That's maybe a few dollars to tens of dollars in electricity per month depending on where in the US you live

> That's like ten normal computers worth of power for the GPUs alone.

Maybe if your "computer" in question is a smartphone? Remember that the M3 Ultra is a 300w+ chip that won't beat one of those 3090s in compute or raster efficiency.

Did you even try to read and understand the parent comment? They said they regularly run out of quota on the exact subscription you're advising they subscribe to.

If you can get near 100% utilization for your own GPUs (i.e. you're letting requests run overnight and not insisting on any kind of realtime response) it starts to make sense. OpenRouter doesn't have any kind of batched requests API that would let you leverage that possibility.

> You could buy a lot of tokens for the price of a pair of 3090s and a machine to run them.

That's a subjective opinion, to which the answer is "no you can't" for many people.

Everyone should do the calculation for themselves. I too pay for couple of subs. But I'm noticing having an agent work for me 24/7 changes the calculation somewhat. Often not taken into account: the price of input tokens. To produce 1K of code for me, the agent may need to churn through 1M of tokens of codebase. IDK if that will be cached by the API provider or not, but that makes x5-7 times price difference. OK discussion today about that and more https://x.com/alexocheema/status/2020626466522685499

And it's worth noting that you can get DeepSeek at those prices from DeepSeek (Chinese), DeepInfra (US with Bulgarian founder), NovitaAI (US), AtlasCloud (US with Chinese founder), ParaSail (US), etc. There is no shortage of companies offering inference, with varying levels of trustworthiness, certificates and promises around (lack of) data retention. You just have to pick one you trust

Doing inference with a Mac Mini to save money is more or less holding it wrong. Of course if you buy some overpriced Apple hardware it’s going to take years to break even.

Buy a couple real GPUs and do tensor parallelism and concurrent batch requests with vllm and it becomes extremely cost competitive to run your own hardware.

I don't think an Apple PC can run full Deepseek or GLM models.

Even if you quantize the hell out of the models to fit in the memory, they will be very slow.

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> In 2 years you could make that investment back in pay raise.

Could you elaborate? I fail to grasp the implication here.

> In 2 years you could make that investment back in pay raise.

you can't be a happy uber driver making more money in the next 24 months by having a fancy car fitted with the best FSD in town when all cars in your town have the same FSD.

This claim has so many assumptions mixed in it's utterly useless

Not the person you’re responding to, but my experience with models up through Qwen3-coder-next is that they’re not even close.

They can do a lot of simple tasks in common frameworks well. Doing anything beyond basic work will just burn tokens for hours while you review and reject code.

It's just as fast, but not nearly as clever. I can push the context size to 120k locally, but quality of the work it delivers starts to falter above say 40k. Generally you have to feed it more bite-sized pieces, and keep one chat to one topic. It's definitely a step down from SOTA.