--- title: "llama2-webui vs exllama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/liltom-eth-llama2-webui-vs-turboderp-exllama" tools: ["liltom-eth-llama2-webui", "turboderp-exllama"] --- # llama2-webui vs exllama *GraphCanon updated Aug 25, 2026* ## Verdict Pick llama2-webui if llama2-webui - Run Llama 2 models locally via Gradio UI on GPU or CPU; 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. [llama2-webui](https://github.com/liltom-eth/llama2-webui) reports 1.9k GitHub stars, 199 forks, and 26 open issues, last pushed Mar 22, 2024. [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 [llama2-webui's repository](https://github.com/liltom-eth/llama2-webui) and [exllama's repository](https://github.com/turboderp/exllama). | | [llama2-webui](/tools/liltom-eth-llama2-webui.md) | [exllama](/tools/turboderp-exllama.md) | | --- | --- | --- | | Tagline | Run Llama 2 locally with gradio UI on GPU or CPU | Memory-efficient rewrite of HF transformers for Llama with quantized weights | | Stars | 1,937 | 2,937 | | Forks | 199 | 220 | | Open issues | 26 | 65 | | Language | Jupyter Notebook | Python | | Adopt for | llama2-webui - Run Llama 2 models locally via Gradio UI on GPU or CPU. | 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 | The MIT License grants permissive software rights making llama2-webui suitable for both proprietary and open-source projects. | MIT | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llama2-webui](/tools/liltom-eth-llama2-webui.md) | [exllama](/tools/turboderp-exllama.md) | | --- | --- | --- | | Days since push | 885d | 1041d | | Open issues (now) | 26 | 65 | | Stars delta | 0 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/liltom-eth-llama2-webui/trust.md) | [trust report](/tools/turboderp-exllama/trust.md) | ## Decision facts: llama2-webui - **Requirements:** - Ensure you have access to Llama 2 models before proceeding.; - Requires a Python environment capable of running Jupyter Notebooks along with the specified dependencies such as Gradio. - **Adopt for:** llama2-webui - Run Llama 2 models locally via Gradio UI on GPU or CPU. - **License detail:** The MIT License grants permissive software rights making llama2-webui suitable for both proprietary and open-source projects. ## 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 llama2-webui if… - llama2-webui is primarily Jupyter Notebook; exllama is Python. - Requirements: - Ensure you have access to Llama 2 models before proceeding.; - Requires a Python environment capable of running Jupyter Notebooks along with the specified dependencies such as Gradio.. - Tags unique to llama2-webui: gradio, llama-2, local-inference. - - When you want to run Llama 2 models locally with minimal setup across various operating systems like Linux, Windows, and Mac. ### Choose exllama if… - exllama is primarily Python; llama2-webui is Jupyter Notebook. - Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu. - 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 llama2-webui - - Avoid if you are looking for broader support beyond Llama 2 models; this tool is specifically tailored to work with the Llama 2 series. - - Not recommended if your project strictly requires a web-based deployment without a local server component, as it emphasizes local model inference. ## 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 llama2-webui and exllama? llama2-webui: Run Llama 2 locally with gradio UI on GPU or CPU. 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 llama2-webui over exllama? Choose llama2-webui over exllama when llama2-webui is primarily Jupyter Notebook; exllama is Python; Requirements: - Ensure you have access to Llama 2 models before proceeding.; - Requires a Python environment capable of running Jupyter Notebooks along with the specified dependencies such as Gradio.; Tags unique to llama2-webui: gradio, llama-2, local-inference; - When you want to run Llama 2 models locally with minimal setup across various operating systems like Linux, Windows, and Mac. ### When should I choose exllama over llama2-webui? Choose exllama over llama2-webui when exllama is primarily Python; llama2-webui is Jupyter Notebook; Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu; 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 llama2-webui? - Avoid if you are looking for broader support beyond Llama 2 models; this tool is specifically tailored to work with the Llama 2 series. - Not recommended if your project strictly requires a web-based deployment without a local server component, as it emphasizes local model inference. ### 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 llama2-webui or exllama more popular on GitHub? exllama has more GitHub stars (2,937 vs 1,937). Stars measure visibility, not whether either tool fits your constraints. ### Are llama2-webui and exllama open source? Yes - both are open-source projects on GitHub (llama2-webui: MIT, exllama: MIT). ### Where can I find alternatives to llama2-webui or exllama? GraphCanon lists graph-backed alternatives at [llama2-webui alternatives](/tools/liltom-eth-llama2-webui/alternatives) and [exllama alternatives](/tools/turboderp-exllama/alternatives) ([llama2-webui markdown twin](/tools/liltom-eth-llama2-webui/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/liltom-eth-llama2-webui-vs-turboderp-exllama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llama2-webui or exllama? llama2-webui: 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 llama2-webui and exllama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llama2-webui trust report](/tools/liltom-eth-llama2-webui/trust); [exllama trust report](/tools/turboderp-exllama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=liltom-eth-llama2-webui`](/api/graphcanon/graph?tool=liltom-eth-llama2-webui) - 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/_