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There's a bunch of skepticism in the replies but I ran over 100 tasks against DeepSeek 4.1 Flash and Sol (among others) and I can confirm, it is in fact a little smarter than Sol and a little more expensive than Luna. https://slopcop.com/power-ranking?pricing=api

I also spent $280 on DeepSeek doing the tests (direct to DS, not OpenRouter). I suggest that if you can't conceive of anyone spending $200 on DeepSeek, you're not being ambitious enough!

Were you using OpenRouter? I've used 1.8bn tokens in the past week from DeepSeek themselves and 99.2% were cache hits. Total cost was $18.13 usd.

Same experience. I often see people say how little they spend on DeepSeek v4.1 flash, but when I put 60 bucks into my account, it was gone in a few days of non-exclusive use. I'm actually curious what the difference is. I used it through pi and opencode, but the harness seemed to have no obvious impact on usage.

This is my experience, too. It's a great model, but it burns tokens if you use it heavily for work on complex domains.

Edit: others have noted the provider and harness matters. My experience is with opencode.

How have you spent hundreds of dollars? I’ve only spent 11 and I’ve been using it for four months!

How on earth you can do 100 dollars in 2-3 days with DeepSeek? I have 7 agents in omp running 24/7 every day. I use maybe 10-15 dollars a day. A rarely see a session going over 2 dollars. My maximum is maybe 3.5 dollars and that session took three days.

What harness you are using?

same, used a wrapper around cc and i was spending up to $30 a day with basic stuff

What bothers me about this whole AI tokenomics situation is the lack of transparency. OpenAI and Anthropic have to perhaps be the most opaque companies in existence wrt their offerings. There's like a thousand variables that they can change on the backend at the push of a button which can wildly swing API spends within the same model (partly also due to the non-deterministic nature of LxMs, but still), and there's no objective way to measure them other than vibes.

When the regulations do arrive, I think they should really focus on AI companies and API providers being more transparent wrt how they're billing their customers. Because right now, it's a totally vibes-dependent and a mess.

> Subagents are like trading derivatives. You can lose as much as you want.

Excellent pithy warning.

Sadly this is true - for individual folks on the lower end of the spend spectrum.

But there’s a point on that spectrum where the ability to run multiple experiments in parallel, even with a significant amount of (one time) wastage, is overall more cost effective than the alternative.

Afaik there is just pay-as-use with Deepseek

Why use subagents at all

> Deepseek 4 Pro

There's your problem, 4.1 Flash is significantly better and cheaper, to the point where the official DeepSeek API is going to (or already has, I forget) redirect requests for Pro to 4.1 Flash, and adjust billing accordingly too.

4 Pro is still offered by providers I'm sure, since it's open weight, so I can understand making that mistake.

That's an unfortunate experience. Think of v4.1 flash as actually v5.0 flash. It's night and day compared to the 4.0 flash (and 4.0 flash was unintuitively better than 4.0 pro). I would re-evaluate with v4.1 flash. I'm not saying it better than Sol or anything, but it's in the ballpark.

You mean 4.1 Flash which is the first great Deepseek? The one that actually surpasses Opus in my books now.

This was my experience 3 months ago. I had an Android app that interacted with a Bluetooth device that I wanted to reverse engineer and build my own Linux app for it. DeepSeek was struggling really hard. Claude did it end to end after 3 or 4 prompts. To be fair, I was using a web interface for DeepSeek and the CLI for Claude; maybe that makes a large difference.

build this prototype from end-to-end, is this how people build serious software with AI?

Oh buddy you have no idea what a good plan and agent harness can do with deepseek…

I am doing mostly hardware drivers recently, it works fine for complex work.

"build this prototype from end-to-end" works fine with DeekSeek V4.1 Flash, the problem occurs if you're not only building a prototype but want a finished product.

47 is my crossover for serious things (e.g. Grok 4.7 is below the line and GPT 6 Sol is above the line). I mean, Opus 5.5 is way better, but GPT 6 Sol still gets the job done for anything that doesn't require design thinking.

Although I do think Luna 6 max is ok for some basic things, would never use it for coding myself.

Had the same experience. I got rid of my pro sub of OpenAI. I’m really freaking impressed.

The premium price is only worth fo the hardest problems.

For CRUD shoveling, models like DS4.1 are enough.

And the intelligence gap between cheap and premium is closing, as can be seen from the title of this post.

