This week, a Reddit post floated a bold hypothesis that sparked discussion in our editorial room: if Google launches a 120B-parameter open-source multimodal large model, it could directly derail the IPO (initial public offering) plans of OpenAI and Anthropic — two companies with a combined valuation of $500 billion. This isn't a technical issue — it's the "trust deficit" Western enterprises have toward Chinese open-source models.

What This Is

Poster EducationalCicada's core logic is simple: the open-source LLM ecosystem (where code and weights are fully public and freely downloadable for deployment) is eating into closed-source giants, and the strongest open-source models right now — Alibaba's Qwen and DeepSeek — both come from China. But due to compliance, data security, and brand trust considerations, many Western enterprises refuse to use Chinese models. If Google leverages DeepMind's research muscle to ship a top-tier open-source flagship at 120B (120 billion) parameters, it could simultaneously fill this market gap and torpedo OAI and Anthropic's IPO prospects.

Industry View

Supporters say the business logic holds. Qwen, DeepSeek, and other Chinese open-source models perform at near GPT-4 levels and are completely free, already threatening the tens of billions in annual API (pay-per-call) revenue at OpenAI and Anthropic. Google has both the research capability (the Gemini team) and enterprise distribution (Google Cloud) — a flagship open-source model could capture Western enterprise customers being siphoned off by the Chinese open-source ecosystem in one move.

But counterarguments are equally sharp. First, Google's own monetization path conflicts with open source — Vertex AI's API revenue would be cannibalized immediately by its own open-source model. Second, a 120B dense model (where all parameters participate in every inference) demands enormous VRAM, which ordinary enterprises simply can't run; MoE (Mixture-of-Experts) architectures (like DeepSeek and Mixtral) are far more practical. Third, "Western firms don't want Chinese models" is fundamentally a compliance and geopolitics issue, not an open-vs-closed one — once European data regulation tightens further, all third-party models will be affected.

Impact on Regular People

For enterprise IT: the 2025 enterprise LLM selection menu could expand from a three-way race (Qwen, Llama, DeepSeek) to a four-way battle, raising procurement bargaining power and lowering overall costs.

For individual careers: closed-source API price wars intensify, the marginal cost of using AI tools for writing, translation, and coding continues to fall, and AI collaboration skills become baseline job requirements.

For the consumer market: the model capabilities embedded in phone assistants, smart customer service, and in-car AI will collectively improve as the open-source ecosystem matures, but ordinary consumers won't perceive meaningful change in the short term.