4 ms·

I think the difference between the Anthropic token maximization approach (vibe code all the things!) and OpenAI's focus on efficiency, terseness and token reduc

• wilg 2mo ago
  Oh no, I use the top shelf models every day and I really think they have a lot of room to improve in pretty much every regard. I suspect Fable usage is flatlining because it's not that good comparitively and way too expensive.
• rebolek 2mo ago
  I really would like to see OpenAI’s focus on efficiency but everytime I use Codex, it wastes tokens like there’s no tomorrow, hitting week limit in a day, where I’m able to use Claude just fine. Maybe it’s based on the codebase, I don’t know, but I have better results with Claude than Codex.
  • jimmydoe 2mo ago
    same boat. gpt 5.5/5.6 goes further on its own much more often than opus 4.8/5 does. codex capped ~300k context when claude does 1m. I don't feel codex is saving tokens, and result is usually not as good imo.
    • gatio 2mo ago
      > codex capped ~300k context when claude does 1m. That's configurable in codex.. but there is a higher cost/usage to using it.
  • bicepjai 2mo ago
    I had the opposite experience. Claude models and its harness feel like they are set to eat tokens for everything, especially if it’s ultracode effort. I have seen it spawn 6 agents and eat my 4-hour quota right in front of me. Codex is on point and follows instructions well even with max effort. I like my analogy of Claude being garrulous and Codex being laconic. If I see more limit hits in same sitting session, I have to rearrange my workflows. my experiments with qwen and deepseek have been good, cant wait to try glm and other models.
    • throwup238 2mo ago
      Just before I canceled my 20x Max sub I had a day where I had ~15% of my weekly I was trying to burn. I set it on ultracode and because I had set the max agents 32 for another project and forgot, the five research agents ended up spinning up a total of 26 subagents and burned through the remainder of my weekly in the span of 20 minutes before I noticed and shut it down. “No, not like THAT!”
      • vanviegen 2mo ago
        How can you burn through your weekly budget in 20 minutes? You'd hit your 5 hour budget way before that, right?
        • throwup238 2mo ago
          The five hour budget is about 15% of the weekly on Max 20x. I had about 15% left.
          • vanviegen 2mo ago
            Ah sorry, I read your earlier comment as you being at 15% of your weekly (so the prompt consuming 85%).
      • wccrawford 2mo ago
        Claude did the same thing to me the other day. I ran out of my 5 hr limit, and it went into my $100 credit they had given me. Multiple parallel agents. It ate it in no time flat. When I checked, all that credit was gone, I still wasn't into the next 5 hours, and all the agents had failed, returning nothing. I didn't even get anything for burning all that credit. If I had paid for it, I'd be very, very pissed.
  • vorticalbox 2mo ago
    It might be your prompting. My boss uses opus and gets good results when I use it always burns tokens. The other way is also true too I get great results with sol/terra but my boss does not.
    • rebolek 2mo ago
      Maybe. But if Claude is fine with my prompts while Codex uses them as an excuse to burn tokens. I have nothing against the model, they are more or less on pair, it’s just that Claude is giving me more value for same money.
      • vorticalbox 2mo ago
        If Claude is working for you then stick with it! Happy you’re getting good value from Claude.
    • ygjb 2mo ago
      One of my challenges is that I often end up burning tokens trying to build the right solution rather than building a solution that is good enough and deferring the right choices until later. I have been actively working to change my expectations for building with AI to accept worse solutions to get things going rather than trying to solve everything at launch. This has been a recurring problem for me - as a security engineer catasrophization is a fundamental skill to finding vulnerabilities in complex systems, but makes me to conservative when building. For some of my leaders they are much better at saying 'good enough, ship it, and fix it later'.
  • llama052 2mo ago
    At least with OpenAI you can use a third party harness like Pi.
  • shepherdjerred 2mo ago
    Are you kidding me? OpenAI weekly limits feel _infinite_. I run out of Anthropic limits reliably halfway through the week
  • chaboud 2mo ago
    Codex is fabulous at work, where token use is near limitless and ultra-thorough tool use is welcome. Go ahead and fire off searches for look-alike terms on my 96-core cloud instance. By contrast, Claude Code's bias to make assumptions of reasonableness about underlying systems has proven to be immensely frustrating over the last month or two, both personally and at work. I've wasted days on "that was my mistake. I've been reporting numbers on the old architecture because I hadn't enabled the new one in the config" both at work and home. It's immensely frustrating. But here we are. Wrestling with energetic idiots in model form, wrangled by over-specific harnesses that struggle to stay off of deranged side-quests. What a time to be alive!