In the Artificial Analysis index, MiMo 2.6 Pro is smarter than GPT-Sol 6.1 Low at the same cost, and only slightly dumber than Medium. MiMo 2.6 Flash is marginally cheaper and smarter than GPT-Luna 6 Max. (There is no GPT 6+ Terra, which would otherwise be in that range.) These are not negligible or trivial results.

If both DS4.1 and Opus can complete the tasks you throw at it at good enough quality the differences are negligible.

Who cares if your car can go 200mph if all you need is 60. If my requirement is 60mph, I want a faster 0-60, not a higher top speed.

I put 5 dollars at deepseek a long time ago, and somehow it has never been fully spent, can’t imagine anyway to spend 200$ on that thing

Recently, drivers for a bunch of obscure hardware. Lots of c\c++, that i am ok with but not enough to make hardware drivers (i am just impatient). Just using pi agent with a few plugins.

> I've spent $200+ on deepseek and this is for making a multiplayer FPS game.

Why do you expect that $200 will give you that on ANY model? Multiplayer FPS games are very difficult to make, no AI will deliver that today.

I use Claude Code + eternal terminal + tailscale + tmux + some custom skills to get notifications through nfty.sh.

I get the same UX on every platform, works perfectly on very low bandwith environments such as in a cabin, in the subway or in the middle of nowhere.

I tried using other harness such as Pi and opencode but I did not like them. If Claude Code gets weird I can swap in an instant.

You just need to follow this guide and disable artifacts in Claude Code's config: https://api-docs.deepseek.com/quick_start/agent_integrations...

https://omp.sh/ has amazing defaults and it sips tokens. Works really well with DeepSeek V4.1 Flash.

Use the model through a fast and reliable provider such as Fireworks directly, skip OpenRouter.

I have a server living in my home office, always on. I have a tmux session on it with vanilla Codex and Claude Code CLI, I can via my Ubiquiti network stack wiregaurd in to this box anywhere on the globe with just my laptop. Works super well for me. I also have some cheap shelley power plugs that I can use to cycle my PC’s power state if needed.

OpenCode works nicely for me. You can connect it to the DeepSeek platform with an API key.

I use pi.dev, it is pretty minimal, but you can extend it however you want since agent has access to it's own documentation.

I use crush (https://github.com/charmbracelet/crush) with the following patches:

  curl https://tg.st/u/0001-fix-unblock-all-commands-in-bash-tool.patch | git am
  curl https://tg.st/u/0002-feat-add-light-theme-with-auto-detection-for-white-b.patch | git am
  curl https://tg.st/u/0003-feat-enable-yolo-mode-by-default.patch | git am
  curl https://tg.st/u/0004-fix-disable-mouse-grabbing-to-restore-native-termina.patch | git am
  curl https://tg.st/u/0005-feat-skip-project-init-prompt-and-quit-immediately-o.patch | git am
  curl https://tg.st/u/0006-feat-remove-scrambled-rune-animation-from-waiting-sp.patch | git am
  curl https://tg.st/u/0007-feat-remove-quit-banner-and-thank-you-message.patch | git am
  curl https://tg.st/u/0008-feat-show-output-in-full-instead-of-collapsing-trunc.patch | git am
  curl https://tg.st/u/0009-fix-discover-map-model-features-advertised-by-v1-mod.patch | git am
  curl https://tg.st/u/0010-feat-keep-large-and-small-model-selections-in-sync.patch | git am

I don't understand any of this naming man. It just gets more confusing.

Terra is the "missing middle" model and had no positive brand recognition. Sol was for intelligence, Luna was for efficiency. Luna max was cheaper and smarter than terra light and sol light was better than terra max.

Because they asked the model what it wanted to be called?

I mean, when I upgraded my pipeline from terra to sol saying "it's the same price basically!" I was excited. Probably would not have felt as excited if it was just a version bump.

Not sure that's why they did it. But that was my experience.

If you run out of sol medium with $100 you're doing something wrong. Astra destroys your usage, I get 1 day of usage with Astra, but 6 sol is almost unlimited and I only use xhigh.

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.

Your tool calls (MCPs?) are very likely too wasteful. Apply some filtering logic on the offending tool’s output. Either a wrapper CLI, or just tell codex how to filter.

you can actually leverage 400k and 1M contexts in codex with very little code changes to the harness. note that excess context past the.. 250k or 400k mark (i don't remember) is charged at 2x the price.

