--- title: "Medusa vs REST" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/fasterdecoding-medusa-vs-fasterdecoding-rest" tools: ["fasterdecoding-medusa", "fasterdecoding-rest"] --- # Medusa vs REST *GraphCanon updated Aug 24, 2026* ## Verdict Pick Medusa if medusa enables quicker language model inference with parallel decoding strategies; pick REST if rEST is a retrieval-based speculative decoding tool implemented in C, designed for use cases that demand efficiency and fine-grained control over inference processes through its distinctive approach. [Medusa](https://sites.google.com/view/medusa-llm) reports 2.8k GitHub stars, 205 forks, and 57 open issues, last pushed Jun 25, 2024. [REST](https://github.com/FasterDecoding/REST) has 220 stars, 17 forks, and 15 open issues, last pushed Mar 5, 2026. Figures are from public GitHub metadata via [Medusa's repository](https://github.com/FasterDecoding/Medusa) and [REST's repository](https://github.com/FasterDecoding/REST). | | [Medusa](/tools/fasterdecoding-medusa.md) | [REST](/tools/fasterdecoding-rest.md) | | --- | --- | --- | | Tagline | Framework for accelerating LLM generation using multiple decoding heads | REST: Retrieval-Based Speculative Decoding | | Stars | 2,767 | 220 | | Forks | 205 | 17 | | Open issues | 57 | 15 | | Language | Jupyter Notebook | C | | Adopt for | Medusa enables quicker language model inference with parallel decoding strategies. | REST is a retrieval-based speculative decoding tool implemented in C, designed for use cases that demand efficiency and fine-grained control over inference processes through its distinctive approach. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving | Data & Retrieval, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Medusa](/tools/fasterdecoding-medusa.md) | [REST](/tools/fasterdecoding-rest.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 790d | 148d | | Open issues (now) | 57 | 15 | | Stars delta | +9 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/fasterdecoding-medusa/trust.md) | [trust report](/tools/fasterdecoding-rest/trust.md) | ## Decision facts: Medusa - **Adopt for:** Medusa enables quicker language model inference with parallel decoding strategies. ## Decision facts: REST - **Adopt for:** REST is a retrieval-based speculative decoding tool implemented in C, designed for use cases that demand efficiency and fine-grained control over inference processes through its distinctive approach. ## Choose when ### Choose Medusa if… - Medusa is primarily Jupyter Notebook; REST is C. - Tags unique to Medusa: acceleration, decoding, inference, llm. - When you need to accelerate inference times for large language models without compromising on output quality. ### Choose REST if… - REST is primarily C; Medusa is Jupyter Notebook. - Tags unique to REST: llm-inference, retrieval, speculative-decoding. - Also covers Data & Retrieval. - - When you need high performance and are willing to work with the C language for customization and optimization. ## When NOT to use Medusa - If your model does not benefit from parallelized decoding, such as when the model architecture inherently limits parallel execution efficiency. - In scenarios where the computational resources required for multiple decoding heads exceed what is available or cost-effective within your infrastructure. ## When NOT to use REST - - Avoid if your team lacks proficiency in C programming as this may lead to an overhead in developing and maintaining the tool. - - Not recommended for projects where flexibility with commonly used high-level languages like Python is essential, as REST primarily relies on lower-level language capabilities. ## Common questions ### What is the difference between Medusa and REST? Medusa: Framework for accelerating LLM generation using multiple decoding heads. REST: REST: Retrieval-Based Speculative Decoding. See the comparison table for live GitHub stats and shared categories. ### When should I choose Medusa over REST? Choose Medusa over REST when Medusa is primarily Jupyter Notebook; REST is C; Tags unique to Medusa: acceleration, decoding, inference, llm; When you need to accelerate inference times for large language models without compromising on output quality. ### When should I choose REST over Medusa? Choose REST over Medusa when REST is primarily C; Medusa is Jupyter Notebook; Tags unique to REST: llm-inference, retrieval, speculative-decoding; Also covers Data & Retrieval; - When you need high performance and are willing to work with the C language for customization and optimization. ### When should I avoid Medusa? If your model does not benefit from parallelized decoding, such as when the model architecture inherently limits parallel execution efficiency. In scenarios where the computational resources required for multiple decoding heads exceed what is available or cost-effective within your infrastructure. ### When should I avoid REST? - Avoid if your team lacks proficiency in C programming as this may lead to an overhead in developing and maintaining the tool. - Not recommended for projects where flexibility with commonly used high-level languages like Python is essential, as REST primarily relies on lower-level language capabilities. ### Is Medusa or REST more popular on GitHub? Medusa has more GitHub stars (2,767 vs 220). Stars measure visibility, not whether either tool fits your constraints. ### Are Medusa and REST open source? Yes - both are open-source projects on GitHub (Medusa: Apache-2.0, REST: Apache-2.0). ### Where can I find alternatives to Medusa or REST? GraphCanon lists graph-backed alternatives at [Medusa alternatives](/tools/fasterdecoding-medusa/alternatives) and [REST alternatives](/tools/fasterdecoding-rest/alternatives) ([Medusa markdown twin](/tools/fasterdecoding-medusa/alternatives.md), [REST markdown twin](/tools/fasterdecoding-rest/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/fasterdecoding-medusa-vs-fasterdecoding-rest.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Medusa or REST? Medusa: Dormant. REST: Slowing. 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 Medusa and REST? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Medusa trust report](/tools/fasterdecoding-medusa/trust); [REST trust report](/tools/fasterdecoding-rest/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=fasterdecoding-medusa`](/api/graphcanon/graph?tool=fasterdecoding-medusa) - 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/_