# AI Model API Price War Intensifies as OpenAI, Anthropic Cut Rates Against Chinese Competitors

> The price of running large language models is collapsing, and competition from China is a big reason why. On July 30 OpenAI cut the cost of its GPT-5.6 Luna model by 80 percent, to $0.20 per million input tokens, just three weeks after launch. Anthropic priced its new Opus 5 at roughly half its higher-end model, and Google trimmed Gemini Flash rates too. The moves look less like generosity and more like defense. The pressure is coming from Chinese labs. Models such as DeepSeek's V4 now deliver comparable coding output at a fraction of the cost, and on the popular OpenRouter marketplace Chinese models have grown from under 2 percent of token usage in late 2024 to more than half by June 2026. Reports put their share of some US enterprise workloads above 46 percent. For developers and companies, cheaper tokens are an obvious win. For the US labs that spent billions training frontier systems, the harder question is whether inference can stay profitable when a capable rival costs a hundredth as much.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: CNBC · Published Wednesday, August 19, 2026_

## Wortins' read

The price of running large language models is collapsing, and competition from China is a big reason why. On July 30 OpenAI cut the cost of its GPT-5.6 Luna model by 80 percent, to $0.20 per million input tokens, just three weeks after launch. Anthropic priced its new Opus 5 at roughly half its higher-end model, and Google trimmed Gemini Flash rates too. The moves look less like generosity and more like defense. The pressure is coming from Chinese labs. Models such as DeepSeek's V4 now deliver comparable coding output at a fraction of the cost, and on the popular OpenRouter marketplace Chinese models have grown from under 2 percent of token usage in late 2024 to more than half by June 2026. Reports put their share of some US enterprise workloads above 46 percent. For developers and companies, cheaper tokens are an obvious win. For the US labs that spent billions training frontier systems, the harder question is whether inference can stay profitable when a capable rival costs a hundredth as much.

## Source

[Read the full story at CNBC](https://www.cnbc.com/2026/07/30/open-ai-price-cut-gpt.html)

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