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This has got to be bait.. 1) OpenAI and Anthropic are killing it, and continue to do so, their coding tools are unmatched for professionals. 2) Local models d

This has got to be bait.. 1) OpenAI and Anthropic are killing it, and continue to do so, their coding tools are unmatched for professionals. 2) Local models don't hold a candle to SOTA models and there's nothing on the horizon that indicates that consumers will be able to run anything close to what you can get in a data center. 3) Coding is a killer product, OpenAI and Anthropic are raking in the cash. The top 3 apps are apps in the app store are AI. Everyone who knows anything is using AI, every day, across the economy.

svcrunch 7mo ago
The grandparent is definitely wrong on (3). Yes, coding is a killer product, I agree with you. On (2), I agree with you for local models. BUT, there are also the open source Chinese models accessible via open-router. Your argument ("don't hold a candle to SOTA models") does not hold if the comparison is between those. On (1), I agree more with the grandparent than with your assessment. Yes, OpenAI and Anthropic are killing it for now, but the time horizon is very short. I use codex and claude daily, but it's also clear to me that open source is catching up quickly, both w.r.t. the models and the agentic harnesses.
- itake 7mo ago
  > the open source Chinese models accessible via open-router And? They aren't as good as SOTA models. Even the SOTA model provider's small models aren't worth using for many of my coding tasks.
  - DeathArrow 7mo ago
    In my limited experience with it, GLM 5.1 is on par with Opus 4.6.
    - naasking 6mo ago
      I used GLM5 quite a bit, and I'd say it was maybe on par with Sonnet for most simple to medium tasks. Definitely not Opus though. Didn't test super long context tasks, and that's where I would expect it to break down. A recent study on software maintainability still showed Sonnet and Opus were peerless on that metric, although GLM series of models has been making impressive gains.
- DeathArrow 7mo ago
  >BUT, there are also the open source Chinese models accessible via open-router. I thought so myself, but after burning a lot of money on OpenRouter in a few days I just subscribed to Z.ai's Coding Pro plan and using the subscription is much, much friendlier with my wallet.
- geysersam 6mo ago
  Open models are good but if you need a $10k GPU to run them then 99% of people are better of subscribing to OAI or CC. Nowadays I also feel model performance matters less than the design of the tool harness, inference speed, and the other systems that surround a typical coding model.
dvt 7mo ago
I don't want to respond to 100 comments about the same thing, and this one happens to be on top, so, in my humble opinion: (1): You don't have to be an Ed Zitron disciple to infer that OpenAI and Anthropic are likely overvalued and that Nvidia is selling everyone shovels in a gold rush. AI is a game-changing technology, but a shitty chat interface does not a company make. OpenAI and Anthropic need to recoup astronomical costs used in training these models. Models that are now being distilled[1] and are quickly becoming commoditized. (And frankly, models that were trained by torrenting copyrighted data[2], anyway.) Many have been calling this out for years: the model cannot be your product. And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing. (2): Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like. The end-state here is likely some models running locally and some running in the cloud. But the current state of OpenClaw token-vomit on top of Claude is fiscally untenable (in fact, this is why Anthropic shut it down). (3): This is typical Dropbox HN snark[3], of which I am also often guilty of. I really don't think AI coding is a killer product and this seems very myopic—engineers are an extreme minority. Imo, the closest we've seen to something revolutionary is OpenClaw, but it's janky, hard to set up, full of vulnerabilities, and you need to buy a separate computer. But there's certainly a spark there. (And that's personally the vertical I'm focusing on.) [1] https://www.anthropic.com/news/detecting-and-preventing-distillation-attacks https://www.anthropic.com/news/detecting-and-preventing-dist... [2] https://media.npr.org/assets/artslife/arts/2025/complaint.pdf https://media.npr.org/assets/artslife/arts/2025/complaint.pd... [3] https://news.ycombinator.com/item?id=9224 https://news.ycombinator.com/item?id=9224
- nl 7mo ago
  > And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing. Anthropic is up to $30B annual recurring revenue. I wish I had failing business models like that. > Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like. I'm not sure what think you are saying here, but if you look at the providers for both "almost-SOTA model (a big Deepseek or Qwen model)" or at the price for Claude on AWS Bedrock, Azure or on GCP you will quickly see inference is very profitable.

