Yes, New Relic AI monitoring can track token usage for cost optimization in DeepSeek applications. This capability is part of New Relic's comprehensive observability solution designed specifically for monitoring DeepSeek, a generative AI (GenAI) model. By integrating New Relic's AI monitoring with DeepSeek, businesses can gain full visibility into their AI applications, including key metrics such as token usage, throughput, latency, and costs. This integration supports DeepSeek and DeepSeek on Microsoft Azure AI Foundry, providing a simplified setup with enhanced data security[1][2][4].
Tracking Token Usage for Cost Optimization:
New Relic's AI monitoring allows businesses to track token usage, which is crucial for managing AI development costs. Token usage is a significant factor in determining the cost of running AI models, as many AI services charge based on the number of tokens processed. By monitoring token usage, companies can optimize their AI costs by identifying areas where token usage can be reduced without compromising performance. This capability also enables businesses to make informed decisions about model selection and deployment, ensuring that they choose the most cost-effective models for their applications[5][8].
Benefits of New Relic AI Monitoring for DeepSeek:
1. Reliability Assurance and Quality: New Relic provides full visibility into DeepSeek-powered AI application performance, allowing businesses to quickly identify and resolve issues. This ensures that applications run reliably and maintain high quality[1][4].
2. Cost Optimization: By tracking token usage and other cost-related metrics, businesses can optimize their AI development costs. This is particularly important when using cost-effective models like DeepSeek, which offer advanced reasoning capabilities at a lower cost[1][5].
3. Confidence in Model Switching: New Relic's model comparison features allow businesses to assess the impact of switching between AI models on performance and costs. This helps in making informed decisions about which models to deploy and when to switch, ensuring that the chosen models align with business needs and budget constraints[4][5].
4. Accelerated Innovation: The combination of New Relic's AI monitoring and DeepSeek's open models accelerates AI innovation and deployment. This enables businesses to adopt and optimize AI technologies more efficiently, driving faster innovation and maintaining a competitive edge in the market[1][7].
Overall, New Relic's AI monitoring for DeepSeek applications provides a robust solution for optimizing AI costs through token usage tracking, among other benefits, helping businesses navigate the complex AI landscape effectively.
Citations:
[1] https://theexchangeasia.com/new-relic-unveils-first-ever-ai-observability-for-deepseek/
[2] https://www.dqchannels.com/news/new-relic-introduces-observability-solution-for-deepseek-ai-monitoring-8689063
[3] https://docs.newrelic.com/docs/ai-monitoring/explore-ai-data/view-ai-responses/
[4] https://newrelic.com/press-release/20250203
[5] https://ecommercenews.com.au/story/new-relic-unveils-ai-monitoring-for-deepseek-applications
[6] https://blog.devops.dev/aws-observability-tools-for-bedrock-large-language-models-d732363993fd
[7] https://www.computerweekly.com/news/366618774/New-Relic-extends-observability-to-DeepSeek
[8] https://newrelic.com/blog/how-to-relic/deploy-deepseek-models-locally-and-monitor-with-new-relic-ai-monitoring