OpenAI o1 and Deepseek r1 have similar performance (o1 is a bit better at reasoning though you can see r1’s though process which you could argue trumps the competition). OpenAI o1 api cost: $60/million output tokens. Deepseek r1 api cost: $2.19/million output tokens.

https://api-docs.deepseek.com/quick_start/pricing https://platform.openai.com/docs/pricing

So basically I can get a ~lifetime supply of r1 tokens for… $20?

~lifespan = 2.27 billion seconds

r1 api can spit out 63 tokens per second

~143 billion lifetime tokens.

~$313 million for a lifetime supply of tokens.

$313 thousand not million which seems reasonable enough.

It's also open source

open weights you mean. People confuse open weights with open source.

Yeah it's a lot more efficient, it's also a very advanced model that answers questions in a multi-step way, like OpenAI-O1, it performs extremely well.

It isn't really hype for me.

For my use, it is better than $20 a month o1 and being able to see the chain of thought is absolutely incredible.

I have learned as much this week from seeing the chain of thought as I have from what it actually outputs.

> Is the only advantage the lower hardware requirements, thus cost?

Yes, but the keep thing is it performs nearly as well as models that are 100x as expensive.

The lower price drastically changes possible utility. For example, I've been rocking RooCode since R1 came out. R1 can do about 95% of the tasks Claude can, but at 1% of the cost. I might burn $10 to $20 per hour on Claude tokens. While spending less than $1 on Deepseek when doing the same task.