6 ms·

This is their hosted-only model, not an open weight model like they’ve become known for. They got a lot of good publicity for their open weight model releases,

This is their hosted-only model, not an open weight model like they’ve become known for. They got a lot of good publicity for their open weight model releases, which was the goal. The hard part is pivoting from an open weight provider to being considered as a competitor to Claude and ChatGPT. Initial reactions are mostly anger from everyone who didn’t realize that the play along was to give away the smaller models as advertising, not because they were feeling generous. Comparing to Opus 4.5 instead of the current 4.6 and other last-gen models is clearly an attempt to deceive, which isn’t winning them any points either. I think there is a moderately large market for models like this that aren’t quite SOTA level but can be served up much cheaper. I don’t know how successful they’ll be in the race to the bottom in this market niche, though. Most users of cheap API tokens are not loyal to any brand and will change providers overnight each time someone releases a slightly better model.

cubefox 7mo ago
> I think there is a moderately large market for models like this that aren’t quite SOTA level but can be served up much cheaper. There isn't, pretty much everyone wants the best of the best.
- scoopdewoop 7mo ago
  That isn't true. In a Codex or Claude Code instance, sure... but those are not the main users of APIs. If you are using LLMs in a service for customers, costs matter.
- Aurornis 7mo ago
  The market for API tokens is bigger than people like you and I (who also want the best) using then for code. There are a lot of data science problems that benefit from running the dataset through an LLM, which becomes bottlenecked on per-token costs. For these you take a sample subset and run it against multiple providers and then do a cost versus accuracy tradeoff. The market for API tokens is not just people using OpenCode and similar tools.
- sidrag22 7mo ago
  maybe there isnt, but as understanding grows people will understand that having an orchestration agent delegate simple work to lesser agents is significant not only for cost savings, but also for preserving context window space.
- Someone1234 7mo ago
  > There isn't, pretty much everyone wants the best of the best. For direct user interaction or coding problems, perhaps. But as API calls get cheaper, it becomes more realistic to use them for completely automated workflows against data-sets, or as sub-agents called from expensive SOTA models. For example, in Claude, using Opus as an orchestrator to call Sonnet sub-agents, is a popular usage "hack." That only gets more powerful, as the Sonnet equivalent model gets cheaper. Now you can spawn entire teams of small specialized sub-agents with small context windows but limited scope.
  - thinkcontext 7mo ago
    > But as API calls get cheaper, it becomes more realistic to use them for completely automated workflows against data-sets Seems like a huge waste of money and electricity for processes that can be implemented as a traditional deterministic program. One would hope that tools would identify recurrent jobs that can be turned into simple scripts.
    - Someone1234 7mo ago
      It depends on the specific task. For example: "Here our dataset that contains customer feedback comment fields; look through them, draw out themes, associations, and look for trends." Solving that with a deterministic program isn't a trivial problem, and it is likely cheaper solved via LLM.
      - cubefox 7mo ago
        It makes sense if the dataset is so large that LLM cost is a prohibitive factor. Otherwise a frontier LLM has the advantage of producing a better result.
  - alexsmirnov 7mo ago
    Exactly. I did create my own MCP with custom agents that combine several tools into a single one. For example, all WebSearch, WebFetch, Context7 exposed as a single "web research" tool, backed by the cheapest model that passes evaluation. The same for a codebase research Use it with both Claude and Opencode saves a lot of time and tokens.
- regularfry 7mo ago
  Everyone may want the best, but the amount of AI-addressable work outstrips the budget available for buying the best by quite a wide margin.
- joefourier 7mo ago
  Ever hit your daily limit on Claude Code and saw how expensive it is to pay per token?
  - girvo 7mo ago
    All the time now… it’s wild how little usage you get with Opus on the Pro sub now haha
- PhilippGille 7mo ago
  The OpenRouter usage stats indicate the opposite: https://openrouter.ai/rankings?view=month https://openrouter.ai/rankings?view=month
  - jjice 7mo ago
    OpenRouter usage is likely skewed towards LLMs that are more niche and/or self-hostable by solid hardware that's available, but most consumers don't have on hand. I can imagine Anthropic and OpenAI LLMs often get called directly from their APIs instead. At least from my experience and friends of mine, we use OpenRouter for cases where we want to use smaller LLMs like Qwen, but when I've used ChatGPT and Claude, I use those APIs directly.
    - senordevnyc 7mo ago
      Same, and my little SaaS is pushing more than 0.1% of the TOTAL volume of tokens on OpenRouter, so the reality is they’re TINY.
      - imtringued 7mo ago
        0.1% of OpenRouter is around 400 billion tokens per month or around $400k per month at a cost of $1 per 1 million input tokens, not counting output. I think it's pretty disingenuous to call your SaaS little when it is projected to spend at least 5 million USD just on tokens and this is a low end estimate.
        senordevnyc 7mo ago
        Their homepage says 30T tokens monthly, so 0.1% would be 30 billion. And I pay way less than $1 per input token, especially when caching is taken into account. EDIT: they updated it in the last day or two, now it says 70T, so I’m a little below 0.1% now. But seriously, the point stands, 70T tokens a month just isn’t that much in the global scheme. The big labs are pushing quadrillions each.
- noman-land 7mo ago
  OpenCode allows for free inference tho.
- esafak 7mo ago