You have a lot of control over compaction, both directly by changing compaction settings, and indirectly by how you structure your codebase/docs so agents use less tokens.

Try Gemini. It’s so cheap I often use my personal AI Pro account for corporate work, and most of the time it doesn’t matter.

you can config codex to compact at a higher context limit

As a reference i burn 1% percent for every 40 minutes of sol on average

And half as good. I didn't have great experiences with Anthropic models in the past, but Opus 5.5 seems to have turned a major corner. It is churning through tasks significantly more quickly and efficiently.

Suggest trying it out yourself: Ask for something difficult from GPT-6 Sol and Opus 5.5 and watch what each one does. The difference is stark.

Edit: Defining "difficult" as a complex coding or systems task (or even series of them in a single prompt).

Based on my benchmark[1] it is the same price as Opus 5.5 and just as capable.

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

The backdrop being deepseek offering 1% (I remember it was ~1% when 4-pro first came out early this year - 4-pro is now removed) / 2% (current for 4.1-flash).

Made the opposite experience. Astra was not good in writing go and c++ code. Had multiple OpenAi and Claude subscriptions and all our coworkers agreed. Switched back to Claude and the experience is so much better. Not vibe coding, but assisted coding with immediate feedback.

Same here. Astra has been the best thing I've seen. Astra on Low has been my favourite thing so far. Higher levels just mean more cruft, not useful.

They never nerfed any model after release.

The lackluster GPT-6 Sol has been superseded by this apparently much better 6.1 Sol within a week.

I am very skeptical of claims that old models weren't much worse. Compare this to February's GPT-5.3.

How large of codebases are you working on? The models have gotten good enough to 1 shot stupid "trivial" throwaway integration projects with 0 handholding (was having RL'd garbage in late 2025), and I'm actually enjoying designing bounded greenfield personal software from scratch with Astra, in my experience. It's quite slow - 2 weeks of credits and constant talking and back and forth with Astra, but it doesn't feel annoying to talk to and is like an intelligent colleague maybe 70% of the time? Which is great. Just push back when it's dumb.

I'm by no means an AI booster, but given 2022 - 2026 progress I'd say it's "exponential" in the sense of, "holy shit, every year I can do more and more genuinely different things", not "RSI mind reading intelligence can do anything is here".

I don't think Navier-Stokes level intelligence translates over to my projects, unfortunately. Yet? Who knows.

> I haven’t seen actual capability growth since ~January, and I’m pretty sure that was all tooling/harness improvements.

Even if that were the case, I'd say that it's improved in practice. And just from a philosophy perspective, if you're trying to imply some kind of mind dualistic way of viewing things, uh, I disagree with those theories of intelligence strongly (which also incidentally also disagrees with AIT-style theories of intelligence on one axis, though I have many bones to pick with the culture there).

In my experience, no. There’s no way to know though. The whole conversation and industry are a combo of benchmaxing, faith, and mysticism.

Since like last December I haven’t had any issues getting work done with whatever the latest Anthropic or OpenAI models at the time were. Tooling and models have only gotten better since then.

Opus 5.5 is so good that I don't want it to be replaced anytime soon. Stop training models, Anthropic, and just serve this thing without regressions for a year or three, can you?

Sol 6 definitely feels kind of dumb and worse than 5.6

Astra seems better though.

Showing one potentially saturated benchmark doesn't necessarily fill me with a lot of confidence in the coding results.

When GPT 6 Sol & Luna were released, everything went down. I have been running Sol at max thinking and it is about the same as old Luna with max thinking, give or take. Sometimes feeling even dumber. I can't trust it to do anything big alone anymore without babysitting.

On r/codex the sentiment seems to be quite wide-spread.

Some version of this claim has been made for the past 4 years. There's a data cliff, there's no more compute to buy, the financials don't make sense and all of these orgs will be out of business by end of quarter.

Not once has any of these predictions come true, the pace of progress has continued on it's exponential trajectory since ChatGPT first came to the public's attention.

So why now? What is special about today that suggests all of this is coming to a screeching halt despite all evidence to the contrary?

It's not so much that they're hitting a plateau in capability, as we're saturating long horizon benchmarks and it's not greatly improving general usability. On the other hand, newer models have been amazing for people interested in 3d, graphics, video editing, etc. The difference between Opus 5.5/Astra and earlier models is night and day even if for many coding tasks they're not a revolution.

