Benchmark notes

Notes on benchmarking results

The key benchmarking results are:

• Percent completed correctly - Measures what percentage of the coding tasks that the LLM completed successfully. To complete a task, the LLM must solve the programming assignment and edit the code to implement that solution.
• Percent using correct edit format - Measures the percent of coding tasks where the LLM complied with the edit format specified in the system prompt. If the LLM makes edit mistakes, aider will give it feedback and ask for a fixed copy of the edit. The best models can reliably conform to the edit format, without making errors.

Notes on the edit format

Aider uses different “edit formats” to collect code edits from different LLMs. The “whole” format is the easiest for an LLM to use, but it uses a lot of tokens and may limit how large a file can be edited. Models which can use one of the diff formats are much more efficient, using far fewer tokens. Models that use a diff-like format are able to edit larger files with less cost and without hitting token limits.

Aider is configured to use the best edit format for the popular OpenAI and Anthropic models and the other models recommended on the LLM page. For lesser known models aider will default to using the “whole” editing format since it is the easiest format for an LLM to use.