Comment by bitexploder
15 days ago
Gemini Flash 3.8 was heavily optimized for agentic coding. It is not an ignored use case. Flash 3.8 benches extremely well on agentic coding. It was very intentionally made good at coding. So was Argon. It is doing a lot of mission critical porting work for things like Rust. Does Google also build models for things other than coding? Yes. It has a lot of enterprise customers that need good general models too. IDK, I haven't seen anything convincing in Flash 3.8 or Argon that say "Google is ignoring coding" it just took a while to get there since Pro 3.1.
(Disclaimer: I work at teh Goog and spend... a lot of time with these models :)
Quota allocations are a massive decision that go all the way up to Sundar: what GDM organizationally wants (training) vs what GCP wants (Anthropic to throw it money hand over fist) are not aligned and a balance has to be made. For various reasons, GCP carved out a significant share; an eleven figure check over a quarter or two carries a real weight. This doesn't mean that GDM was starved for compute or that it wasn't making significant progress, but it absolutely could have had a more impressive H1 if given more resources.
Am I misreading the Argon numbers then? It leads on DeepSWE and Vibe Code Bench but lags on FrontierSWE and Terminal Bench. Should we be viewing Argon as a frontier coding model?