  That's only because current models don't saturate people's needs. Once they are fast and smart enough people will pick cheaper ones.
- wolttam 7mo ago
  Nope. I get very good results from GLM 5 and 5.1. I’m not working on anything so complex and groundbreaking that I need the best. Coding is a rung on the ladder of model capability. Frontier models will grow to take on more capabilities, while smaller more focused models start becoming the economical choice for coding
  - girvo 7mo ago
    GLM-5 is surprisingly good to be fair. Punches well above its weight IMO
- wongarsu 7mo ago
  For coding I want the best. Both I and $work do lots of things besides coding where smaller models like qwen3.5-27b work great, at much lower cost.
- thraxil 7mo ago
  No. Right now I'm upset that Google has removed (or at least is in the process of removing) the Gemini 2.0 flash model. We use it for some pretty basic functionality because it's cheap and fast and honestly good enough for what we use it for in that part of our app. We're being forced to "upgrade" to models that are at least 2.5 times as expensive, are slower and, while I'm sure they're better for complex tasks, don't do measurably better than 2.0 flash for what we need. Yay. We've stuck with the GCP/Gemini ecosystem up until now, but this is kind of forcing us to consider other LLM providers.
  - toofy 7mo ago
    this is one of the reasons im hearing more and more people are using open/locally hosted models. particularly so we dont have to waste time to entirely redo everything when inevitably a company decides to pull the rug out from under us and change or remove something integral to our flow, which over the years we've seen countless times, and seems to be getting more and more common. products entirely disappearing or significantly changing will be more and more common in the llm arena as things move forward towards companies shutting down, bubbles deflating, brand priorities drastically reshifting, etc... i think, we're at or at least close to a time to really put some thought into which pieces of your flow could be done entirely with an open/local model and be honest with ourselves on which pieces of our flow truly needs sota or closed models that may entirely disappear or change. in the long run, putting a little bit of thought into this now will save a lot of headache later.
    - jimbokun 7mo ago
      What’s interesting about this is that for previous technologies you could define a standard and demonstrate compliance with interfaces and behavior. But with LLMs, how do you know switching from one to another won’t change some behavior your system was implicitly relying on?
    - thraxil 7mo ago
      Yeah. Back when Gemma2 came out we benchmarked it and were looking at open models. For our use case though, while the tasks are pretty simple, we do need a pretty large context window and Gemini had a big lead there over the open models for quite a while. I'll probably be evaluating the current batch of open models in the near future though.
- wolvoleo 7mo ago
  Not really. It depends on the usecase. For private stuff I'm very happy to take what was SOTA a year or 2 ago if I can have it all running in my home and don't have to share any of my data with some sleazy big tech cloud. The price is a concern too of course. But privacy is a bigger one for me. I absolutely don't trust any of their promises not to use data for training purposes.
- freehorse 7mo ago
  Not all tasks require models like opus. If they do not, then it is more efficient to use cheaper and faster models. For most of my tasks now I use the big kimi/qwen/glm models because they are cheap and good enough, if not even the smaller locals ones. I would say that for a significant part of the current market open-source models are good enough to fill a part of it.
zozbot234 7mo ago
> not an open weight model like they’ve become known for. Right, they state that they'll release "smaller" variants openly at some point, with few details as to what that means. Will there be a ~300B variant as with Qwen 3.5? The blog post doesn't say.
- echelon 7mo ago
  I'm not interested in adopting an inferior closed source weight from a geopolitical rival. The open source weights argument was the one thing China had going and that I was seriously cheering them on for. They could have been our saviors and disrupted the US tech giants - and if it was open, I'd have welcomed it. Now they show their true colors. They want to train models on our engineering to replace us, while simultaneously giving nothing back? No thanks. I'd rather fund the shitty US hyperscalers. At least that leads to jobs here. If there's a company willing develop and foster large scale weights in the open, I'll adopt their tooling 100%. It doesn't matter if they're a year behind. Just do it open and build an entire ecosystem on top of it. The re-AOLization of the internet into thin clients is bullshit, and all it takes is one player to buck the rules to topple the whole house of cards.
  - zozbot234 7mo ago
    > I'm not interested in adopting an inferior closed weights model from a geopolitical rival. That's a very reasonable stance. It doesn't change the fact that we do have plenty of local models (up to and including Qwen 3.5) that are still quite useful.
  - cmrdporcupine 7mo ago
    Whereas I as a Canadian am absolutely eager to see a serious competitor from a rival to the US because sending money south to Anthropic and OpenAI who think it's ok to spy on (or worse) their non-American customers, and are headquartered in a country that is trying to crush my country's economy, interfere in our domestic politics, and put us out of work and making threats on political allies. I'd prefer them to be open weight, but I'd love to sub a decent competitive coding plan from a European or Chinese provider. Right now they're not quite there. If closing it and charging for it brings them closer to competitive, that's ok. If the US tech and AI industry long term wants customers and a broad market outside of their own domestic base, they need to reconsider who they are bending the knee to, and how they are defining their policies in relation to the Trump administration. Bring on the Chinese competition.
