DeepSeek models are open-source so there are a bunch of third-party providers offering similar prices. Factoring in that DeepSeek have to train the model (whereas third parties can make a small profit over just the inference costs) I'd assume that on net they're spending investor money, but I wouldn't think that's any less true of OpenAI.
Yes, DeepSeek is open-weight, but these third-party providers offering similar prices are subsidized with VC money as well. And you can find a range of prices for deepseek-v4-flash going up to and over $1/Mtok.
Even that $1/Mtok provided by Together AI is heavily subsidized by more than $1B in VC money.
This makes it unclear how the true cost curve is progressing. It’s not possible to confidently comment one way or another on the rate that cost is coming down when the entire industry is so heavily subsidized.
> Even that $1/Mtok provided by Together AI is heavily subsidized
Can you link this? I'm unable to find them offering deepseek-v4-flash. I think you could even host the pro model for a bit under $1/Mtok. You can get ~1000TPS out of the box on a B300 that you can rent for ~$3/hr, so around $0.83/Mtok.
Regardless - Alibaba, DeepSeek, NovitaAI, AtlasCloud, Cloudflare, DeepInfra, SiliconFlow, GMICloud, Morph, Baidu, Parasail, DigitalOcean, AkashML, StreamLake and likely others all seem to be offering it under $0.3 per million output tokens[0].
> This makes it unclear how the true cost curve is progressing
For no actual improvement in efficiency to be presented as a 10X yearly improvement since 2018, we'd need to currently be getting 100000000X more intensive models than we should be for what we're paying (a $1/Mtok model actually costs $100000000/Mtok). Presenting, say, a 9X actual yearly improvement as a 10X yearly improvement seems feasible, but for much beyond that I think the exponential just compounds too fast to reasonably fake.