--- title: "TurboOCR vs airunner" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aiptimizer-turboocr-vs-capsize-games-airunner" tools: ["aiptimizer-turboocr", "capsize-games-airunner"] --- # TurboOCR vs airunner *GraphCanon updated Sep 20, 2026* ## Verdict Pick TurboOCR if turboOCR, optimized for GPUs, delivers high-speed OCR with support for TensorRT FP16 acceleration and PP-OCRv5 model; 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. [TurboOCR](https://turboocr.com) reports 1.1k GitHub stars, 111 forks, and 1 open issues, last pushed Sep 8, 2026. [airunner](https://airunner.art) has 1.3k stars, 103 forks, and 70 open issues, last pushed Sep 19, 2026. Figures are from public GitHub metadata via [TurboOCR's repository](https://github.com/aiptimizer/TurboOCR) and [airunner's repository](https://github.com/Capsize-Games/airunner). | | [TurboOCR](/tools/aiptimizer-turboocr.md) | [airunner](/tools/capsize-games-airunner.md) | | --- | --- | --- | | Tagline | Fast GPU-based OCR server for document parsing | Offline inference engine for art, real-time voice conversations, LLM powered chatbots and automated workflows | | Stars | 1,078 | 1,316 | | Forks | 111 | 103 | | Open issues | 1 | 70 | | Language | C++ | Python | | Adopt for | TurboOCR, optimized for GPUs, delivers high-speed OCR with support for TensorRT FP16 acceleration and PP-OCRv5 model. | AIRunner supports offline multimodal operations with a strong focus on image generation, real-time voice conversations, and LLM-powered chatbots via GUI or API. | | Persona | - | - | | Runtime | - | - | | License | MIT | GPL-3.0, ensuring free use but requiring sharing of modifications in a similar manner. | | Categories | Computer Vision, Inference & Serving | Computer Vision, Inference & Serving, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [TurboOCR](/tools/aiptimizer-turboocr.md) | [airunner](/tools/capsize-games-airunner.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 11d | 0d | | Open issues (now) | 1 | 70 | | Stars delta | +92 (30d) | +4 (30d) | | Open issues delta | 0 (30d) | +65 (30d) | | Full report | [trust report](/tools/aiptimizer-turboocr/trust.md) | [trust report](/tools/capsize-games-airunner/trust.md) | ## Decision facts: TurboOCR - **Adopt for:** TurboOCR, optimized for GPUs, delivers high-speed OCR with support for TensorRT FP16 acceleration and PP-OCRv5 model. ## 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. ## Choose when ### Choose TurboOCR if… - TurboOCR is primarily C++; airunner is Python. - License: TurboOCR is MIT, airunner is GPL-3.0. - Tags unique to TurboOCR: document-ai, document-parsing, gpu-ocr, grpc. - When you need fast text detection and recognition on GPU-enabled systems ### Choose airunner if… - airunner is primarily Python; TurboOCR is C++. - License: airunner is GPL-3.0, TurboOCR 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 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 NOT to use TurboOCR - If your infrastructure lacks a supported NVIDIA GPU or has less than required VRAM - In scenarios where the initial TensorRT engine build time cannot be accommodated ## 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) ## Common questions ### What is the difference between TurboOCR and airunner? TurboOCR: Fast GPU-based OCR server for document parsing. airunner: Offline inference engine for art, real-time voice conversations, LLM powered chatbots and automated workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose TurboOCR over airunner? Choose TurboOCR over airunner when TurboOCR is primarily C++; airunner is Python; License: TurboOCR is MIT, airunner is GPL-3.0; Tags unique to TurboOCR: document-ai, document-parsing, gpu-ocr, grpc; When you need fast text detection and recognition on GPU-enabled systems. ### When should I choose airunner over TurboOCR? Choose airunner over TurboOCR when airunner is primarily Python; TurboOCR is C++; License: airunner is GPL-3.0, TurboOCR 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 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 avoid TurboOCR? If your infrastructure lacks a supported NVIDIA GPU or has less than required VRAM In scenarios where the initial TensorRT engine build time cannot be accommodated ### 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) ### Is TurboOCR or airunner more popular on GitHub? airunner has more GitHub stars (1,316 vs 1,078). Stars measure visibility, not whether either tool fits your constraints. ### Are TurboOCR and airunner open source? Yes - both are open-source projects on GitHub (TurboOCR: MIT, airunner: GPL-3.0). ### Where can I find alternatives to TurboOCR or airunner? GraphCanon lists graph-backed alternatives at [TurboOCR alternatives](/tools/aiptimizer-turboocr/alternatives) and [airunner alternatives](/tools/capsize-games-airunner/alternatives) ([TurboOCR markdown twin](/tools/aiptimizer-turboocr/alternatives.md), [airunner markdown twin](/tools/capsize-games-airunner/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/aiptimizer-turboocr-vs-capsize-games-airunner.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, TurboOCR or airunner? TurboOCR: Active. airunner: Very active. 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 TurboOCR and airunner? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [TurboOCR trust report](/tools/aiptimizer-turboocr/trust); [airunner trust report](/tools/capsize-games-airunner/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aiptimizer-turboocr`](/api/graphcanon/graph?tool=aiptimizer-turboocr) - 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/_