dev_l1x_be 7mo ago
How stupid somebody has to be to mix up Opus with Qwen?
- cieplok 7mo ago
  OP didn't say about confusing Opus with Qwen but rather people being confused about Qwen3.6-Plus not being available as an "open weight" model available for self hosting.
jstummbillig 7mo ago
> Initial reactions are mostly anger from everyone who didn’t realize that the play along was to give away the smaller models as advertising, not because they were feeling generous. The naivety around this has been staggering quite frankly. All of a sudden, people thinking that meta etc are releasing free models because they believe in open access and distribution of knowledge. No, they just suck comparatively. There is nothing to sell. Using it to recruit and generate attention is the best play for them.
- Gracana 7mo ago
  I don't think there's so much naivety. People can be aware of the the plan and still be frustrated and disappointed when it happens.
  - zozbot234 7mo ago
    I'm not frustrated or disappointed, we have lots of models from Qwen already. We haven't really lost anything. And plenty of players only release "smaller" models anyway, so it's hardly unprecedented.
  - Aurornis 7mo ago
    For a brief moment there were a lot of comments about how Chinese tech companies are our saviors in the age of AI because they were releasing their models. It was an edgy contrarian take that was getting a lot of traction, mostly from commenters who were unfamiliar with Alibaba and thought it was the anti-Big-tech
    - Gracana 7mo ago
      My explanation is simpler and does not rely on assuming that anyone is an idiot. Or an edgy contrarian.
  - GorbachevyChase 7mo ago
    I’m waiting for the grand reversal where Anthropic abuses the Qwen API to train the next Haiku.
true_religion 7mo ago
Opus was released in Feb 2026. Even though it feels like a long 2 months has passed, its' not really clear that they were developing this as a competitor to that product. There's nothing really strange about not competing directly with the best, but rather showing whom you are as good as.
- Aurornis 7mo ago
  I don’t know why anyone would do the mental backflips to defend this. They posted charts with logos for Claude and others. You had to read the fine details to realize they weren’t comparing to the latest offerings from those companies. They were counting on you not noticing. There’s zero reason to compare to old models unless you’re trying to mislead.
miki123211 7mo ago
Ah, so that explains the recent wave of Qwen team-member departures.
- dhfs 7mo ago
  Interesting! What is your reasoning behind that? I just learned there where closed models from the team before this so that shouldn’t have been a surprise for the employees? Or do you think the internal communication was: we will release better open models the the existing closed ones to push everything forward and now when they are getting competitive they are becoming proprietary?
jimbokun 7mo ago
I’m starting to wonder where the most is for any of these models. Sure they are not cheap to train. But if open weight models continue to be trained and continue to become available on cheaper hardware, how do dedicated AI companies protect their margins?
- nextaccountic 7mo ago
  OpenAI found the answer: artificially curtail the supply of DRAM wafers (by buying 40% of world's supply without necessarily having a feasible plan to make use of all of them], to prevent consumers from getting access to gpus with more and more memory, which could allow them to get dangerously close to the state of art while running local AI Rather than an increase in VRAM of consumer gpus, we are seeing a decrease, which is pretty optimal for OpenAI
nwienert 7mo ago
4.5 is better than 4.6 though in practice. 4.6 was purely a cost savings change with enough benchmark gamification to look better.
- girvo 7mo ago
  Exactly. 3.6 plus in the exact same coding agent harness is notably worse in all of my testing compared to 3.5 plus. The former gets stuck in ridiculous thought loops on the exact same tasks I’m testing. Fascinating really, I expected more for some reason.
- SyneRyder 7mo ago
  I've found Opus 4.6 to be smarter than 4.5, at least in some ways. There's a bug I'd been trying to solve for a decade (and so had other humans) and I've been giving it to each model to try and solve, including in interactive sessions. Each model got closer, but none of them actually solved it, until Opus 4.6 got it on the first go (I probably used Ultrathink). This was before the 1M context was available. I'd agree that 4.6 and 4.5 are different, but I don't think it's correct that 4.6 is just reduced and benchmaxxed. It genuinely solved problems for me that no other model has been able to. I think I'd like to have seen the 4.6 benchmarks also included against Qwen.
cyanydeez 7mo ago
The business model, howver, is lobster in a bucket. Any model that starts gaining as a private model will have competitors to release comparable open models because those locked in customers will not swotch unless you demo the capabilities. So expect every now and then a open model burp from the trailing frontiers. Afterall, its all sunk cost so once you have it and no customers, theres zero reason not to spike your competition and try again or exit.
epolanski 7mo ago
I use different models in production and model's "personality" as in tendency to not go off script, not consume gazillions of tokens recursively, follow instructions etc, are more relevant than "brute" power which is okayish as a metric for agentic coding on generous token plans. Chinese models are very competitive in that regard, you'll often look at 70-90% price reduction at the same quality.
jona-f 7mo ago
> Most users of cheap API tokens are not loyal to any brand In the exploration phase, yes. But once your setup settles down you likely want to stay on the same model for stable operation.
- 8n4vidtmkvmk 7mo ago
  I feel like this is true. I don't mind being a blip behind the bleeding edge if I don't have to change my tooling every month. But the second my current provider tries to screw me over, I'll still jump ship

