Reasoning models are the same speed. They’re just post trained with RL to do CoT inside tags like <thinking></thinking> before a tag like <response></response>
There’s no difference in the inference implementation, parameter count, or speed.
There's a difference in the latency distribution between when you submit a query and you see the response, which is what the comment is (clumsily) asking about.
But yeah, there are a lot of factors, so it's hard to answer, and tokens/s isn't the right question.
So this demo is around 90 times faster than typical speeds for the same model at openrouter, and around 30 times faster than the absolute fastest option available (Groq).
AIs don't intrinsically know anything about themselves so they often give wrong answers to such questions. This can be fixed by putting info in the system prompt but they may consider it a waste of tokens since most usage doesn't benefit from that information.
It's running a very small, non-reasoning model at the moment. But more generally, almost all LLMs argue on the hardware/model they are/are on.
What would tokens/sec performance look like for a reasoning model? An order of magnitude slower?
Reasoning models are the same speed. They’re just post trained with RL to do CoT inside tags like <thinking></thinking> before a tag like <response></response>
There’s no difference in the inference implementation, parameter count, or speed.
There's a difference in the latency distribution between when you submit a query and you see the response, which is what the comment is (clumsily) asking about.
But yeah, there are a lot of factors, so it's hard to answer, and tokens/s isn't the right question.
Which model? Or how many active parameters?
Llama 3.1 8B model
So this demo is around 90 times faster than typical speeds for the same model at openrouter, and around 30 times faster than the absolute fastest option available (Groq).
https://taalas.com/h-content/uploads/2026/02/graph.png
https://xkcd.com/1162/
im assuming energy expenditure is substantially lower as well
AIs don't intrinsically know anything about themselves so they often give wrong answers to such questions. This can be fixed by putting info in the system prompt but they may consider it a waste of tokens since most usage doesn't benefit from that information.
That proves it's conscious!
(/s!)