Is there anything that could happen that you wouldn't use as evidence that they are hitting a plateau?

It just seems like these claims are constant and looking back the calls of 'plateau' between 2023 and 2025 were clearly false, why should we think it's different now?

Nvidia can start putting weights in silicon if model development slows down.

I think they are hitting compute restrictions. And buying compute right now can be 3-4X. And the costs are increasing. If they train a larger model and demand is high, that’s a lot of compute for Codex subscriptions, which is a loss leader for them. Especially Pro 20X which they just nerfed to 10X.

>Another piece of evidence on the pile that the sudden panic and desire to "slow down" is because they're hitting the plateau on capability

if true then LLM related AI (post-post AI winter AI?) is probably one of the fastest inception-to-plateau tech sectors to have ever existed.

We're still improving transistors on a somewhat routine basis.

>Another piece of evidence on the pile that the sudden panic and desire to "slow down" is because they're hitting the plateau on capability

I think it's more a token-cost-demand plateau. They've reached the scale and investor trillions to which they can't 10x the hardware cost of inference any more. They can't afford to compete by eating costs and there isn't appetite for more expensive inference.

So in order that they don't bankrupt each other they're looking for the legal cartel behavior coordinating a stop to growth by convincing governments to regulate them into stopping.

There's a lot of juice to squeeze in efficiency but only so much whereas it seemed like capability was going to continue to scale with parameter count.

Maybe it's good news for everyone that model capability is now going to scale on semiconductor cost meaning huge players are going to be very motivated to make semiconductors cheap.

What universe do you live in that you can look at the past six months and see anything like a plateau in capability?

Edit: removed a comment that was uncharitable and rude, for which I apologize.

> sudden panic and desire to "slow down" is because they're hitting the plateau on capability

I don't think that's the motivation, it's because both companies want to IPO and the _only_ way to even hope to be profitable is to do a whole lot less training, which costs a fortune. But unless Chinese labs go along with this gentleman's agreement (they won't), slowing down on training will bring about the inevitable Chinese model parity date more rapidly. At which point the game is well and truly over for OpenAI and Anthropic. Bit of a pickle they've gotten themselves into with the emphasis on being best, with premium prices to match.

> Another piece of evidence on the pile that the sudden panic and desire to "slow down" is because they're hitting the plateau on capability

People were talking about plateau for years already.

I guess I'm out of touch. What did china do to german cars?

We can only hope.

Why make a new account just to post this comment?

It's not even anything controversial..

Yup.

I see posts about OpenAI and Anthropic latest and don’t even care looking at what they do better. I just read the comments here.

I use DS4.1 Flash and GLM 5.3 Flash, pay peanuts per day and get more than acceptable results.

There is already tooling to automatically pick models within an organization. Eventually it could be as easy as flipping a switch in group policy that forces everyone to switch to the cheaper models.

Insane pricing pressure on the horizon. Even if big companies will not go with open weight models, the threat will be ever present that they can instantly flip flop on providers.

Not an AWS customer, I take it? :-)

That's relative to where you live.

Consumers are now saying the new pricing with lower usage caps is not so great. https://news.ycombinator.com/item?id=49896975

That makes sense. There's not really much else you can say about it.

I always notice this too. Getting it right seems (psychologically for me anyway) to be a big part of "a good pelican" whenever I look at these. But doesn't always seem to correlate with increasing intelligence of models (measured via benchmarks, experience with the model etc.).

It's not frontier pelican without the back leg behind the bike frame IMO.

Sorry about that, markdown bug, now fixed.

Let's be honest, they're all guessing when it comes to rendering order

This is it.

It's because they need subscription money and interaction data and so keeping a version bump in the wings to stop the bleeding from your competitor's version bump is the logical thing to do. It has nothing to do with RSI.

Maybe process maturity too.

Like think about a software org with good CI/CD versus one without. The mature org can do consistent incremental releases because each one is safe and low overhead, the messier org will do fewer big releases because each release requires a big effort on its own.

As model developers mature we might expect to see more frequent point releases rather than the big bang evolutions.

Probably one of the factors. Signed up to openai pro a few days ago, deciding between openai and anthropic, then sonnet 5.5 was released and am wondering whether I made a mistake.

Luckily it's not a mistake as now we have access to . . . dots.

(and sol 6.1, it seems)

jokes on me, I pay for all the subscriptions.

