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| ▲ | alexjplant 3 hours ago | parent | next [-] |
| If you don't have regulatory hurdles to jump over then there are a whole raft of open-weight models that perform basically as well as Anthropic's offerings (and, in many cases, better because they're pulling fewer capacity-stretching shenanigans). Check out Kimi, DeepSeek, and GLM series models in particular with something like OpenCode or Pi as a coding harness. If you need a Claude-alike web UI then spin up Open WebUI in a container and expose it via cloudflared so you can use it on the go. |
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| ▲ | jatora 2 hours ago | parent | next [-] | | > perform basically as well
> in many cases, better Completely, unequivocably, factually inaccurate. I wonder if you are being dishonest on purpose? Best case scenario you are advocating this from a place of little experience. Either way it is dishonest. | | |
| ▲ | throw1234567891 2 hours ago | parent [-] | | It’s not, you drink too much Kool-Aid, and your employer has too much money. Or the things you do are simply so irrelevant that nobody cares you’re sending stuff to a company of dubious morality. |
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| ▲ | gymbeaux 3 hours ago | parent | prev [-] | | Kimi and DeepSeek are impressive for their size but still run slow on any hardware you or I would have. If you’re proposing we run those via a cloud service, I don’t see a reason to do that when it’s an inferior model and I still have to pay per token for it. | | |
| ▲ | alexjplant 3 hours ago | parent | next [-] | | OpenCode Go provides a lot of usage for these models for the paltry sum of $10/month. Z.ai's coding plan provides a single-digit multiple of Claude Code's usage for a similar price and performance level. Kimi and DeepSeek models are hundreds of billions of parameters (or, in K3's case, >1T). Many of these models have Opus-level benchmarks and, as I pointed out previously, often practically outperform Anthropic models because they're more consistent. | |
| ▲ | throw1234567891 2 hours ago | parent | prev [-] | | You should run the maths once. Those tokens cost you much more than the hardware would. But yeah, CAPEX vs OPEX something something. |
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| ▲ | jnathsf 3 hours ago | parent | prev | next [-] |
| Codex w GPT 5.6 no issues w downtime and more token/cost efficient than Opus |
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| ▲ | joshheitzman 3 hours ago | parent | prev [-] |
| Dozens of providers of open-weight models. I have one session going with synthetic.new and another going with novita.ai right now. |
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| ▲ | gymbeaux 3 hours ago | parent [-] | | But they’re slower (and benchmark worse) than Opus, GPT, et al. Why? | | |
| ▲ | joshheitzman 24 minutes ago | parent [-] | | Personally I don't care about common benchmarks as I don't find actual coding agent performance correlates strongly with them. One reason to use open-weight models is that they don't hide the reasoning, so you can do very aggressive context management in your harness to use significantly less tokens. Smaller prompts are faster since KV is N^2 plus it can be dramatically cheaper (if you balance your aggressive context management with maintaining the prefix cache as much as possible). Even paying for API prices directly and using agents as much as I want I spend less per month than the $200 I spent on a Claude MAX sub when I had it. |
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