and (unless I’m reading it wrong) xhigh has actually degraded in quality?

I was hoping for a serious Luna upgrade. It was already cheap enough. This feels more like a price reduction than an upgrade.

That said, if the new Luna is able to handle ultra mode and subagents v2 in codex cli, then at least that’s a win.

The thin serifs not being slightly shifted to align weight-wise with the sans serif is triggering my OCD, but yeah Astra is miles ahead here

yeah I used to love claude! but these days it refuses and responds as if its like a big brother. glad competition exists and for the past few months codex has been significantly better. Even some oss models like glm are good but they dont have enough compute and get capacity constraints

Yup more like a 5.7 than a 6

Can we trust AA anymore after the last debacle a week or two ago?

Those two reasoning efforts are for entirely different classes of problems. I'd compare Opus Medium vs Sol High.