Listen - that's the sound of millions of companies and users doubling down on Chinese models.
It might be a national security problem for other nations to have access to these models. But it's equally now a national security problem for any other nation to depend on them. Or US tech in general.
As it happens, the current number-two article on HN is about a similar consequence of Chinese export controls--a car manufacturer developing electric motors that do not use rare earths:
The incentives around OSS become stronger the further down in the list of market leaders a company is. The #1 company has no particular incentive to push open software apart from a belief that the market is going to be come commoditised anyway. But the 2nd or 3rd largest player has actual incentives to break the market up and remove software quality as a consideration. No #10 may as well not bother with a proprietary option since if they make it a software quality battle they're going to lose each customer 9 times anyway.
Just because the Chinese are running export controls in one market doesn't mean that they're going to close of access to AI. They might, but each market should be considered in isolation.
And it is nearly always hubris - the people making these decisions are surrounded by yes-men who built their whole career pumping up the egos of their superiors.
A sample of one, but I was getting more stuff done despite Fable uses tokens twice as fast as Opus, because it understood the goals so well and worked to achieve them.
Can you give an example of what those "toughest problems/great code" are? I don't need to know the prompt nor the output, but the general idea, what it is about.
Some very tough computational geometry problems I couldn't solve on my own, nor with the assistance of other AIs or my colleagues. Fable did them all first go. The most impressive built a custom optimizer with a ludicrous number of adaptive switches that absolutely crunched through an error surface with a bunch of nontrivial nullspaces and some wild curvature. That optimizer is of independent interest; it's not totally novel in theory, but the implementation is an impressive piece of engineering.
Was it a better prompt? Have you tried giving the same prompt to other models?
I have found out that the mistakes of other models (which I choose first to save money) help me refine the prompt more and more, until I am fed up and pick Opus 4.8 (for example) which magically seems to get it right, but there is a lot of pre-work there...
Yes I have tried giving these same prompts to other models. The difference has been painfully clear. Switching back to Opus, it is completely unable to do anything that I had asked of Fable without significant conceptual and engineering errors. Functioning code, sure, but not even remotely capable of accomplishing the task to the accuracy I need. Sonnet, GPT 5.5, Gemini, DeepSeek, it's all the same deal. I accepted this in the past because that was just how it was. Now it's tremendously irritating.
I wish Fable really was only a minor upgrade so that it wouldn't be missed, but this feels like the difference between having a post-doctoral colleague and educating a student that I have to constantly guide and correct. It's so profound for me that some of the reactions in this thread feel like they come from another reality entirely. Or maybe they just got instantly diverted to Opus, who knows.
Given the same usage limits, I was able to get more stuff done and not even hit the usage limits, because I wasn't working on constantly fixing what Opus was trying to do, Fable just understands the task correctly and works great with the given context.
Same here, not n=3, plus the above 3 reporting, so n=6 and rising
Fable was definitely better for a variety of tasks, even accounting for using 2X the token rate, like the way it used the tokens faster reduced the wasted tokens, as least for the subset of those who already knew at least some optimizations...?
Yep. I love open source but there isn’t a model that comes close still to the closed source options like Opus 4.8 and that’s obvious from most people I see across the software industry as well. There are at least another few models after Opus from OpenAI and Anthropic most would go down the list using before any of the Chinese models at this point.
Opus 4.8 has taken such a beating over the last couple of days since the release of fable, videos online of people referring to it like the “redheaded stepchild” (is there a better way of saying this, this sounds racist) basically at this point, everyone is going to be seriously disappointed to fall back to that.
Yeah, not sure where the phrase originated but it does sound bad when you put some thought into it. My sister is a redhead and people loved to make fun of her growing up, telling her there's no way two parents with brown hair could have a kid with red hair, so the mailman (who also had red hair) was obviously her dad.
MiniMax M3 is surprisingly powerful, and open weight (or is about to be). There's others in this space too: MiMo v2.5, GLM 5.1. There's quite a few to pick from if you want strong models running on "your" hardware.
For starters, there's a C++ application written with MFC and an absolute ton of inline assembly and threading (yes, in a 1990's C++ application). I'm porting it to MacOS/Linux currently.
Opus 4.6+ is able to make slow progress, but it takes several revisions per workstream. It requires constant supervision as it often creates convoluted solutions that expand the code in bloated ways. It works, but still requires my constant input.
Fable was able to almost one shot most of the big migrations with very few bugs, and was able to fix those bugs with 1 review pass. I almost didn't believe it. I was able to put it on a task (with dangerous permissions) and come back hours later to see it done, working, and clean.
I tried DeepSeek v4 and it wasn't able to make any meaningful progress at all. It kept creating dangling pointers and had trouble understanding the inline assempbly needed to be replaced if we were to compile for 64 bit. It kept getting stuck and looping on the same problem, without making progress.
