Isn't what the leading labs are currently chasing after is not pretraining and massive parameters but enriched and deep fine tuning and post training for agentic tasks/coding? MoE with just new post training paradigms lets smaller models perform quite well, and much more pragmatic to scale inference with. Given that, this choice seems super odd, as the frontier labs seem to stay neck and neck, and I don't even see Grok being used in any benchmarks because of how poorly it performs