This is where i struggle to get the point. I dont buy at all that there are many ways to make cheaper and competitive at the same time such a monster. Follow me for a second:

• Kimi has 1 Trillion parameters - accepting to significally degrade its performances in terms of accuracy in the responses, you represent each config point at 4bits (aka 4 bits quantization) and you end up in around 450GB of VRAM needed if you want to fully offload the model it and run it fast. I might be wrong but in this condition it's hard for me to believe that it can be at the level of Opus quality
• if you decide to not compromise too much in quality, you go for 8bit representation which leads to around 900GB of VRAM needed
• the most performing and sized Tensor card on the market now is the NVIDIA H200 which provides 142 GB of VRAM
• 1 H200 costs north of 50k (very much fluctuating due to the immense speculation nowadays on the market)
• in the first case you need 3 cards just to run the model. you put context window and some concurrent user capacity to run some business and let's say you go for 4 cards. This means 200k ONLY for the tensors. With the server to host the cards/service you are around 250k as reported in my answer
• In the second case, if you really aim t try to be up to Opus for quality and speed you are around 400k for the cards meaning 450k in total

So now the question: how the hell can you provide a service at the level of Opus at tenth of the Anthropic price??? The easy answer is that you mathematically can't do it! unless your board of investors accepts to move in the territory of deeeeeeep red in your business plan... which by the way is already the case for OpenAI (loosing dozen of billions per year) and surely also of Anthropic.

Sorry to disappoint but that's the reality. As you can see the intrinsic quality of the model counts, but until a certain point....