Yeah, real Jev got really weird, no benchmarking clause. Their Terms of Use (1(v)) and MCA (2.3(f)) both prohibit users from publishing "benchmarks or performance information about the Services". No major AI has it; we are back to Oracle-style legal.

Though Jev is original, it looks highly replicable.

▲ sodimel 4 hours ago | parent | next [-]

I'm working on something from a crappy laptop, those numbers from jev can totally be matched:

    Local Latency: 0.1813 seconds

	▲	toasty228 3 hours ago \| parent \| next [-]
		I can also run a 0.6b model on my phone faster than openai can run astra, it doesn't mean my model is useful.
	▲	cmrdporcupine 3 hours ago \| parent \| prev [-]
		and frankly for many of the kind of thing people probably want to use this for... you would want to run locally anyways. why even bother with a network hop? build a specialized engine which does the prefill->measure cycle on local GPU/TPU/NPU with a model fine tuned for your application (e.g. gaming NPCs, autonomous driving, agricultural intelligence, drone.. target... selection, whatever) the nice thing is that if you're skipping decode you're not as memory bandwidth bound.

▲ cmrdporcupine 3 hours ago | parent | prev [-]

There's also prior art. Or probably, anyways.

https://www.reddit.com/r/LocalLLaMA/comments/1wijo3e/i_liter...

Not only is it replicable as you say, things like it already exist(ed).

The important bit of course is in the actual implementation: a) models fine tuned to produce good results for these types of questions and b) runtimes optimized to do this quickly and at scale