--- title: "BodhiApp vs exllama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bodhisearch-bodhiapp-vs-turboderp-exllama" tools: ["bodhisearch-bodhiapp", "turboderp-exllama"] --- # BodhiApp vs exllama *GraphCanon updated Aug 13, 2026* ## Verdict Pick BodhiApp if bodhiApp streamlines local deployment of open-source and open-weight LLMs via Docker images, compatible with multiple hardware acceleration methods; 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. [BodhiApp](https://getbodhi.app/) reports 136 GitHub stars, 10 forks, and 10 open issues, last pushed Jul 26, 2026. [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 [BodhiApp's repository](https://github.com/BodhiSearch/BodhiApp) and [exllama's repository](https://github.com/turboderp/exllama). | | [BodhiApp](/tools/bodhisearch-bodhiapp.md) | [exllama](/tools/turboderp-exllama.md) | | --- | --- | --- | | Tagline | Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs | Memory-efficient rewrite of HF transformers for Llama with quantized weights | | Stars | 136 | 2,937 | | Forks | 10 | 220 | | Open issues | 10 | 65 | | Language | TypeScript | Python | | Adopt for | BodhiApp streamlines local deployment of open-source and open-weight LLMs via Docker images, compatible with multiple hardware acceleration methods. | 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 license information for BodhiApp has not been provided. | MIT | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [BodhiApp](/tools/bodhisearch-bodhiapp.md) | [exllama](/tools/turboderp-exllama.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 18d | 1041d | | Open issues (now) | 10 | 65 | | Owner type | Organization | User | | Full report | [trust report](/tools/bodhisearch-bodhiapp/trust.md) | [trust report](/tools/turboderp-exllama/trust.md) | ## Decision facts: BodhiApp - **Pricing:** unknown - Pricing details are not mentioned in the repository data. - **Requirements:** Requires Docker; Requires Docker environment. Specific model requirements vary depending on the hardware variant chosen. - **Adopt for:** BodhiApp streamlines local deployment of open-source and open-weight LLMs via Docker images, compatible with multiple hardware acceleration methods. - **License detail:** The license information for BodhiApp has not been provided. ## 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 BodhiApp if… - BodhiApp is primarily TypeScript; exllama is Python. - Pricing: Pricing details are not mentioned in the repository data.. - Requirements: Requires Docker; Requires Docker environment. Specific model requirements vary depending on the hardware variant chosen.. - Tags unique to BodhiApp: gemma, generative-ai, llama, llm. - You need to deploy LLMs locally with flexible hardware support including AMD, NVIDIA GPUs, and CPUs. ### Choose exllama if… - exllama is primarily Python; BodhiApp is TypeScript. - 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 BodhiApp - Your project strictly requires non-local deployment options, as BodhiApp focuses on local hosting of models. - If your environment is limited to unsupported GPU hardware or lacks adequate drivers for CUDA, ROCm, or Vulkan acceleration methods. - You need support beyond Mac platforms as BodhiApp does not yet provide installation instructions for other operating systems. ## 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 BodhiApp and exllama? BodhiApp: Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs. 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 BodhiApp over exllama? Choose BodhiApp over exllama when BodhiApp is primarily TypeScript; exllama is Python; Pricing: Pricing details are not mentioned in the repository data.; Requirements: Requires Docker; Requires Docker environment. Specific model requirements vary depending on the hardware variant chosen.; Tags unique to BodhiApp: gemma, generative-ai, llama, llm; You need to deploy LLMs locally with flexible hardware support including AMD, NVIDIA GPUs, and CPUs. ### When should I choose exllama over BodhiApp? Choose exllama over BodhiApp when exllama is primarily Python; BodhiApp is TypeScript; 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 BodhiApp? Your project strictly requires non-local deployment options, as BodhiApp focuses on local hosting of models. If your environment is limited to unsupported GPU hardware or lacks adequate drivers for CUDA, ROCm, or Vulkan acceleration methods. You need support beyond Mac platforms as BodhiApp does not yet provide installation instructions for other operating systems. ### 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 BodhiApp or exllama more popular on GitHub? exllama has more GitHub stars (2,937 vs 136). Stars measure visibility, not whether either tool fits your constraints. ### Are BodhiApp and exllama open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to BodhiApp or exllama? GraphCanon lists graph-backed alternatives at [BodhiApp alternatives](/tools/bodhisearch-bodhiapp/alternatives) and [exllama alternatives](/tools/turboderp-exllama/alternatives) ([BodhiApp markdown twin](/tools/bodhisearch-bodhiapp/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/bodhisearch-bodhiapp-vs-turboderp-exllama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, BodhiApp or exllama? BodhiApp: Active. 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 BodhiApp and exllama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [BodhiApp trust report](/tools/bodhisearch-bodhiapp/trust); [exllama trust report](/tools/turboderp-exllama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bodhisearch-bodhiapp`](/api/graphcanon/graph?tool=bodhisearch-bodhiapp) - 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/_