• smartmic 2mo ago
  > who wins the long-term race Isn’t the race between Chinese open-weight models and the others more decisive for the future?
  • colechristensen 2mo ago
    it'll all be centralized models justifying their capability against local inference in, maybe 3 years or less once we have a bit more memory fab capacity and the insane bottomless investment in AI giants realizes there is a bottom, local hardware will catch up with model performance to the extent that centralized inference will be downgraded to special cases or for orgs that find it cheaper than buying expensive hardware but really most power users are going to have 1 TB unified RAM and local models that will do well enough for light office use you can still have a cheap laptop and a claude subscription
  • polotics 2mo ago
    I think the race is actually between locally optimized rigs with extremely strict context management, and the rest.
    • nozzlegear 2mo ago
      Those rigs are running one of the open Chinese models though, right?
• apsurd 2mo ago
  You've articulated what I found unsettling about Boris' pov that "coding is a solved problem". I listened to a few of his talks and was instinctively off-put by that sentiment. I figured a fellow programmer would understand and speak on the nuances. Granted it did make me think about my biases and to lean into more future facing inevitabilities. But you've nailed it, for Boris and Anthropic, they are betting that coding is a solved problem in the sense that any person can one-shot any random idea and the output will be in some abstract sense "good". And then at what cost and toward what end?
  • cloverich 2mo ago
    On the one hand it feels true. On the other I ask - what good software have anthropic, or anyone else, produced that was fully vibed? As someone who does near 100% of my coding via LLM these days, i still find that for anything complex i am still looking at and thinking in terms of code. Im still quality checking and steering at some interval via code. And im still not sure how or whether i can replicate that level of thought without still dealing in code at times.
    • polotics 2mo ago
      It's a scale thing. with one fairly simple Android app, it's doable. anything Enterprisey is a nightmare. maybe that's the lesson and the problem is not with the llms but with accidental complexity. Just right now I feel like I'm one mythical LLM minute away from the next clean pull request...
    • joquarky 2mo ago
      You'll have to define "good" before you can expect quality responses.
  • mattm 2mo ago
    In this last week I've started reviewing code more and in just a short time, I've found 3 fairly simple things that were introduced by Claude that were not wrong per se, however, they were very inefficient and didn't address the root of the issue. I still think we're in a place where the output looks good as long as you don't look under the hood or keep it scoped to small, vibe-coded projects. Once you get beyond that it can fall apart. Anthropic must have a large codebase by now though. Yet I haven't seen much released from them about how they actually work day to day on development.
• ph4rsikal 2mo ago
  Claude used to be 10x more efficient. I think there are no barriers of entry between one coding agent and the other. Therefore, I expect them to reverse as soon as people switch. At least this is what I will do.
• alightsoul 2mo ago
  There is no evidence regarding distillation. It is impossible to distill a model in just a month which was the gap between fable and Kimi k3. Anthropic wouldn't even keep up with the load. It is just another example of American exceptionalism.
  • Barbing 2mo ago
    “In one notable technique, their prompts asked Claude to imagine and articulate the internal reasoning behind a completed response and write it out step by step—effectively generating chain-of-thought training data at scale. We also observed tasks in which Claude was used to generate censorship-safe alternatives to politically sensitive queries like questions about dissidents, party leaders, or authoritarianism, likely in order to train DeepSeek’s own models to steer conversations away from censored topics. By examining request metadata, we were able to trace these accounts to specific researchers at the lab.” — “You are an expert data analyst combining statistical rigor with deep domain knowledge. Your goal is to deliver data-driven insights — not summaries or visualizations — grounded in real data and supported by complete and transparent reasoning.” (variations appearing 10s of 1000s of times) https://www.anthropic.com/news/detecting-and-preventing-distillation-attacks https://www.anthropic.com/news/detecting-and-preventing-dist... Does Dario have the same relationship with the truth as Sam? (Their companies pirate books and develop products that compete at some level with those books’ authors, so obviously neither are that wonderfully trustworthy, so maybe “no evidence” meant you don’t believe this evidence rather than you weren’t aware of it. I would understand and respect your lack of belief!)
    • maxdo 2mo ago
      When they do that they pay billions . Unlike China. That’s the order of law vs bunch of companies in a totalitarian government
      • alightsoul 2mo ago
        They are not paying billions anymore. They just switched to buying and then destroying books. Arguably that's worse than training off of Anna's archive which Chinese companies still do. This comment is another example of American exceptionalism.