cubefox 7mo ago

> I think there is a moderately large market for models like this that aren’t quite SOTA level but can be served up much cheaper. There isn't, pretty much everyone wants the best of the best.

scoopdewoop 7mo ago
That isn't true. In a Codex or Claude Code instance, sure... but those are not the main users of APIs. If you are using LLMs in a service for customers, costs matter.
Aurornis 7mo ago
The market for API tokens is bigger than people like you and I (who also want the best) using then for code. There are a lot of data science problems that benefit from running the dataset through an LLM, which becomes bottlenecked on per-token costs. For these you take a sample subset and run it against multiple providers and then do a cost versus accuracy tradeoff. The market for API tokens is not just people using OpenCode and similar tools.
sidrag22 7mo ago
maybe there isnt, but as understanding grows people will understand that having an orchestration agent delegate simple work to lesser agents is significant not only for cost savings, but also for preserving context window space.
Someone1234 7mo ago
> There isn't, pretty much everyone wants the best of the best. For direct user interaction or coding problems, perhaps. But as API calls get cheaper, it becomes more realistic to use them for completely automated workflows against data-sets, or as sub-agents called from expensive SOTA models. For example, in Claude, using Opus as an orchestrator to call Sonnet sub-agents, is a popular usage "hack." That only gets more powerful, as the Sonnet equivalent model gets cheaper. Now you can spawn entire teams of small specialized sub-agents with small context windows but limited scope.
- thinkcontext 7mo ago
  > But as API calls get cheaper, it becomes more realistic to use them for completely automated workflows against data-sets Seems like a huge waste of money and electricity for processes that can be implemented as a traditional deterministic program. One would hope that tools would identify recurrent jobs that can be turned into simple scripts.
  - Someone1234 7mo ago
    It depends on the specific task. For example: "Here our dataset that contains customer feedback comment fields; look through them, draw out themes, associations, and look for trends." Solving that with a deterministic program isn't a trivial problem, and it is likely cheaper solved via LLM.
    - cubefox 7mo ago
      It makes sense if the dataset is so large that LLM cost is a prohibitive factor. Otherwise a frontier LLM has the advantage of producing a better result.
- alexsmirnov 7mo ago
  Exactly. I did create my own MCP with custom agents that combine several tools into a single one. For example, all WebSearch, WebFetch, Context7 exposed as a single "web research" tool, backed by the cheapest model that passes evaluation. The same for a codebase research Use it with both Claude and Opencode saves a lot of time and tokens.
regularfry 7mo ago
Everyone may want the best, but the amount of AI-addressable work outstrips the budget available for buying the best by quite a wide margin.
joefourier 7mo ago
Ever hit your daily limit on Claude Code and saw how expensive it is to pay per token?
- girvo 7mo ago
  All the time now… it’s wild how little usage you get with Opus on the Pro sub now haha
PhilippGille 7mo ago
The OpenRouter usage stats indicate the opposite: https://openrouter.ai/rankings?view=month https://openrouter.ai/rankings?view=month
- jjice 7mo ago
  OpenRouter usage is likely skewed towards LLMs that are more niche and/or self-hostable by solid hardware that's available, but most consumers don't have on hand. I can imagine Anthropic and OpenAI LLMs often get called directly from their APIs instead. At least from my experience and friends of mine, we use OpenRouter for cases where we want to use smaller LLMs like Qwen, but when I've used ChatGPT and Claude, I use those APIs directly.
  - senordevnyc 7mo ago
    Same, and my little SaaS is pushing more than 0.1% of the TOTAL volume of tokens on OpenRouter, so the reality is they’re TINY.
    - imtringued 7mo ago
      0.1% of OpenRouter is around 400 billion tokens per month or around $400k per month at a cost of $1 per 1 million input tokens, not counting output. I think it's pretty disingenuous to call your SaaS little when it is projected to spend at least 5 million USD just on tokens and this is a low end estimate.
