--- title: "image-hijacks vs FastChat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/euanong-image-hijacks-vs-lm-sys-fastchat" tools: ["euanong-image-hijacks", "lm-sys-fastchat"] --- # image-hijacks vs FastChat *GraphCanon updated Jul 11, 2026* ## Verdict Pick image-hijacks when license: image-hijacks is MIT, FastChat is Apache-2.0; pick FastChat when license: FastChat is Apache-2.0, image-hijacks is MIT. [image-hijacks](https://image-hijacks.github.io/) reports 56 GitHub stars, 12 forks, and 8 open issues, last pushed Sep 19, 2023. [FastChat](https://github.com/lm-sys/FastChat) has 39k stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. Figures are from public GitHub metadata via [image-hijacks's repository](https://github.com/euanong/image-hijacks) and [FastChat's repository](https://github.com/lm-sys/FastChat). | | [image-hijacks](/tools/euanong-image-hijacks.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Tagline | Official codebase for Image Hijacks: Adversarial Images can Control Generative Models at Runtime | An open platform for training, serving, and evaluating large language models | | Stars | 56 | 39,490 | | Forks | 12 | 4,788 | | Open issues | 8 | 1,027 | | Language | Python | Python | | Adopt for | - | FastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Model Training, Inference & Serving, Computer Vision | LLM Frameworks, Model Training, Inference & Serving, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [image-hijacks](/tools/euanong-image-hijacks.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 1026d | 71d | | Open issues (now) | 8 | 1.0k | | Owner type | User | Organization | | Full report | [trust report](/tools/euanong-image-hijacks/trust.md) | [trust report](/tools/lm-sys-fastchat/trust.md) | ## Shared compatibility - **Python**: [image-hijacks](/tools/euanong-image-hijacks.md) - Python runtime; [FastChat](/tools/lm-sys-fastchat.md) - Python runtime ## Decision facts: FastChat - **Adopt for:** FastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB ## Choose when ### Choose image-hijacks if… - License: image-hijacks is MIT, FastChat is Apache-2.0. - Tags unique to image-hijacks: python. - Also covers Computer Vision. ### Choose FastChat if… - License: FastChat is Apache-2.0, image-hijacks is MIT. - Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving. - Also covers LLM Frameworks, Evaluation & Observability. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ## When NOT to use image-hijacks - Last GitHub push was 1026 days ago (dormant maintenance, Sep 19, 2023). Validate activity before betting a new project on image-hijacks. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## When NOT to use FastChat - - You require a proprietary or closed-source framework; FastChat is open-source under Apache-2.0 license and its use might be unsuitable for environments requiring proprietary solutions. - - Your chatbot evaluation needs do not align with the types of data used in FastChat's datasets (e.g., human votes, MT-Bench evaluations). - - You prefer a more user-friendly setup without the need to clone a repository and manually install dependencies; FastChat requires installation from source with additional steps for Rust and CMake on - + Mac. ## Common questions ### What is the difference between image-hijacks and FastChat? image-hijacks: Official codebase for Image Hijacks: Adversarial Images can Control Generative Models at Runtime. FastChat: An open platform for training, serving, and evaluating large language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose image-hijacks over FastChat? Choose image-hijacks over FastChat when License: image-hijacks is MIT, FastChat is Apache-2.0; Tags unique to image-hijacks: python; Also covers Computer Vision. ### When should I choose FastChat over image-hijacks? Choose FastChat over image-hijacks when License: FastChat is Apache-2.0, image-hijacks is MIT; Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving; Also covers LLM Frameworks, Evaluation & Observability; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I avoid image-hijacks? Last GitHub push was 1026 days ago (dormant maintenance, Sep 19, 2023). Validate activity before betting a new project on image-hijacks. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### When should I avoid FastChat? - You require a proprietary or closed-source framework; FastChat is open-source under Apache-2.0 license and its use might be unsuitable for environments requiring proprietary solutions. - Your chatbot evaluation needs do not align with the types of data used in FastChat's datasets (e.g., human votes, MT-Bench evaluations). - You prefer a more user-friendly setup without the need to clone a repository and manually install dependencies; FastChat requires installation from source with additional steps for Rust and CMake on + Mac. ### Is image-hijacks or FastChat more popular on GitHub? FastChat has more GitHub stars (39,490 vs 56). Stars measure visibility, not whether either tool fits your constraints. ### Are image-hijacks and FastChat open source? Yes - both are open-source projects on GitHub (image-hijacks: MIT, FastChat: Apache-2.0). ### Where can I find alternatives to image-hijacks or FastChat? GraphCanon lists graph-backed alternatives at [image-hijacks alternatives](/tools/euanong-image-hijacks/alternatives) and [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) ([image-hijacks markdown twin](/tools/euanong-image-hijacks/alternatives.md), [FastChat markdown twin](/tools/lm-sys-fastchat/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/euanong-image-hijacks-vs-lm-sys-fastchat.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, image-hijacks or FastChat? image-hijacks: Dormant. FastChat: Steady. 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 image-hijacks and FastChat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [image-hijacks trust report](/tools/euanong-image-hijacks/trust); [FastChat trust report](/tools/lm-sys-fastchat/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=euanong-image-hijacks`](/api/graphcanon/graph?tool=euanong-image-hijacks) - 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/_