Worked on expanding the capabilities of the embeddings-benchmark/mteb repository by integrating the infly/inf-retriever-v1 model into the benchmarking suite. Focused on model integration and metadata management, the work involved creating a dedicated Python module to register the new model and updating the benchmark’s overview logic to ensure proper recognition and evaluation support. This addition broadened the benchmark’s coverage, allowing users to assess the latest retriever model for production use cases. No major bugs were addressed during this period, as the primary effort centered on feature delivery and establishing a foundation for future model support within the benchmarking framework.