      - senordevnyc 7mo ago
        Their homepage says 30T tokens monthly, so 0.1% would be 30 billion. And I pay way less than $1 per input token, especially when caching is taken into account. EDIT: they updated it in the last day or two, now it says 70T, so I’m a little below 0.1% now. But seriously, the point stands, 70T tokens a month just isn’t that much in the global scheme. The big labs are pushing quadrillions each.
noman-land 7mo ago
OpenCode allows for free inference tho.
esafak 7mo ago
That's only because current models don't saturate people's needs. Once they are fast and smart enough people will pick cheaper ones.
wolttam 7mo ago
Nope. I get very good results from GLM 5 and 5.1. I’m not working on anything so complex and groundbreaking that I need the best. Coding is a rung on the ladder of model capability. Frontier models will grow to take on more capabilities, while smaller more focused models start becoming the economical choice for coding
- girvo 7mo ago
  GLM-5 is surprisingly good to be fair. Punches well above its weight IMO
wongarsu 7mo ago
For coding I want the best. Both I and $work do lots of things besides coding where smaller models like qwen3.5-27b work great, at much lower cost.
thraxil 7mo ago
No. Right now I'm upset that Google has removed (or at least is in the process of removing) the Gemini 2.0 flash model. We use it for some pretty basic functionality because it's cheap and fast and honestly good enough for what we use it for in that part of our app. We're being forced to "upgrade" to models that are at least 2.5 times as expensive, are slower and, while I'm sure they're better for complex tasks, don't do measurably better than 2.0 flash for what we need. Yay. We've stuck with the GCP/Gemini ecosystem up until now, but this is kind of forcing us to consider other LLM providers.
- toofy 7mo ago
  this is one of the reasons im hearing more and more people are using open/locally hosted models. particularly so we dont have to waste time to entirely redo everything when inevitably a company decides to pull the rug out from under us and change or remove something integral to our flow, which over the years we've seen countless times, and seems to be getting more and more common. products entirely disappearing or significantly changing will be more and more common in the llm arena as things move forward towards companies shutting down, bubbles deflating, brand priorities drastically reshifting, etc... i think, we're at or at least close to a time to really put some thought into which pieces of your flow could be done entirely with an open/local model and be honest with ourselves on which pieces of our flow truly needs sota or closed models that may entirely disappear or change. in the long run, putting a little bit of thought into this now will save a lot of headache later.
  - jimbokun 7mo ago
    What’s interesting about this is that for previous technologies you could define a standard and demonstrate compliance with interfaces and behavior. But with LLMs, how do you know switching from one to another won’t change some behavior your system was implicitly relying on?
  - thraxil 7mo ago
    Yeah. Back when Gemma2 came out we benchmarked it and were looking at open models. For our use case though, while the tasks are pretty simple, we do need a pretty large context window and Gemini had a big lead there over the open models for quite a while. I'll probably be evaluating the current batch of open models in the near future though.
wolvoleo 7mo ago
Not really. It depends on the usecase. For private stuff I'm very happy to take what was SOTA a year or 2 ago if I can have it all running in my home and don't have to share any of my data with some sleazy big tech cloud. The price is a concern too of course. But privacy is a bigger one for me. I absolutely don't trust any of their promises not to use data for training purposes.
freehorse 7mo ago
Not all tasks require models like opus. If they do not, then it is more efficient to use cheaper and faster models. For most of my tasks now I use the big kimi/qwen/glm models because they are cheap and good enough, if not even the smaller locals ones. I would say that for a significant part of the current market open-source models are good enough to fill a part of it.

