--- title: "fastembed-rs vs fastembed" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/anush008-fastembed-rs-vs-qdrant-fastembed" tools: ["anush008-fastembed-rs", "qdrant-fastembed"] --- # fastembed-rs vs fastembed *GraphCanon updated Aug 22, 2026* ## Verdict Pick fastembed-rs if fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes; pick fastembed if fastembed is a lightweight and efficient Python library for creating state-of-the-art embeddings. [fastembed-rs](https://docs.rs/fastembed) reports 992 GitHub stars, 136 forks, and 1 open issues, last pushed Aug 16, 2026. [fastembed](https://qdrant.github.io/fastembed/) has 3.2k stars, 231 forks, and 111 open issues, last pushed Aug 19, 2026. Figures are from public GitHub metadata via [fastembed-rs's repository](https://github.com/Anush008/fastembed-rs) and [fastembed's repository](https://github.com/qdrant/fastembed). | | [fastembed-rs](/tools/anush008-fastembed-rs.md) | [fastembed](/tools/qdrant-fastembed.md) | | --- | --- | --- | | Tagline | Rust library for generating vector embeddings and reranking locally. | Fast, Accurate, Lightweight Python library for creating state-of-the-art embeddings | | Stars | 992 | 3,158 | | Forks | 136 | 231 | | Open issues | 1 | 111 | | Language | Rust | Python | | Adopt for | fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes. | Fastembed is a lightweight and efficient Python library for creating state-of-the-art embeddings. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 License | | Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [fastembed-rs](/tools/anush008-fastembed-rs.md) | [fastembed](/tools/qdrant-fastembed.md) | | --- | --- | --- | | Days since push | 6d | 2d | | Open issues (now) | 1 | 111 | | Stars delta | +20 (30d) | +55 (30d) | | Open issues delta | -2 (30d) | -26 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/anush008-fastembed-rs/trust.md) | [trust report](/tools/qdrant-fastembed/trust.md) | ## Decision facts: fastembed-rs - **Adopt for:** fastembed-rs is a Rust-based library that specializes in generating vector embeddings and performing local reranking to improve retrieval-augmented generation processes. ## Decision facts: fastembed - **Requirements:** Does not require Docker, making the setup straightforward for Python environments. - **Adopt for:** Fastembed is a lightweight and efficient Python library for creating state-of-the-art embeddings. - **License detail:** Apache-2.0 License ## Choose when ### Choose fastembed-rs if… - fastembed-rs is primarily Rust; fastembed is Python. - Tags unique to fastembed-rs: fastembed, reranker, reranking, retrieval. - When you seek high-performance embedding generation within an application written in Rust. ### Choose fastembed if… - fastembed is primarily Python; fastembed-rs is Rust. - Requirements: Does not require Docker, making the setup straightforward for Python environments.. - Tags unique to fastembed: openai, retrieval-augmented-generation. - When you need to generate high-quality embeddings quickly in Python. ## When NOT to use fastembed-rs - Avoid if your project demands integration with languages other than Rust, as the tool does not offer bindings for other programming languages. - Not recommended when the primary focus is on distributed or cloud-based embedding services, as fastembed-rs focuses specifically on local processing. ## When NOT to use fastembed - If your project is not using Python, as Fastembed does not offer support for other programming languages directly. - In scenarios demanding heavy customization or fine-tuning at a lower level than what Fastembed provides out-of-the-box. Consider alternatives that may offer more flexibility. ## Common questions ### What is the difference between fastembed-rs and fastembed? fastembed-rs: Rust library for generating vector embeddings and reranking locally.. fastembed: Fast, Accurate, Lightweight Python library for creating state-of-the-art embeddings. See the comparison table for live GitHub stats and shared categories. ### When should I choose fastembed-rs over fastembed? Choose fastembed-rs over fastembed when fastembed-rs is primarily Rust; fastembed is Python; Tags unique to fastembed-rs: fastembed, reranker, reranking, retrieval; When you seek high-performance embedding generation within an application written in Rust. ### When should I choose fastembed over fastembed-rs? Choose fastembed over fastembed-rs when fastembed is primarily Python; fastembed-rs is Rust; Requirements: Does not require Docker, making the setup straightforward for Python environments.; Tags unique to fastembed: openai, retrieval-augmented-generation; When you need to generate high-quality embeddings quickly in Python. ### When should I avoid fastembed-rs? Avoid if your project demands integration with languages other than Rust, as the tool does not offer bindings for other programming languages. Not recommended when the primary focus is on distributed or cloud-based embedding services, as fastembed-rs focuses specifically on local processing. ### When should I avoid fastembed? If your project is not using Python, as Fastembed does not offer support for other programming languages directly. In scenarios demanding heavy customization or fine-tuning at a lower level than what Fastembed provides out-of-the-box. Consider alternatives that may offer more flexibility. ### Is fastembed-rs or fastembed more popular on GitHub? fastembed has more GitHub stars (3,158 vs 992). Stars measure visibility, not whether either tool fits your constraints. ### Are fastembed-rs and fastembed open source? Yes - both are open-source projects on GitHub (fastembed-rs: Apache-2.0, fastembed: Apache-2.0). ### Where can I find alternatives to fastembed-rs or fastembed? GraphCanon lists graph-backed alternatives at [fastembed-rs alternatives](/tools/anush008-fastembed-rs/alternatives) and [fastembed alternatives](/tools/qdrant-fastembed/alternatives) ([fastembed-rs markdown twin](/tools/anush008-fastembed-rs/alternatives.md), [fastembed markdown twin](/tools/qdrant-fastembed/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/anush008-fastembed-rs-vs-qdrant-fastembed.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, fastembed-rs or fastembed? fastembed-rs: Very active. fastembed: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for fastembed-rs and fastembed? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [fastembed-rs trust report](/tools/anush008-fastembed-rs/trust); [fastembed trust report](/tools/qdrant-fastembed/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=anush008-fastembed-rs`](/api/graphcanon/graph?tool=anush008-fastembed-rs) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_