Comment by simonw
17 days ago
> Who else has the sort of resources to train and run SOTA models at scale?
Google, OpenAI, Anthropic, Meta, Amazon, Reka AI, Alibaba (Qwen), 01 AI, Cohere, DeepSeek, Nvidia, Mistral, NexusFlow, Z.ai (GLM), xAI, Ai2, Princeton, Tencent, MiniMax, Moonshot (Kimi) and I've certainly missed some.
All of those organizations have trained what I'd class as a GPT-4+ level model.
> Google, OpenAI, Anthropic, Meta, Amazon, Reka AI, Alibaba (Qwen), 01 AI, Cohere, DeepSeek, Nvidia, Mistral, NexusFlow, Z.ai (GLM), xAI, Ai2, Princeton, Tencent, MiniMax, Moonshot (Kimi) and I've certainly missed some.
This is not a lot competition though. And you need to assume, that like other industries, mergers and acquisitions will happen over time which will put you in an increasingly worse position.
Kimi 2.5 is an opensource model with many providers https://openrouter.ai/moonshotai/kimi-k2.5/providers
Sure, opus and codex are significantly better. But price wise they cannot deviate too much from open models.
Especially if the open models are grounded against the digital twin.
Ah but I said "_... and running at scale_"
Of the list I gave you, at a guess:
Google, OpenAI, Anthropic, Meta, Amazon, Alibaba (Qwen), Nvidia, Mistral, xAI - and likely more of the Chinese labs but I don't know much about their size.
I guess where I was leading to is who owns the compute that runs those models. Mistral, for example, lists Microsoft and Google as subprocessors (1). Anthropic is (was?) running on GCP and AWS.
So, we have multiple providers, but for how long? They're all competing for the same hardware and the same energy, and it will naturally converge into an oligopoly. So, if competition doesn't set the floor, what does?
Local models? If you're not running the best model as fast as you can, then you'll be outpaced by someone that does.
1. https://trust.mistral.ai/subprocessors
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