HomeDeepSeek API Input Cache Price Slashed to One-Tenth of Original
The leading domestic large language model, DeepSeek, recently announced a significant price cut, reducing the input cache hit price across all API series to one-tenth of the original rate. This move marks a new phase in cost management for domestic AI, aiming to attract more developers and businesses by offering exceptional value for money.
Core Price Cuts Address Industry Pain Points
This price adjustment covers the entire V4-Pro and V4-Flash series. The input cache price for V4-Pro has been reduced to 0.1 RMB per million tokens, and with a limited-time promotion, the actual payment is only 0.025 RMB. Compared to overseas competitors, the input cache price is just 1/700 of GPT-5.5 Pro, demonstrating strong market competitiveness.
In addition to cache hit scenarios, prices for cache miss and output scenarios have also been reduced to one-quarter of the original price. This pricing strategy precisely targets high-frequency use cases such as RAG knowledge bases, intelligent customer service, and document analysis, potentially cutting enterprise operational costs by over 90%.
DeepSeek's ability to significantly reduce prices stems from its self-developed sparse attention architecture. This technology supports ultra-long context processing of up to 160K, improving efficiency in handling long texts while effectively lowering underlying computing power consumption and storage costs.
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The leading domestic large language model, DeepSeek, recently announced a significant price cut, reducing the input cache hit price across all API series to one-tenth of the original rate. This move marks a new phase in cost management for domestic AI, aiming to attract more developers and businesses by offering exceptional value for money.
Core Price Cuts Address Industry Pain Points
This price adjustment covers the entire V4-Pro and V4-Flash series. The input cache price for V4-Pro has been reduced to 0.1 RMB per million tokens, and with a limited-time promotion, the actual payment is only 0.025 RMB. Compared to overseas competitors, the input cache price is just 1/700 of GPT-5.5 Pro, demonstrating strong market competitiveness.
In addition to cache hit scenarios, prices for cache miss and output scenarios have also been reduced to one-quarter of the original price. This pricing strategy precisely targets high-frequency use cases such as RAG knowledge bases, intelligent customer service, and document analysis, potentially cutting enterprise operational costs by over 90%.
DeepSeek's ability to significantly reduce prices stems from its self-developed sparse attention architecture. This technology supports ultra-long context processing of up to 160K, improving efficiency in handling long texts while effectively lowering underlying computing power consumption and storage costs.
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