What I do use DeepSeek for is lots of my automations on my websites. I find DeepSeek is fantastically cheap and fast and effective as summarization, collation, generating reports, finding and reporting issues from logs, etc. But I haven't found a way to get it to effectively port 90's C++ code to modern, cross-platform standards. But I want to be clear- I really like DeepSeek and use it wherever I can.. I mean.. it's so affordable!
I was building a cli tool that showed a graph of git commits, kind of like git log --graph, and deepseek v4 simply could not figure out a specific ui quirk where things weren't lining up correctly. I spent like $0.10 and 30 minutes trying to figure it out on deepseek.
Then I had deepseek summarize the bug, gave it to Opus, and it solved it in $1.12 and five minutes.
Fun fact, I was trying this afternoon Deepseek vs Opus 4.8 high, and I was surprised at how good Deepseek was. It outperformed Opus 4.8 on multiple occasions.
Found just later I was using v4 flash and not pro (for mistakenly setting the model to deepseek-chat and not v4-pro).
There are aspects about Deepseek I don't like though, when pushed against it will eagerly bend instead of reasoning and advocating for his points, something Opus 4.7 and later models started doing a lot (even when wrong).
Which models? Im curious what kind of more specific hypothesis you're willing to put forth. Anthropic going to lose 20-30-40-50% of users to Deepseek? What?
I quit paying for Claude Code to buy z.ai's coding plan for use with OpenCode. I'm not a power user, but I don't regret switching away from Claude. OpenCode is generally nicer for my work.
Why z.ai and not an ollama pro plan that can use all the open models? Real question, not snark. I've only ever done ollama and wonder what I'm missing.
Because I bought a year's subscription in December, when it was still $6/mo :P
I have decently capable hardware, but stuff like Qwen 3.6 and Gemma 4 still doesn't compare to agentic editing with a frontier model. Right now, OpenCode's $10/mo "Go" plan is what I'd be looking to try once my year expires.
As a non-US person, I will use whatever is the best and reasonably priced. I could not give one iota about who makes or hosts these models. The origin or political leanings of these models mean nothing in my usage calculus.
Chinese models are next, the whole reason this is happening is because they don't want China to steal their tech. It is no secret anymore that they have been distilling US models. That's why it is explicitly aimed at foreign nationals.
TikTok wasn’t open source and able to be run on your own hardware. Banning Alibaba’s models (or even a personal fork of them) running on your machines seems hard to defend in court.
The two main bills I'm aware of are the Decoupling America's AI Capabilities from China Act and No Adversarial AI Act. The former would have made it illegal for any American citizen to simply use DeepSeek. I couldn't find any lobbying data, but the obvious effect is that Americans would be forced to pay for more expensive domestic alternatives.
A House committee also recently probed Cursor and Airbnb for using Chinese models, rather than more expensive American alternatives. A sexagenarian Congressman gave a nonsense quote that he certainly did not come up with himself,[1] which sounds very similar to language Anthropic uses in its marketing materials.[2][3]
Moolenaar's quote: "The AI models these companies use are trained by China’s censorship regime and introduce hidden vulnerabilities that put Americans’ data and businesses at risk." That is, Americans using Chinese-trained AI models are exposed to some form of cybersecurity risk.
That's not really a threat model described in either of the Anthropic posts you share, which mainly talk about the risks of allowing authoritarian regimes to use powerful US-trained models, and the geopolitical risks of authoritarian countries developing strong AI before democratic/liberal countries do.
They'll have to remove sections like this from their AI Action Plan
> We need to ensure America has leading open models founded on American values. Open-
source and open-weight models could become global standards in some areas of business and
in academic research worldwide. For that reason, they also have geostrategic value. While the
decision of whether and how to release an open or closed model is fundamentally up to the
developer, the Federal government should create a supportive environment for open models.
US will ban American companies from using Chinese models and also ban them from dealing with companies who use Chinese models. “Code produced by Chinese models may be deliberately introduce backdoors and vulnerabilities” that kind of thing.
To do what? I mean they’re good models, but frankly, they fucking suck (relatively speaking). I’m not looking to going back to a week of back-and-forth with the LLM once I’ve gotten used to all this one shotting.
works really well with pi for small to medium sized coding tasks for me - C++ is an interesting case since it's probably more challenging just due to the complexity of the syntax. But it works great with Groovy which is another slightly off-mainstream language (these days).
I use DSv4 through opencode. I use it from deepseek directly, not through a third-party platform.
I mostly do C# and some frontend. I was starting to feel really depressed and unengaged at work because I was starting to use AI far too much like a magic slot machine. I'm now making a conscious effort to go back to using it as a tool used a bit more deliberately.
I'm not even using the pro model. The flash version is fast so I can keep it interactive rather than context switching to reddit while the model is working, and it turns out using my brain means I don't really need the model to be that smart.
It might be a national security problem for other nations to have access to these models. But it's equally now a national security problem for any other nation to depend on them. Or US tech in general.