> But also, the latest DeepSeek is 1.6T parameters. “Choosing” to run this locally is a choice that comes with a seven digit price tag

Unless you're specifically thinking about running the model at stock precision in a datacenter environment and generating ~100 tok/s or more on a 24/7 basis (the equivalent of a >$1000/mo spend even on the cheapest third-party APIs), that's very likely off by multiple orders of magnitude. Even then, experimentation can be done with cheap neoclouds on a pay-as-you-go basis.

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kube-system an hour ago | parent [-]

I’m aware. The context of the discussion here is choosing DeepSeek over a US hosted model from Google, Anthropic or OpenAI.

The equivalent comparison would be running it at full frontier quality.

If you want less than frontier quality, there’s tons of great open weight models other than DeepSeek.

> cheap neoclouds

Again, fails the compliance checkbox.

	▲	zozbot234 34 minutes ago \| parent \| next [-]
		> Again, fails the compliance checkbox. OK, then the not-so-cheap hyperscalers that these enterprises are already relying on. E.g. AWS Bedrock will run these models. It's silly to insist on all three of your checkboxes being ticked anyway - U.S. proprietary models don't give you that because the frontier ones are super expensive and the mini models have only barely acceptable cost.
	▲	qarl 36 minutes ago \| parent \| prev \| next [-]
		Azure serves DeepSeek V4 Pro, about 10X cheaper than GPT-5.5.
	▲	qarl an hour ago \| parent \| prev [-]
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