diff --git a/README.md b/README.md index ae991eb..3e8786b 100755 --- a/README.md +++ b/README.md @@ -400,46 +400,18 @@ Options: ## Benchmarks -Run the comparison yourself: -```bash -python examples/compare_faiss_vs_leann.py -``` -| System | Storage | -|--------|---------| -| FAISS HNSW | 5.5 MB | -| LEANN | 0.5 MB | -| **Savings** | **91%** | +📊 **[Simple Example: Compare LEANN vs FAISS →](examples/compare_faiss_vs_leann.py)** +### Storage Comparison -Same dataset, same hardware, same embedding model. LEANN just works better. +| System | DPR (2.1M) | Wiki (60M) | Chat (400K) | Email (780K) | Browser (38K) | +|--------|-------------|------------|-------------|--------------|---------------| +| Traditional vector database (e.g., FAISS) | 3.8 GB | 201 GB | 1.8 GB | 2.4 GB | 130 MB | +| LEANN | 324 MB | 6 GB | 64 MB | 79 MB | 6.4 MB | +| Savings| 91% | 97% | 97% | 97% | 95% | -### Storage Usage Comparison - -| System | DPR (2.1M chunks) | RPJ-wiki (60M chunks) | Chat history (400K messages) | Apple emails (780K messages chunks) |Google Search History (38K entries) -|-----------------------|------------------|------------------------|-----------------------------|------------------------------|------------------------------| -| Traditional Vector DB(FAISS) | 3.8 GB | 201 GB | 1.8G | 2.4G |130.4 MB | -| **LEANN** | **324 MB** | **6 GB** | **64 MB** | **79 MB** |**6.4MB** | -| **Reduction** | **91% smaller** | **97% smaller** | **97% smaller** | **97% smaller** |**95% smaller** | - - - -*Benchmarks run on Apple M3 Pro 36 GB* - ## Reproduce Our Results ```bash