zozbot234 7mo ago

> not an open weight model like they’ve become known for. Right, they state that they'll release "smaller" variants openly at some point, with few details as to what that means. Will there be a ~300B variant as with Qwen 3.5? The blog post doesn't say.

echelon 7mo ago
I'm not interested in adopting an inferior closed source weight from a geopolitical rival. The open source weights argument was the one thing China had going and that I was seriously cheering them on for. They could have been our saviors and disrupted the US tech giants - and if it was open, I'd have welcomed it. Now they show their true colors. They want to train models on our engineering to replace us, while simultaneously giving nothing back? No thanks. I'd rather fund the shitty US hyperscalers. At least that leads to jobs here. If there's a company willing develop and foster large scale weights in the open, I'll adopt their tooling 100%. It doesn't matter if they're a year behind. Just do it open and build an entire ecosystem on top of it. The re-AOLization of the internet into thin clients is bullshit, and all it takes is one player to buck the rules to topple the whole house of cards.
- zozbot234 7mo ago
  > I'm not interested in adopting an inferior closed weights model from a geopolitical rival. That's a very reasonable stance. It doesn't change the fact that we do have plenty of local models (up to and including Qwen 3.5) that are still quite useful.
- cmrdporcupine 7mo ago
  Whereas I as a Canadian am absolutely eager to see a serious competitor from a rival to the US because sending money south to Anthropic and OpenAI who think it's ok to spy on (or worse) their non-American customers, and are headquartered in a country that is trying to crush my country's economy, interfere in our domestic politics, and put us out of work and making threats on political allies. I'd prefer them to be open weight, but I'd love to sub a decent competitive coding plan from a European or Chinese provider. Right now they're not quite there. If closing it and charging for it brings them closer to competitive, that's ok. If the US tech and AI industry long term wants customers and a broad market outside of their own domestic base, they need to reconsider who they are bending the knee to, and how they are defining their policies in relation to the Trump administration. Bring on the Chinese competition.

dev_l1x_be 7mo ago

How stupid somebody has to be to mix up Opus with Qwen?

cieplok 7mo ago
OP didn't say about confusing Opus with Qwen but rather people being confused about Qwen3.6-Plus not being available as an "open weight" model available for self hosting.

jstummbillig 7mo ago

> Initial reactions are mostly anger from everyone who didn’t realize that the play along was to give away the smaller models as advertising, not because they were feeling generous. The naivety around this has been staggering quite frankly. All of a sudden, people thinking that meta etc are releasing free models because they believe in open access and distribution of knowledge. No, they just suck comparatively. There is nothing to sell. Using it to recruit and generate attention is the best play for them.

