It's likely no coindicence that they only show "median latency", not how latency scales with input size.
For small inputs Jev is slow, but its latency curve is very flat. Fine-tuning a decently-sized llm (like this 27B model) gives you something that's faster on small input sizes, but even with moderate contexts quickly becomes much slower than Jev. Characterizing it as "faster than Jev" is very misleading, unless you know all your questions have tiny context (less than 1k tokens or so)
yes. Jev is text-only, while Clef and a lot of the other alternatives are fine-tunes of multi-modal models, so you get image-input basically for free. Actual decision quality based on images is a bit up in the air though, I am not aware of any benchmarks testing that
For small inputs Jev is slow, but its latency curve is very flat. Fine-tuning a decently-sized llm (like this 27B model) gives you something that's faster on small input sizes, but even with moderate contexts quickly becomes much slower than Jev. Characterizing it as "faster than Jev" is very misleading, unless you know all your questions have tiny context (less than 1k tokens or so)