> Different models have different strengths and weaknesses
I would add different errors as well. Here are two examples where GPT-4o and Claude 3.5 Sonnet cannot tell that "GitHub" is spelled like "GitHub".
GPT-4o: https://app.gitsense.com/?doc=6c9bada92&model=GPT-4o&samples...
Claude 3.5 Sonnet: https://app.gitsense.com/?doc=905f4a9af74c25f&model=Claude+3...
I don't think there will be one model that will rule them all, unless there is a breakthrough. If things continue on the same path, I think AWS, Microsoft and Google will be the last ones standing, since they can provide models from all the major LLM players.
AWS having customers using its own model probably improves AWS's margins, but having multiple models available (e.g. Anthropic's) improves their ability to capture market share. To date, AWS's efforts (e.g. Q, CodeWhisperer) have not met with universal praise. So for at least for the present, it makes sense to bring customers to AWS to "do AI" whether they're using AWS's models or someone else's.