Claude code is 60-80 tps, codex varies by model but mostly 40-50 tps.

200-250 is the rate I've seen my context window fill up during longer tasks with Claude. The 40-80 figure is what Google's AI mode says, but I don't know where it got that from.

I've been messing around low computing power hardware to run models locally and to me 100 is already plenty fast. You most likely won't notice a huge difference between 184 and 250, unless you're running some serious multi-age agent circus.

Another data point: I got 94.74 tokens/s on an M4 Pro Mac mini 64GB with the simonw prompt "Generate an SVG of a pelican riding a bicycle". TTFT was 0.37s. The model thought for 40.75s before answering.

(The resulting pelican was underwhelming.)

>How many tokens/s do you need for a coding agent to feel like Claude or codex?

it's kind of a loaded question, this model gets a lot of tok/s but reasoning is forced on; the time-to-answer is really a combination of things like "how much does this thing want to over-reason" and "how much does this thing like tool use?" .

AFAIU prefill speed makes a bigger difference in agentic coding workflows as the harness likely spends more time reading than creating new code. Qwen in particular spends a lot of time reasoning so it does make a larger impact there

I’d say only 65