241–250 of 559 posts
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Yea as far has hobbies go, I feel like this is on the low end. I know people who collect watches and corvettes, that's way more expensive and functionally you can't really do anything special with them.
The difference is watches and corvettes typically appreciate in value, where as computer hardware typically drops like a rock.
Does a bit worse than Opus 4.8 in my tests[0], but it's 5x cheaper and 3x slower. [0]: https://aibenchy.com/compare/anthropic-claude-opus-4-8-mediu...
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We need a benchmark of independent community sourced benchmarks! …probably already is one
It's not super scientific, but I really like to watch Bijan Bowen's videos on Youtube. I think he's pretty fair about the way he compares them, and it's enough for what I'm doing.
I like reading benchmarks, but I take them all with a grain of salt. They're just to tell me if the model is worth even trying for my task. I've heavily used self-hosted Qwen 3.6 and Gemma 4 on a bunch of different tasks, and while the benchmarks consistently say Qwen is the better model, I simply don't find that to be the case for anything I do. I think Qwen is tuned for benchmarks, while Google couldn't give two shits about most of the benchmarks, they're just busy making unusually smart tiny models.
I have taken another look on these open models after the fiasco of Fable and GPT 5.6 this weekend and... GLM-5.2 truly is a good workhorse model for daily programming. I consider myself a heavy user of LLMs and a seasoned developer. A typical session for me with GPT is usually over a hundred dollars... This weekend I programmed a matrix bot with encryption and a Rust agent with some tools. Because I need one and Open…
> A typical session for me with GPT is usually over a hundred dollars. I don't think a $100 session is "typical". I use GPT for months. $20/m plus plan is enough for my daily work.
I'd blow through $20/month plan in hours.
I have taken another look on these open models after the fiasco of Fable and GPT 5.6 this weekend and... GLM-5.2 truly is a good workhorse model for daily programming. I consider myself a heavy user of LLMs and a seasoned developer. A typical session for me with GPT is usually over a hundred dollars... This weekend I programmed a matrix bot with encryption and a Rust agent with some tools. Because I need one and Open…
GLM 5.2 is a great model, but if you only want to use the best model available, it isn't there yet. Every lab releases models that memorize benchmark answers, both intentionally and unintentionally. But we consistently find that models from Chinese labs have a wider gap between public benchmarks and our evaluations, which we designed to be less vulnerable to benchmaxxing. In multi-agent coding environments, GLM 5.2 i…
I have taken another look on these open models after the fiasco of Fable and GPT 5.6 this weekend and... GLM-5.2 truly is a good workhorse model for daily programming. I consider myself a heavy user of LLMs and a seasoned developer. A typical session for me with GPT is usually over a hundred dollars... This weekend I programmed a matrix bot with encryption and a Rust agent with some tools. Because I need one and Open…
Twenty dollars? How are you comfortable spending that much to write something as simple as a matrix bot? Are people doing this kind of thing just super rich or am I missing something?
I use GLM 5.2 via Neuralwatt and it's gotten so cheap I wouldn't mind cancelling my personal Claude subscription if work gave me one. I've spent 374M tokens this month and it only cost me $18 on energy-based pricing.
I have taken another look on these open models after the fiasco of Fable and GPT 5.6 this weekend and... GLM-5.2 truly is a good workhorse model for daily programming. I consider myself a heavy user of LLMs and a seasoned developer. A typical session for me with GPT is usually over a hundred dollars... This weekend I programmed a matrix bot with encryption and a Rust agent with some tools. Because I need one and Open…
Twenty dollars? How are you comfortable spending that much to write something as simple as a matrix bot? Are people doing this kind of thing just super rich or am I missing something?
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Do quantized models specifically prune out specific knowledge? I think they just compress things down but they're still in there. You'd most likely need to do that when you're doing the initial model training, but I'm not expert.
> they just compress things down but they're still in there The compression is almost certainly in part specific knowledge getting fuzzed.