Gracana 7mo ago
I don't think there's so much naivety. People can be aware of the the plan and still be frustrated and disappointed when it happens.
- zozbot234 7mo ago
  I'm not frustrated or disappointed, we have lots of models from Qwen already. We haven't really lost anything. And plenty of players only release "smaller" models anyway, so it's hardly unprecedented.
- Aurornis 7mo ago
  For a brief moment there were a lot of comments about how Chinese tech companies are our saviors in the age of AI because they were releasing their models. It was an edgy contrarian take that was getting a lot of traction, mostly from commenters who were unfamiliar with Alibaba and thought it was the anti-Big-tech
  - Gracana 7mo ago
    My explanation is simpler and does not rely on assuming that anyone is an idiot. Or an edgy contrarian.
- GorbachevyChase 7mo ago
  I’m waiting for the grand reversal where Anthropic abuses the Qwen API to train the next Haiku.

true_religion 7mo ago

Opus was released in Feb 2026. Even though it feels like a long 2 months has passed, its' not really clear that they were developing this as a competitor to that product. There's nothing really strange about not competing directly with the best, but rather showing whom you are as good as.

Aurornis 7mo ago
I don’t know why anyone would do the mental backflips to defend this. They posted charts with logos for Claude and others. You had to read the fine details to realize they weren’t comparing to the latest offerings from those companies. They were counting on you not noticing. There’s zero reason to compare to old models unless you’re trying to mislead.

miki123211 7mo ago

Ah, so that explains the recent wave of Qwen team-member departures.

dhfs 7mo ago
Interesting! What is your reasoning behind that? I just learned there where closed models from the team before this so that shouldn’t have been a surprise for the employees? Or do you think the internal communication was: we will release better open models the the existing closed ones to push everything forward and now when they are getting competitive they are becoming proprietary?

jimbokun 7mo ago

I’m starting to wonder where the most is for any of these models. Sure they are not cheap to train. But if open weight models continue to be trained and continue to become available on cheaper hardware, how do dedicated AI companies protect their margins?

nextaccountic 7mo ago
OpenAI found the answer: artificially curtail the supply of DRAM wafers (by buying 40% of world's supply without necessarily having a feasible plan to make use of all of them], to prevent consumers from getting access to gpus with more and more memory, which could allow them to get dangerously close to the state of art while running local AI Rather than an increase in VRAM of consumer gpus, we are seeing a decrease, which is pretty optimal for OpenAI

nwienert 7mo ago

4.5 is better than 4.6 though in practice. 4.6 was purely a cost savings change with enough benchmark gamification to look better.

girvo 7mo ago
Exactly. 3.6 plus in the exact same coding agent harness is notably worse in all of my testing compared to 3.5 plus. The former gets stuck in ridiculous thought loops on the exact same tasks I’m testing. Fascinating really, I expected more for some reason.
SyneRyder 7mo ago
I've found Opus 4.6 to be smarter than 4.5, at least in some ways. There's a bug I'd been trying to solve for a decade (and so had other humans) and I've been giving it to each model to try and solve, including in interactive sessions. Each model got closer, but none of them actually solved it, until Opus 4.6 got it on the first go (I probably used Ultrathink). This was before the 1M context was available. I'd agree that 4.6 and 4.5 are different, but I don't think it's correct that 4.6 is just reduced and benchmaxxed. It genuinely solved problems for me that no other model has been able to. I think I'd like to have seen the 4.6 benchmarks also included against Qwen.

cyanydeez 7mo ago

The business model, howver, is lobster in a bucket. Any model that starts gaining as a private model will have competitors to release comparable open models because those locked in customers will not swotch unless you demo the capabilities. So expect every now and then a open model burp from the trailing frontiers. Afterall, its all sunk cost so once you have it and no customers, theres zero reason not to spike your competition and try again or exit.

epolanski 7mo ago

I use different models in production and model's "personality" as in tendency to not go off script, not consume gazillions of tokens recursively, follow instructions etc, are more relevant than "brute" power which is okayish as a metric for agentic coding on generous token plans. Chinese models are very competitive in that regard, you'll often look at 70-90% price reduction at the same quality.

jona-f 7mo ago

> Most users of cheap API tokens are not loyal to any brand In the exploration phase, yes. But once your setup settles down you likely want to stay on the same model for stable operation.

8n4vidtmkvmk 7mo ago
I feel like this is true. I don't mind being a blip behind the bleeding edge if I don't have to change my tooling every month. But the second my current provider tries to screw me over, I'll still jump ship