Yes it is and has been for a very long time, it has been years now. Gemini 1.5 Pro is when LLM translations started significantly outperforming non-LLM machine translation, and that came out over 2 years ago.
Ever since then Google models have been the strongest at translation across the board, so it's no surprise Gemma 4 does well. Gemini 3 Flash is better at translation than any Claude or GPT model. OpenAI models have always been weakest at it, continuing to this day. It's quite interesting how these characteristics have stayed stable over time and many model versions.
I'm primarily talking about non-trivial language pairs, something like English<>Spanish is so "easy" now it's hard to distinguish the strong models.
I translate texts between Ukrainian, Russian and English dozens of times daily. The LLM translation is not only better, it's also refineable, you can chat with the AI to make changes to what you meant.
Proof they don't nerf it only after testing that the benchmarks there stay the same? So overall performance degrades but they isolate those benchmarks?
Fair enough. But, to be fair to them, they did have a falling out. There was a story on here how it went all the way to PG and then they asked Sam to leave (Something like that). I think saw it in a comment here, really don't remember.
if the project already has positive revenue then arguably the ability to capture new users is worth a lot, which requires acceptable performance even when a big traffic surge is happening (like a HN hug of attention)
if the scalability is in the number of "zero cost" projects to start, then 5 vs 15 is a 3x factor.
The bus supposedly only had Israelis. Israel attacked a neutral country Qatar with a missile to eliminate some supposed enemy agent to a civilian building, so I don't think they have any problems with this.