It feels like an updated 4.6. It's fantastic.

> I'm not the only one

See, that's an/the issue. As soon as people start to flee to the improved model, they start to serve degraded models to keep up with the demand.

Which paper are you referring to?

What's that in summary?

and seems like they're claiming Sol/Opus are not frontier (and only Astra/Fable are)

The old "the bigger number is better", GPT announces model 6.1, the obvious thing to do next is to announce Gemini 27, and after that Claudé 3000, then a flute album.

If you look closely at various benchmarks, you'll see that often models will improve in certain areas while regressing in others. It suggests we're already at the point of diminishing returns.

I can't recommend Chinese models enough. My personal favorite is DeepSeek v4.1 Flash but I have tried Qwen 3.8, Kimi 3 and GLM 5.3 which are equally impressive but DeepSeek is the cheapest and fastest regularly hitting 270 token per second.

And yeah I have worked with Anthropic and OpenAI models, they're good but they cost a fortune while Chinese models are already really good at a fraction of the cost.

I keep hearing about these Chinese models, but what exactly are you doing with the models and coding? I have a need to fully write code with full tool calling capabilities. Not just methods or functions. I want to be able to prompt a feature and it makes the JIRA ticket, and fully implements it and makes a PR. I don't want to babysit it or even read the code. Once it creates the PR, I want it to monitor it for any comments fro Copilot/security review and then fix it as necessary.

Is that what the Chinese models are capable of? If so, how are you using them? API? Or is there an inference provider that is as fast as the big 2? What about the coding harness?

Alas, I did enjoy burning investor money on my taxis, movies and tokens.

> Our VC-backed subscription days are numbered

Well, the time it takes to compress frontier intelligence down to DeepSeek V4.1 Flash costs (basically too cheap to meter) is dropping, and the differential between the two is also dropping...

So... who cares?

I'm ok with whatever price they give out given they are not a monopoly and have competition, the lock in is minimum for me. This means they have legit reasons to send us this price plan. I don't believe they would shoot themselves in the foot when there is cut throat competition (Claude/opensource) out there.

Lastly, I'd like to actually use it in the real world to see how far my plan goes or if its unusable.

how could u even ban them? lol

Ultrafast uses 6x the usage. They probably realize that people will complain if the plan limits are too low. In any case, the TCO of the newer chips is supposedly lower. Hopefully everyone is on ultrafast eventually.

Yeah, that's not going to happen. They are more likely to lose a lot of customers, unless Anthropic does the same thing.

But $200 is likely the ceiling of what people will pay for a subscription with usage based on vibes.

Very risky to do so especially considering how well is opus 5.5.

I am skeptical that individuals on the $200 and $500 plans make up that meaningful of a portion of revenue.

The 200$ plan was appealing because you got 4x usage for 2x the price.

Now, as it's linear, it makes much more sense to downgrade to 100$ OAI and pick up a 100$ Claude sub. (without doing the numbers) the usage should remain the same, total paid the same, but having access to best of both worlds. It should be a win for the user, and a loss for OAI.

With this in mind, it sounds like a fumble by OAI.

Have you looked at the prices of GPUs lately?

Well, here is a breaking-news for you: the 20x from Claude is not a 20x on the weekly usage, it's a 20x on the 5h usage, while the weekly usage is simply double the $100 plan...

Basically OpenAI aligned with Anthropic on the weekly usage with the caveat that OpenAI doesn't have a 5h limit.

> According to the company, existing subscribers will keep their current limits for a time, and will later receive a one-time credit to help them make the most of their new reduced allowances

Might want to hold off on canceling and continue to bleed them dry until the nerf hits

It really does look like OpenAI is trying to gradually get rid of their subscription plans. Every week there is noticeably less usage available to them while each new model release boasts substantially cheaper API token pricing. If this continues then the two pricing models will eventually be at parity.

Interesting! Can you share an example?

You need to use the Blender MCP. There is an official plugin for this now, so the third party one can be avoided.

I've only dabbled but yes with SOTA models it is very good at animating and really most Blender tasks you can think of. Certainly if you are coming at Blender at below expert level it makes it far more accessible and fun to work with.

There are still rough edges of course. But try the official MCP out with Astra and judge for yourself.

I've only tried animating models in Astra-6, and I was quite impressed! It's rarely able to one-shot things perfectly, but it usually gets pretty close.

