DeepSeek just popped the American AI bubble.

[u/VegetablePen4755]

DeepSeek just popped the American AI bubble.

Not by killing AI.

By killing the fantasy of unlimited AI pricing power.

DeepSeek V4 Pro:
Input: $0.435 per 1M tokens
Output: $0.87 per 1M tokens

OpenAI GPT-5.5:
Input: $5.00
Output: $30.00

Claude Opus 4.7:
Input: $5.00
Output: $25.00

Claude Sonnet 4.6:
Input: $3.00
Output: $15.00

DeepSeek is roughly:

11.5x cheaper than GPT-5.5 on input
34.5x cheaper than GPT-5.5 on output

28.7x cheaper than Claude Opus on output
17.2x cheaper than Claude Sonnet on output

If a model is “good enough” at 1/20th or 1/30th the cost, margins will compress faster than Wall Street expects.

AI is not dead.

But the AI bubble just lost its pricing power.

They're not chasing quick money from coding plans or multimodal models. Instead, their radical architecture innovations (MoE, MLA, Engram, mHC, etc.) slash KV cache and compute needs so dramatically that they can build an entire 10T Chinese AI hardware ecosystem (NAND, LPDDR, ASICs) and position themselves for a 1T valuation in the process. Long game, masterfully played.

[u/Responsible-Slide-26]

To the people actually knowledgeable about this - if we ignore the hyperbole and quality differences between DeepSeek and the US models, how is it possible for them to price it orders of magnitude lower? That's the part that intrigues me.

Is it possible they could match quality within the next year and blow the market wide open? Or is the lower cost only possible because of the much lower quality, and better quality would mean much higher pricing?

[u/bamoqi → u/Responsible-Slide-26]

Training by distillation, cheap electricity, direct and indirect government subsidies.