update benchmard section
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42
README.md
42
README.md
@@ -400,46 +400,18 @@ Options:
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## Benchmarks
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Run the comparison yourself:
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```bash
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python examples/compare_faiss_vs_leann.py
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```
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| System | Storage |
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|--------|---------|
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| FAISS HNSW | 5.5 MB |
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| LEANN | 0.5 MB |
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| **Savings** | **91%** |
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📊 **[Simple Example: Compare LEANN vs FAISS →](examples/compare_faiss_vs_leann.py)**
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### Storage Comparison
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Same dataset, same hardware, same embedding model. LEANN just works better.
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| System | DPR (2.1M) | Wiki (60M) | Chat (400K) | Email (780K) | Browser (38K) |
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|--------|-------------|------------|-------------|--------------|---------------|
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| Traditional vector database (e.g., FAISS) | 3.8 GB | 201 GB | 1.8 GB | 2.4 GB | 130 MB |
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| LEANN | 324 MB | 6 GB | 64 MB | 79 MB | 6.4 MB |
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| Savings| 91% | 97% | 97% | 97% | 95% |
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### Storage Usage Comparison
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| System | DPR (2.1M chunks) | RPJ-wiki (60M chunks) | Chat history (400K messages) | Apple emails (780K messages chunks) |Google Search History (38K entries)
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|-----------------------|------------------|------------------------|-----------------------------|------------------------------|------------------------------|
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| Traditional Vector DB(FAISS) | 3.8 GB | 201 GB | 1.8G | 2.4G |130.4 MB |
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| **LEANN** | **324 MB** | **6 GB** | **64 MB** | **79 MB** |**6.4MB** |
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| **Reduction** | **91% smaller** | **97% smaller** | **97% smaller** | **97% smaller** |**95% smaller** |
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<!-- ### Memory Usage Comparison
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| System j | DPR(2M docs) | RPJ-wiki(60M docs) | Chat history() |
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| --------------------- | ---------------- | ---------------- | ---------------- |
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| Traditional Vector DB(LLamaindex faiss) | x GB | x GB | x GB |
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| **Leann** | **xx MB** | **x GB** | **x GB** |
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| **Reduction** | **x%** | **x%** | **x%** |
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### Query Performance of LEANN
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| Backend | Index Size | Query Time | Recall@3 |
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| ------------------- | ---------- | ---------- | --------- |
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| DiskANN | 1M docs | xms | 0.95 |
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| HNSW | 1M docs | xms | 0.95 | -->
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*Benchmarks run on Apple M3 Pro 36 GB*
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## Reproduce Our Results
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```bash
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