--- title: "ell vs exllama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/madcowd-ell-vs-turboderp-exllama" tools: ["madcowd-ell", "turboderp-exllama"] --- # ell vs exllama *GraphCanon updated Aug 7, 2026* ## Verdict Pick ell if ell is a Python-based language model development library and prompt engineering tool; pick exllama if exLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series onwards. [ell](http://docs.ell.so/) reports 5.9k GitHub stars, 343 forks, and 186 open issues, last pushed Jun 5, 2025. [exllama](https://github.com/turboderp/exllama) has 2.9k stars, 220 forks, and 65 open issues, last pushed Sep 30, 2023. Figures are from public GitHub metadata via [ell's repository](https://github.com/MadcowD/ell) and [exllama's repository](https://github.com/turboderp/exllama). | | [ell](/tools/madcowd-ell.md) | [exllama](/tools/turboderp-exllama.md) | | --- | --- | --- | | Tagline | A language model programming library | Memory-efficient rewrite of HF transformers for Llama with quantized weights | | Stars | 5,869 | 2,937 | | Forks | 343 | 220 | | Open issues | 186 | 65 | | Language | Python | Python | | Adopt for | ell is a Python-based language model development library and prompt engineering tool. | ExLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series onwards. | | Persona | - | - | | Runtime | - | - | | License | MIT - Permissive free software license | MIT | | Categories | LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ell](/tools/madcowd-ell.md) | [exllama](/tools/turboderp-exllama.md) | | --- | --- | --- | | Days since push | 417d | 1041d | | Open issues (now) | 186 | 65 | | Full report | [trust report](/tools/madcowd-ell/trust.md) | [trust report](/tools/turboderp-exllama/trust.md) | ## Decision facts: ell - **Pricing:** freemium - Free to use under MIT License, with no premium plans mentioned. - **Adopt for:** ell is a Python-based language model development library and prompt engineering tool. - **License detail:** MIT - Permissive free software license ## Decision facts: exllama - **Adopt for:** ExLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series onwards. ## Choose when ### Choose ell if… - Pricing: Free to use under MIT License, with no premium plans mentioned.. - Tags unique to ell: ai, prompt-engineering. - When you require a dedicated Python framework for developing custom language models and fine-tuning them with specific prompts for your application. ### Choose exllama if… - Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu. - Also covers Inference & Serving. - exllama ships Docker support for self-hosted deployment. - - When deploying LLaMa models on NVIDIA GPUs from the 30-series or later that have strong FP16 support. ## When NOT to use ell - If you prefer JavaScript or other languages over Python, consider alternative frameworks that support the language of your choice. ## When NOT to use exllama - - If you are operating older GPUs such as Pascal series, which lack robust FP16 support; alternatives like AutoGPTQ might perform better. - - In scenarios that involve AMD GPU hardware (due to limited testing and optimization efforts). ## Common questions ### What is the difference between ell and exllama? ell: A language model programming library. exllama: Memory-efficient rewrite of HF transformers for Llama with quantized weights. See the comparison table for live GitHub stats and shared categories. ### When should I choose ell over exllama? Choose ell over exllama when Pricing: Free to use under MIT License, with no premium plans mentioned.; Tags unique to ell: ai, prompt-engineering; When you require a dedicated Python framework for developing custom language models and fine-tuning them with specific prompts for your application. ### When should I choose exllama over ell? Choose exllama over ell when Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu; Also covers Inference & Serving; exllama ships Docker support for self-hosted deployment; - When deploying LLaMa models on NVIDIA GPUs from the 30-series or later that have strong FP16 support. ### When should I avoid ell? If you prefer JavaScript or other languages over Python, consider alternative frameworks that support the language of your choice. ### When should I avoid exllama? - If you are operating older GPUs such as Pascal series, which lack robust FP16 support; alternatives like AutoGPTQ might perform better. - In scenarios that involve AMD GPU hardware (due to limited testing and optimization efforts). ### Is ell or exllama more popular on GitHub? ell has more GitHub stars (5,869 vs 2,937). Stars measure visibility, not whether either tool fits your constraints. ### Are ell and exllama open source? Yes - both are open-source projects on GitHub (ell: MIT, exllama: MIT). ### Where can I find alternatives to ell or exllama? GraphCanon lists graph-backed alternatives at [ell alternatives](/tools/madcowd-ell/alternatives) and [exllama alternatives](/tools/turboderp-exllama/alternatives) ([ell markdown twin](/tools/madcowd-ell/alternatives.md), [exllama markdown twin](/tools/turboderp-exllama/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/madcowd-ell-vs-turboderp-exllama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ell or exllama? ell: Dormant. exllama: Dormant. 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 ell and exllama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ell trust report](/tools/madcowd-ell/trust); [exllama trust report](/tools/turboderp-exllama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=madcowd-ell`](/api/graphcanon/graph?tool=madcowd-ell) - 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/_