Does Switching Models Change What Gets Logged? A Per-Vendor Retention Walkthrough
When you send a prompt through an LLM aggregator, the request may be routed to different model vendors, each with distinct data retention practices. This article explains how to assess what gets logged per vendor, based on publicly available policies, and how to make informed choices for privacy-sensitive workloads.
Why Retention Varies by Model Vendor
When you call a model through an aggregator, your request is forwarded to the underlying vendor (e.g., Anthropic, OpenAI, DeepSeek, Qwen, GLM, Kimi). Each vendor has its own data retention policy, which determines how long your prompts and completions are stored and for what purposes. The aggregator itself may also log requests, but the primary retention risk lies with the model provider.
Understanding these differences is crucial for applications handling sensitive data. Even if the aggregator is privacy-conscious, the vendor's policy applies once your data reaches their servers.
Key Factors in Vendor Retention Policies
Retention policies typically address:
- Storage duration: How long inputs and outputs are kept (e.g., 30 days, indefinitely).
- Purpose of retention: Whether data is used for abuse monitoring, service improvement, or model training.
- User controls: Options to opt out of training or request deletion.
- Data location: Where data is stored and processed (relevant for cross-border transfers).
Not all vendors publish detailed policies, and some may update them over time. Always refer to the vendor's official documentation for the most current information.
A Hypothetical Walkthrough: Same Prompt, Different Backends
Imagine you send the prompt "Summarize this customer feedback" through an aggregator that routes to six different backends. Here's what might happen at each step:
- Aggregator logging: The aggregator records the request metadata (timestamp, model, token counts) and may store the prompt/completion for billing and debugging. Retention here is governed by the aggregator's policy.
- Vendor processing: The request is sent to the chosen vendor. The vendor logs the request according to its own retention rules.
- Retention differences: Vendor A might retain data for 30 days for abuse monitoring; Vendor B might retain indefinitely unless you opt out; Vendor C might not retain at all for API users. These differences mean the same prompt has different privacy implications depending on the backend.
Assessing Retention for Your Use Case
To make informed decisions:
- Read vendor policies: Look for sections on "data retention," "privacy," or "trust center." Check if they differentiate between consumer and API offerings.
- Check opt-out mechanisms: Some vendors allow enterprises to disable logging or request zero data retention.
- Consider data sensitivity: For highly sensitive data, choose vendors with minimal retention and strong user controls.
- Use aggregator features: Some aggregators provide transparency reports or allow you to restrict routing to specific vendors.
Practical Steps for Developers
When building with an aggregator:
- Document your data flows: Map which vendors receive what data and under which policies.
- Implement data minimization: Avoid sending unnecessary sensitive information in prompts.
- Monitor policy changes: Vendor retention policies can change; subscribe to updates.
- Leverage aggregator controls: If available, use features to exclude vendors with unacceptable retention.
Conclusion
Switching models does change what gets logged because each vendor applies its own retention policy. While the aggregator adds a layer, the ultimate retention is determined by the model provider. By understanding these differences and taking steps to align vendor policies with your privacy requirements, you can use aggregators effectively without compromising on data governance.