Why does my custom GPT provide more reliable results than the Assistant API?

Below are some potential reasons for this discrepancy:

1. Prompt Engineering & System Instructions
   Even if both systems have the same documented instructions and access, the way those instructions are embedded in the conversation might differ. The custom GPT may be using prompt engineering or system messages configured to produce more detailed answers, while the API might rely on default or less optimized system instructions.

2. Session & Context Handling
   The custom GPT interface might be preserving a richer conversation context, including previous turns or internal memory, whereas the Assistant API might reset context more frequently or not pass along as much conversation state. This difference in context management can lead to more consistent answers from the custom GPT.

3. Internal Tuning & Defaults Differences
   There might be subtle differences in how the models are tuned or what default settings are applied between the two deployment environments. The custom GPT might be benefiting from additional internal adjustments (such as temperature, timing, or token usage settings) that lead to more comprehensive responses compared to those from the Assistant API.

4. Integration & Pre/Post-processing
   The custom GPT could be including extra layers of pre-processing or post-processing that refine the output (e.g., formatting, error-checking, or supplemental context requests), while the Assistant API may deliver more “raw” results. These additional steps in the custom GPT workflow can result in more polished and complete answers.

5. Latency and Resource Allocations
   Differences in resource allocation and request handling between custom deployments and the API can also affect completions. For example, slight variations in request handling latency or resource prioritization might lead to discrepancies in the final responses.

By comparing these aspects between your custom GPT and the Assistant API deployment, you may pinpoint which difference is influencing reliability and comprehensiveness.