svcrunch 7mo ago

The grandparent is definitely wrong on (3). Yes, coding is a killer product, I agree with you. On (2), I agree with you for local models. BUT, there are also the open source Chinese models accessible via open-router. Your argument ("don't hold a candle to SOTA models") does not hold if the comparison is between those. On (1), I agree more with the grandparent than with your assessment. Yes, OpenAI and Anthropic are killing it for now, but the time horizon is very short. I use codex and claude daily, but it's also clear to me that open source is catching up quickly, both w.r.t. the models and the agentic harnesses.

itake 7mo ago
> the open source Chinese models accessible via open-router And? They aren't as good as SOTA models. Even the SOTA model provider's small models aren't worth using for many of my coding tasks.
- DeathArrow 7mo ago
  In my limited experience with it, GLM 5.1 is on par with Opus 4.6.
  - naasking 6mo ago
    I used GLM5 quite a bit, and I'd say it was maybe on par with Sonnet for most simple to medium tasks. Definitely not Opus though. Didn't test super long context tasks, and that's where I would expect it to break down. A recent study on software maintainability still showed Sonnet and Opus were peerless on that metric, although GLM series of models has been making impressive gains.
DeathArrow 7mo ago
>BUT, there are also the open source Chinese models accessible via open-router. I thought so myself, but after burning a lot of money on OpenRouter in a few days I just subscribed to Z.ai's Coding Pro plan and using the subscription is much, much friendlier with my wallet.
geysersam 6mo ago
Open models are good but if you need a $10k GPU to run them then 99% of people are better of subscribing to OAI or CC. Nowadays I also feel model performance matters less than the design of the tool harness, inference speed, and the other systems that surround a typical coding model.

dvt 7mo ago

I don't want to respond to 100 comments about the same thing, and this one happens to be on top, so, in my humble opinion: (1): You don't have to be an Ed Zitron disciple to infer that OpenAI and Anthropic are likely overvalued and that Nvidia is selling everyone shovels in a gold rush. AI is a game-changing technology, but a shitty chat interface does not a company make. OpenAI and Anthropic need to recoup astronomical costs used in training these models. Models that are now being distilled[1] and are quickly becoming commoditized. (And frankly, models that were trained by torrenting copyrighted data[2], anyway.) Many have been calling this out for years: the model cannot be your product. And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing. (2): Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like. The end-state here is likely some models running locally and some running in the cloud. But the current state of OpenClaw token-vomit on top of Claude is fiscally untenable (in fact, this is why Anthropic shut it down). (3): This is typical Dropbox HN snark[3], of which I am also often guilty of. I really don't think AI coding is a killer product and this seems very myopic—engineers are an extreme minority. Imo, the closest we've seen to something revolutionary is OpenClaw, but it's janky, hard to set up, full of vulnerabilities, and you need to buy a separate computer. But there's certainly a spark there. (And that's personally the vertical I'm focusing on.) [1] https://www.anthropic.com/news/detecting-and-preventing-distillation-attacks https://www.anthropic.com/news/detecting-and-preventing-dist... [2] https://media.npr.org/assets/artslife/arts/2025/complaint.pdf https://media.npr.org/assets/artslife/arts/2025/complaint.pd... [3] https://news.ycombinator.com/item?id=9224 https://news.ycombinator.com/item?id=9224

nl 7mo ago
> And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing. Anthropic is up to $30B annual recurring revenue. I wish I had failing business models like that. > Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like. I'm not sure what think you are saying here, but if you look at the providers for both "almost-SOTA model (a big Deepseek or Qwen model)" or at the price for Claude on AWS Bedrock, Azure or on GCP you will quickly see inference is very profitable.