--- title: "airunner vs fastDeploy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/capsize-games-airunner-vs-notai-tech-fastdeploy" tools: ["capsize-games-airunner", "notai-tech-fastdeploy"] --- # airunner vs fastDeploy *GraphCanon updated Sep 20, 2026* ## Verdict Pick airunner if aIRunner supports offline multimodal operations with a strong focus on image generation, real-time voice conversations, and LLM-powered chatbots via GUI or API; pick fastDeploy if fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines. [airunner](https://airunner.art) reports 1.3k GitHub stars, 103 forks, and 70 open issues, last pushed Sep 19, 2026. [fastDeploy](https://github.com/notAI-tech/fastDeploy) has 105 stars, 17 forks, and 0 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [airunner's repository](https://github.com/Capsize-Games/airunner) and [fastDeploy's repository](https://github.com/notAI-tech/fastDeploy). | | [airunner](/tools/capsize-games-airunner.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Tagline | Offline inference engine for art, real-time voice conversations, LLM powered chatbots and automated workflows | Deploy DL/ML inference pipelines with minimal extra code. | | Stars | 1,316 | 105 | | Forks | 103 | 17 | | Open issues | 70 | 0 | | Language | Python | Python | | Adopt for | AIRunner supports offline multimodal operations with a strong focus on image generation, real-time voice conversations, and LLM-powered chatbots via GUI or API. | fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0, ensuring free use but requiring sharing of modifications in a similar manner. | MIT | | Categories | Computer Vision, Inference & Serving, Speech & Audio | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [airunner](/tools/capsize-games-airunner.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 221d | | Open issues (now) | 70 | 0 | | Stars delta | +4 (30d) | 0 (30d) | | Open issues delta | +65 (30d) | 0 (30d) | | Full report | [trust report](/tools/capsize-games-airunner/trust.md) | [trust report](/tools/notai-tech-fastdeploy/trust.md) | ## Decision facts: airunner - **Requirements:** Min 16 GB RAM; Requires Docker; Requires specific GPU support (NVIDIA) and larger storage allocations compared to competitors - **Adopt for:** AIRunner supports offline multimodal operations with a strong focus on image generation, real-time voice conversations, and LLM-powered chatbots via GUI or API. - **License detail:** GPL-3.0, ensuring free use but requiring sharing of modifications in a similar manner. ## Decision facts: fastDeploy - **Pricing:** freemium - - - **Requirements:** - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory. - **Adopt for:** fastDeploy simplifies ML/DL model deployment focusing on minimal code for inference pipelines. ## Choose when ### Choose airunner if… - License: airunner is GPL-3.0, fastDeploy is MIT. - Requirements: Min 16 GB RAM; Requires Docker; Requires specific GPU support (NVIDIA) and larger storage allocations compared to competitors. - Tags unique to airunner: ai art, chatbot, image-generation, speech-to-text. - Also covers Computer Vision, Speech & Audio. - airunner ships Docker support for self-hosted deployment. - When needing an all-inclusive offline tool for both image generation and speech-to-text/text-to-speech functionalities ### Choose fastDeploy if… - License: fastDeploy is MIT, airunner is GPL-3.0. - Pricing: -. - Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory.. - Tags unique to fastDeploy: deep-learning, docker, falcon, gevent. - When you aim to streamline the deployment of TensorFlow Serving, TorchServe, and Triton Inference Server models without extensive coding. ## When NOT to use airunner - If your primary need is cloud-based services as AIRunner focuses on local deployments only - In scenarios where minimal hardware requirements are crucial, given AIRunner's higher system demands (min. 16 GB RAM, NVIDIA RTX 3060) ## When NOT to use fastDeploy - Avoid if you are looking for a solution that supports real-time interactive deployments requiring advanced websocket handling beyond fastDeploy's basic capability. - Not recommended when the project requires heavy customization of deployment scripts, as it emphasizes minimal coding and may restrict flexibility in pipeline configurations. ## Common questions ### What is the difference between airunner and fastDeploy? airunner: Offline inference engine for art, real-time voice conversations, LLM powered chatbots and automated workflows. fastDeploy: Deploy DL/ML inference pipelines with minimal extra code.. See the comparison table for live GitHub stats and shared categories. ### When should I choose airunner over fastDeploy? Choose airunner over fastDeploy when License: airunner is GPL-3.0, fastDeploy is MIT; Requirements: Min 16 GB RAM; Requires Docker; Requires specific GPU support (NVIDIA) and larger storage allocations compared to competitors; Tags unique to airunner: ai art, chatbot, image-generation, speech-to-text; Also covers Computer Vision, Speech & Audio; airunner ships Docker support for self-hosted deployment; When needing an all-inclusive offline tool for both image generation and speech-to-text/text-to-speech functionalities. ### When should I choose fastDeploy over airunner? Choose fastDeploy over airunner when License: fastDeploy is MIT, airunner is GPL-3.0; Pricing: -; Requirements: - Python is required for running fastDeploy.; - Docker installation is suggested but not mandatory.; Tags unique to fastDeploy: deep-learning, docker, falcon, gevent; When you aim to streamline the deployment of TensorFlow Serving, TorchServe, and Triton Inference Server models without extensive coding. ### When should I avoid airunner? If your primary need is cloud-based services as AIRunner focuses on local deployments only In scenarios where minimal hardware requirements are crucial, given AIRunner's higher system demands (min. 16 GB RAM, NVIDIA RTX 3060) ### When should I avoid fastDeploy? Avoid if you are looking for a solution that supports real-time interactive deployments requiring advanced websocket handling beyond fastDeploy's basic capability. Not recommended when the project requires heavy customization of deployment scripts, as it emphasizes minimal coding and may restrict flexibility in pipeline configurations. ### Is airunner or fastDeploy more popular on GitHub? airunner has more GitHub stars (1,316 vs 105). Stars measure visibility, not whether either tool fits your constraints. ### Are airunner and fastDeploy open source? Yes - both are open-source projects on GitHub (airunner: GPL-3.0, fastDeploy: MIT). ### Where can I find alternatives to airunner or fastDeploy? GraphCanon lists graph-backed alternatives at [airunner alternatives](/tools/capsize-games-airunner/alternatives) and [fastDeploy alternatives](/tools/notai-tech-fastdeploy/alternatives) ([airunner markdown twin](/tools/capsize-games-airunner/alternatives.md), [fastDeploy markdown twin](/tools/notai-tech-fastdeploy/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/capsize-games-airunner-vs-notai-tech-fastdeploy.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, airunner or fastDeploy? airunner: Very active. fastDeploy: 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 airunner and fastDeploy? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [airunner trust report](/tools/capsize-games-airunner/trust); [fastDeploy trust report](/tools/notai-tech-fastdeploy/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=capsize-games-airunner`](/api/graphcanon/graph?tool=capsize-games-airunner) - 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/_