DeepSeek has drastically lowered the prices of its latest AI model, V4-Pro. The Chinese AI developer is cutting rates by 75 percent. This comes just a few weeks after the new V4 series was introduced. This further increases the pressure on competitors such as OpenAI, Anthropic, and Google.
The price reduction applies to both input and output tokens. While using V4-Pro previously cost up to $3.48 per million output tokens, that rate is dropping to a maximum of $0.87. The lowest price tiers are also dropping significantly. According to DeepSeek, the adjusted rates will largely remain in place even after the temporary discount period ends.
Analysts say the price cut primarily demonstrates how rapidly the costs of AI inference are falling. Sanchit Vir Gogia of Greyhound Research states in InfoWorld that DeepSeek has succeeded in making the model more efficient, requiring less computing power and memory for complex AI tasks with large context windows. The lower prices would therefore stem from technological optimizations rather than a temporary marketing campaign.
Pressure on OpenAI and Anthropic
DeepSeek unveiled its V4 models last month as the successor to the earlier R1 reasoning model. Like previous versions, the new models are also available as open source. This allows developers to run them locally and customize them for their own applications.
According to Neil Shah of Counterpoint Research, DeepSeek has largely closed the performance gap with Western AI models in certain areas with V4-Pro. He points, among other things, to performance in complex computational tasks and reasoning tasks. At the same time, he notes that DeepSeek still lags behind internationally in areas such as support, ecosystem integrations, and adoption within major cloud platforms.
The combination of relatively high performance and low operating costs can be particularly attractive to companies looking to scale up AI projects. Many organizations are currently facing high operational costs as AI applications are rolled out more widely.
Inference Costs a Major Bottleneck
According to market analysts, inference costs have now become a major bottleneck for enterprise AI. In recent years, companies have discovered that not only model usage but also retrieval, orchestration, and infrastructure place a heavy burden on the total costs of AI projects.
Amit Jaju of Ankura Consulting says that the benefits of DeepSeek are particularly evident when organizations run the model on their own infrastructure. In that scenario, costs can drop significantly, making applications such as permanent AI co-pilots, large-scale document analysis, code generation, and multi-agent workflows more economically viable.
However, the ultimate benefit depends on how companies deploy DeepSeek. When organizations use external providers or cloud platforms, additional costs can partially offset the savings.