No, because I always hit my Fable quota (Max 20x) in 12 hours on simpler tasks, and I'd hate to need to buy tokens at API pricing.

Astra 6.1 light, not the full-fledged version.

Only for the $100 subscription, correct?

Sol 6 was a flop. Nobody would have cared if it was called Terra 6.

People said Astra was a gut punch and that Anthropic was reeling. (Opus 5 was almost universally panned)

The best thing is that we benefit from these constant back and forth gut punches :)

It is at least 3x cheaper than Astra in the 20x subscription.

So yes, it is clearly cheap in comparison.

So their original plan was to axe Terra, but then introduce an "Astra Light" model a week later? They had a nice lineup named for a whole 3 months, and they're already messing with it.

Wait, so is coding not solved?

Wholeheartedly agree. Astra was some improvement over 5.6-sol in the sense that I'd "argue less" with it, but still frustrating and still sloppy. I'm starting to feel people are not honest about their experiences, they do very simple things or have very low standards. The biggest improvement i've seen from Astra so far is speed.

My experience with agentic coding on projects I care about (because my responsibility in my firm is to care about these things, at least for now) has not changed a lot in the past few months, and I have kept up with every single model update / experimented with harness a great deal.

8x for subscription, 6x for credits/enterprise: https://learn.chatgpt.com/docs/agent-configuration/speed

6x

i'm watching the keynote

Sol 6 is in there? You may be on Enterprise where it didn't roll out by default and comes out in a week or so. (Which is a weird and bad change to their model releases.)

6 Sol was worse than 5.6 Sol from my own experiences. Far worse.

Will see if this remedies things.

"no homerS -- we're allowed to have one"

https://amphetamem.es/meme?id=the-simpsons_06_12_71&text=We%...

well i could certainly be in the wrong; i'm just speaking from my personal and likely flawed experience but i feel like i've noticed silly mistakes in every (llm) model that has been released (and that i've sufficiently used) and it hasn't felt like 6 Sol was much of a regression from 6 Astra (more than reported in both model cards), both of which ive very extensively.

not saying this is the case here but it does feel a bit like wine tasting sometimes, everyone claims to be an expert that can taste a few tokens and tell you exactly what region and vineyard its from.

Yes I do. I've got a spare desktop that isn't too efficient (probably ~100W idle but annoyingly I've lost my power meter) so I don't leave it on even though I would like to use it as a server.

Laptops use very minimal power - you don't need to worry about them. If they didn't their battery life would suck.

Likely orders of magnitude different, this is a weak whataboutism.

Because people find video games fun, though I suppose there's some vocal people that think of them as bad for society. In contrast the AI companies are promising a torment nexus future.

I'd be curious as to how much of internet infrastructure is dedicated to gaming though.

Considering Nvidia's hard shift to crypto and now AI, I doubt videogames are even in the same ballpark.

How many DCs are devoted solely to gaming?

If you recall history past the last 5 minutes, you will remember that people have indeed been enraged with the environmental costs of things for a long time. Its just that AI seems to have induced a mass amnesia, and people tend to forget about what happened pre 2024.

I don't think video games consume nearly as much power. A PS5's power consumption is apparently around 200W. That's not enough to run even one GPU, let alone the armada it presumably takes to run Astra.

Even then people do care about the power consumption of non-AI things. Look at the energy label on your TV or tumble drier for example.

The misstep was naming it Sol - it was Terra-level all along.

Bro, I'm a visual thinker

No because then I'll go to the competition.

Because it is more work?

It's just vibe versioning, right? Fable 5 is a beloved product, it gets a .1 bump to feel close. Opus 5 and Sonnet 5 had a mixed reception, they get a .5 bump to create a sense of distance.

After what DeepSeek pulled with V4.1 Flash I've given up on trying to map LLM versions to semver.

Is this due to a similar safety concern or just because it's not ready yet for one (or more) of a myriad of possible reasons?

The coverage around 6.1 Astra seems deliberately playing into the dubious, recently headline "safety" narrative in a way that feels distinct. But you may be correct in which case, I would take the correction on board and maybe suggest a different alternative.

Although in theory if OpenAI was boycotted in this way the market pressure would force them to release. Then everyone moves back over there. Then Claude faces the same pressure. So even so, I think it could still work even if you have to trade off who you are boycotting from time to time.

Without more details on the credibility of the "safety" concern this seems like a totally coherent action for customers to take. We shouldn't put up with teasing.