• deleted 2mo ago
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• WhiteDawn 2mo ago
  Not to sound like a mark, I try to not get attached to any of these providers. I've jumped between copilot, claude, gemini and chatgpt since the start of the year. chatgpt wasn't even worth looking at early this year. Anthropic has the smarter models for sure, and seems to be default in corporate. However, the amount of budget you get with GPT as a user is much better, the harness feels more polished, and the models are faster. They are also much nicer to work with, I can just read the output for the most part. With claude I get pages of text and need to skim to find where the actual information i need to care about lies. So much more cognitive overhead. Sol is smart enough for anything I've thrown at it, it's not one-shotting like fable, but I'm more willing to actually go back and forth with it, and it's likely producing better output to keep a human in the loop rather than trying to solve the world independently and making multiple incorrect assumptions. I think GPT sees the market changing and is correctly repositioning themselves. Anthropic is down the wrong road, and if they don't correct course quickly I'm sure many of those enterprise contracts will start pivoting.
  • throwaway894345 2mo ago
    I just need a Sol translator to sit in front of Fable and Opus :/
    • vardalab 2mo ago
      Opus yesterday produced this gem: "Standing where it stood." I replied, "never stop stopping!" and we had a stalemate, lol
    • astro1234 2mo ago
      The Opus-human patois is unbearable
  • esseph 2mo ago
    > I think GPT sees the market changing and is correctly repositioning themselves I'm not sure how they'll survive their creditors tbh
    • 2mo ago
• Ameo 2mo ago
  Seems like it wouldn't be hard for Anthropic to tweak a few prompts or RL pipelines to tune for terseness and token-efficiency if that stays as something that consumers want. I find it unlikely that there's some fundamental property of OpenAI's models' "personality" or style which Anthropic (or any other serious AI firm) wouldn't be able to match if they wanted to.
• throwaway894345 2mo ago
  > My money is on the more efficient solution. Even if Anthropic can win some benchmarks by using 3x tokens over 3x time, it is a terrible base to build toward the future. Users are no longer willing to wait exponentially long for linear improvements. As much as I wish you were right, everything about software economics for the last 30+ years has favored _less efficient software_. Traditional hardware has been optimized for traditional software for decades and we still see bloated software win consistently. LLM hardware is at the start of its cycle, with abundant low-hanging fruit to conquer--I would expect the pro-bloat dynamics to weigh even more heavily in the LLM space than in the traditional software space.
• maxglute 2mo ago
  [dead]
• thefourthchime 2mo ago
  If the problem isn't that hard, I've been using Cursor's Auto or Grok 4.5 (not 4.6, it's too slow). They're both pretty damn competent and more important, Extremely Fast! I find the speed more useful than trying to be a hundred percent complete on every task. The big intelligent models screw up all the time as well, but I have to wait twenty minutes to three hours to find out. GPT 5.6 is especially tenacious and seems to want to solve every bug in edge case 1000% all the time. Sometimes that's what you need, but a lot of times you're just trying to move fast and figure out what the product is.
• planckscnst 2mo ago
  LLMs are already of sufficient capability that if they were super cheap and fast and made no progress on intelligence, we will still make huge leaps in our ability to build systems and solve problems. I'm just happy there is capital behind the efficiency path because I am confident we can get positive value on that path.
• JamesSwift 2mo ago
  They are both on borrowed time. The only thing keeping them afloat business wise is that current hardware costs are prohibitive which keeps local models artificially constrained. The next era will be open weight / local model for the masses and SOTA for the big players.
  • Tarean 2mo ago
    If your prognosis is true I'm not sure it's fully positive. Inference without batching is just massive less efficient, even if local hardware can be more energy efficient per operation and can skip out on cooling. Open weights, obviously beneficial. Local compute when not necessary, seems like it'd be significantly worse for the environment?
    • JamesSwift 2mo ago
      To more fully flesh out what my thoughts on this: I think because more devs cant run things locally, we are not getting the "open source gains" that you would get by having the network effect of more eyes on the work. Theres still little nuggets of gold in there though (eg antirez's DS4 project). But once more people can get their hands on hardware, I think the flood gates will open. And once that happens, I dont necessarily think people will run locally. But that will enable fungible service providers which we already see, but at a much larger scale. To a lesser degree, open weights also leads to an eventuality of these two companies not being able to sustain their capital investments. Not to mention their pricing models are unsustainable as they currently stand. So they are being eroded from the outside-in, while also trying to fight the internal pressure to continue to raise prices/margins. EDIT: I actually think the harness is more of a future for these big players. And theres real value in providing a high quality harness. So maybe they move to SAAS for claude code in the future. Who knows