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Baidu Wenxin Large Model Cost Optimization Analysis Report

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January 5, 2026

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Baidu Wenxin Large Model Cost Optimization Analysis Report

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According to the information found,

the training cost of the Wenxin Large Model has indeed shown a significant downward trend
. Here is the detailed analysis:

Core Cost Reduction Data

According to data disclosed at Baidu’s April 2024 Create AI Developer Conference [1]:

  • Algorithm training efficiency increased to 5.1 times that of a year ago
  • Average weekly training efficiency reached 98.8%
  • Inference performance increased by 105 times
  • Cost decreased by 99%
Cost Optimization Drivers
1. Technical Architecture Optimization

Baidu’s launched “Wanyuan” Intelligent Computing Operating System has achieved significant results in cost control [1]:

  • ModelBuilder provides model routing services
    , selecting models with appropriate parameter scales to form optimal solutions,
    reducing inference costs by 30%
  • The Baige AI heterogeneous computing platform is compatible with chips from different manufacturers,
    with mixed training efficiency of 97%/95% for 100 cards/1000 cards
2. Model Architecture Innovation

The Wenxin Large Model uses multiple technologies to reduce operating costs [1]:

  • Mixture of Experts (MoE) model
    : Does not rely on a single model; mixes large and small models according to scenario matching
  • Lightweight model strategy
    : Lightweight models such as ERNIE Speed, Lite, and Tiny reduce the demand for computing resources
3. Scale Effect Emerges

With the explosive growth in API calls, costs have been further diluted [3]:

  • The number of Wenxin Large Model API calls increased from 50 million in 2023 to
    1.65 billion in 2024
  • The number of Wenxin Yiyan users exceeded 200 million, with daily API calls exceeding 200 million
Market Background

The large model industry as a whole has entered a cost reduction cycle [2]:

  • At the end of 2024, Alibaba announced a price reduction of more than 80% for its large models
  • Baidu Intelligent Cloud’s AI-related revenue grew by nearly 300%, and the scale effect further reduced marginal costs
  • Baidu expects the cost of basic models to continue to
    decline steadily
    , lowering the threshold for use
Conclusion

The training cost of the Wenxin Large Model shows a significant downward trend
, mainly due to the superposition of three factors: technical architecture optimization, model efficiency improvement, and scale effect. This trend will promote the further popularization of large model applications, which is in line with industry development laws.


References:

[1] BOCOM International - 2024 Baidu Create AI Conference Minutes (https://pdf.dfcfw.com/pdf/H3_AP202404191630636523_1.pdf)
[2] 36Kr - In 2025, Are “Large Model Price Wars” No Longer Afraid of Losing Money? (https://m.36kr.com/p/3125094788382464)
[3] Wall Street News - Baidu Intelligent Cloud’s AI-related Revenue Grew by Nearly 300% in 2024 (https://wallstreetcn.com/articles/3741365)

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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.