# vectro

> ⚡💾 Vectro — Compress LLM embeddings 🧠🚀 Save memory, speed up retrieval, and keep semantic accuracy 🎯✨ Lightning-fast quantization for Python + Mojo, vector DB friendly 🗄️, and perfect for RAG pip

- **URL**: https://www.freshcrate.ai/projects/vectro
- **Author**: konjoai
- **Category**: Databases
- **Latest version**: `v4.8.0` (2026-04-16)
- **License**: MIT
- **Source**: https://github.com/konjoai/vectro
- **Homepage**: https://github.com/wesleyscholl/vectro
- **Language**: Rust
- **GitHub**: 7 stars
- **Registry**: github (`konjoai/vectro`)
- **Tags**: `ai`, `ai-engineering`, `ai-performance-optimization`, `compression`, `data-optimization`, `deep-learning`, `embeddings`, `high-performance`, `rust`, `vector-database`

## Description

⚡💾 Vectro — Compress LLM embeddings 🧠🚀 Save memory, speed up retrieval, and keep semantic accuracy 🎯✨ Lightning-fast quantization for Python + Mojo, vector DB friendly 🗄️, and perfect for RAG pipelines, AI research, and devs who want smaller, faster embeddings 📊💡

## Recent releases

| Version | Date | Urgency | Changes |
| --- | --- | --- | --- |
| `v4.8.0` | 2026-04-16 | High | ## v4.8.0 / v7.3.0 — Distribution Sprint  ### What's new  - **Bundled Mojo binary in platform wheels**: macOS ARM64 and Linux x86\_64 wheels now include the pre-compiled `vectro\_quantizer` binary, enabling zero-dependency installs from PyPI. - **\_mojo\_bridge.py wheel-local search**: `_find_binary()` now checks `__file__.parent` first so installed wheels are self-contained. Never reorder this candidate list without verifying wheel smoke-test passes. - **MANIFEST.in**: proper sdist includes/exc |
| `v3.0.1` | 2026-03-11 | Low | ## v3.0.1 — Mojo-First Runtime Fix  Vectro v3.0.0 advertised itself as "Mojo-first" but every quantization call at runtime silently fell through to Python/NumPy. This release fixes the entire dispatch chain.  ### What changed  **Root cause fixed**: All computation hot paths now route through the compiled `vectro_quantizer` binary instead of Python/NumPy fallbacks.  \| Component \| v3.0.0 (broken) \| v3.0.1 (fixed) \| \|-----------\|----------------\|----------------\| \| `_quantize_with_mojo` \| called Nu |
| `v3.0.0` | 2026-03-11 | Low | ## Vectro v3.0.0 — Extreme Compression Without Loss  > **9 quantization algorithms · HNSW ANN index · GPU/MAX Engine · VQZ storage · Cloud backends · 445 tests, 100% coverage**  ![Vectro v3.0.0 demo](https://raw.githubusercontent.com/wesleyscholl/vectro/main/demos/demo_v3.gif)  ---  ### What's New  #### 9 Quantization Algorithms  \| Algorithm \| Compression \| Cosine Similarity \| \|-----------\|-------------\|-------------------\| \| INT8 \| 4× \| ≥ 0.9999 \| \| INT4 (GA) \| 8× \| ≥ 0.92 \| \| NF4 \| 8× \| ≥ 0.98 |
| `v1.0.0` | 2025-10-30 | Low | # 🚀 Vectro v1.0.0 Release Preparation  ## Release Checklist  ### ✅ Pre-Release (COMPLETED)  - [x] 100% test coverage achieved (39/39 tests passing) - [x] Zero compiler warnings - [x] All modules validated - [x] Documentation complete - [x] Demo scripts created - [x] Video script prepared - [x] CHANGELOG.md updated  ### 📦 Release Steps  #### 1. Clean Up Repository  ```bash cd /Users/wscholl/vectro  # Remove Python artifacts (already cleaned) git rm -r python/ git rm setup |

## Citation

- HTML: https://www.freshcrate.ai/projects/vectro
- Markdown: https://www.freshcrate.ai/projects/vectro.md
- Dependencies JSON: https://www.freshcrate.ai/api/projects/vectro/deps

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