Porting a Prompt From One Vendor's Idiom to Another on One Key: A Field-by-Field Diff

Why Prompts Are Vendor-Specific

Prompts tuned for one model often exploit that vendor's quirks: system role handling, special tokens, default temperature, and even formatting expectations. Porting to another vendor requires more than swapping endpoints—you need to translate the prompt's structure and assumptions.

The Field-by-Field Diff Method

A systematic diff helps you spot hidden dependencies. For each prompt component, compare how the source and target vendors interpret it.

System vs. User Role

• Some vendors treat the system message as a strong directive; others treat it as a weak hint.
• Check if the target vendor supports a system role at all—some legacy APIs only use user/assistant.
• Rewrite: If the target lacks a system role, merge system instructions into the first user message with clear delimiters.

Message Ordering and Few-Shot Examples

• Vendors differ in how they weight few-shot examples. Some expect examples interleaved; others prefer a block.
• Verify whether the target model benefits from labeled examples (e.g., "Input:" / "Output:").
• Rewrite: Reformat examples to match the target's documented style, and test if examples should be in the system or user message.

Special Tokens and Delimiters

• Models may rely on vendor-specific tokens like <|im_start|> or ###.
• Remove or replace these with plain text markers that the target model understands.
• Rewrite: Use descriptive labels such as [INSTRUCTION] and [EXAMPLE] instead of opaque tokens.

Temperature and Sampling Defaults

• Default temperature varies by vendor; a prompt tuned for 0.7 may be too random or too rigid elsewhere.
• Check if the target vendor uses topp, topk, or other sampling parameters differently.
• Rewrite: Explicitly set temperature and other sampling params in your API call to match the source behavior.

Output Format Instructions

• Vendors parse instructions like "respond in JSON" differently. Some need schema hints; others need examples.
• Rewrite: For the target vendor, add a concrete example of the desired output format.

Stop Sequences and Max Tokens

• Stop sequences are vendor-specific. A sequence that works on one may be ignored on another.
• Max token limits differ; ensure your prompt fits within the target's context window.
• Rewrite: Remove unnecessary stop sequences and adjust max tokens based on the target's limits.

Using a Third Model as a Checker

After rewriting, call a third model on the same API key with both the original and rewritten prompts. Ask it to compare the outputs and flag semantic differences. This neutral check catches drift you might miss.

• Use a model from a different family than both source and target.
• Prompt the checker with: "Compare these two responses for intent equivalence. List any differences."
• Iterate on the rewrite until the checker confirms alignment.

One Key, Many Models

On our platform, you can access multiple vendors with a single API key, making cross-model testing trivial. You pay official price × 1.3 per call, and key contributors earn official price × 1.1 (or × 1.2 for premium models) in USDC. This model encourages careful prompt engineering without hidden fees.

Summary Checklist

• Diff each field: system role, examples, tokens, sampling, output format, stops.
• Rewrite to match target vendor's documented idioms.
• Validate with a third model as a neutral checker.
• Use one key to streamline the process.