--- title: "whisper-timestamped vs FastChat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/linto-ai-whisper-timestamped-vs-lm-sys-fastchat" tools: ["linto-ai-whisper-timestamped", "lm-sys-fastchat"] --- # whisper-timestamped vs FastChat *GraphCanon updated Jul 11, 2026* ## Verdict Pick whisper-timestamped when license: whisper-timestamped is AGPL-3.0, FastChat is Apache-2.0; pick FastChat when license: FastChat is Apache-2.0, whisper-timestamped is AGPL-3.0. [whisper-timestamped](https://github.com/linto-ai/whisper-timestamped) reports 2.8k GitHub stars, 210 forks, and 49 open issues, last pushed Sep 9, 2025. [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 [whisper-timestamped's repository](https://github.com/linto-ai/whisper-timestamped) and [FastChat's repository](https://github.com/lm-sys/FastChat). | | [whisper-timestamped](/tools/linto-ai-whisper-timestamped.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Tagline | Multilingual Automatic Speech Recognition with word-level timestamps and confidence | An open platform for training, serving, and evaluating large language models | | Stars | 2,823 | 39,490 | | Forks | 210 | 4,788 | | Open issues | 49 | 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 | AGPL-3.0 | Apache-2.0 | | Categories | Inference & Serving, Model Training, Speech & Audio | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whisper-timestamped](/tools/linto-ai-whisper-timestamped.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Steady (60%) | | Days since push | 305d | 71d | | Open issues (now) | 49 | 1.0k | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/linto-ai-whisper-timestamped/trust.md) | [trust report](/tools/lm-sys-fastchat/trust.md) | ## Shared compatibility - **Python**: [whisper-timestamped](/tools/linto-ai-whisper-timestamped.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 whisper-timestamped if… - License: whisper-timestamped is AGPL-3.0, FastChat is Apache-2.0. - Tags unique to whisper-timestamped: asr, attention mechanism, attention-is-all-you-need, attention-model. - Also covers Speech & Audio. - whisper-timestamped ships Docker support for self-hosted deployment. ### Choose FastChat if… - License: FastChat is Apache-2.0, whisper-timestamped is AGPL-3.0. - Tags unique to FastChat: chatbots, distributed serving, evaluation system, large-language-models. - Also covers Evaluation & Observability, LLM Frameworks. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ## When NOT to use whisper-timestamped - Last GitHub push was 306 days ago (slowing maintenance, Sep 9, 2025). Validate activity before betting a new project on whisper-timestamped. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## 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 whisper-timestamped and FastChat? whisper-timestamped: Multilingual Automatic Speech Recognition with word-level timestamps and confidence. 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 whisper-timestamped over FastChat? Choose whisper-timestamped over FastChat when License: whisper-timestamped is AGPL-3.0, FastChat is Apache-2.0; Tags unique to whisper-timestamped: asr, attention mechanism, attention-is-all-you-need, attention-model; Also covers Speech & Audio; whisper-timestamped ships Docker support for self-hosted deployment. ### When should I choose FastChat over whisper-timestamped? Choose FastChat over whisper-timestamped when License: FastChat is Apache-2.0, whisper-timestamped is AGPL-3.0; Tags unique to FastChat: chatbots, distributed serving, evaluation system, large-language-models; Also covers Evaluation & Observability, LLM Frameworks; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I avoid whisper-timestamped? Last GitHub push was 306 days ago (slowing maintenance, Sep 9, 2025). Validate activity before betting a new project on whisper-timestamped. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### 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 whisper-timestamped or FastChat more popular on GitHub? FastChat has more GitHub stars (39,490 vs 2,823). Stars measure visibility, not whether either tool fits your constraints. ### Are whisper-timestamped and FastChat open source? Yes - both are open-source projects on GitHub (whisper-timestamped: AGPL-3.0, FastChat: Apache-2.0). ### Where can I find alternatives to whisper-timestamped or FastChat? GraphCanon lists graph-backed alternatives at [whisper-timestamped alternatives](/tools/linto-ai-whisper-timestamped/alternatives) and [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) ([whisper-timestamped markdown twin](/tools/linto-ai-whisper-timestamped/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/linto-ai-whisper-timestamped-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, whisper-timestamped or FastChat? whisper-timestamped: Slowing. 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 whisper-timestamped and FastChat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whisper-timestamped trust report](/tools/linto-ai-whisper-timestamped/trust); [FastChat trust report](/tools/lm-sys-fastchat/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=linto-ai-whisper-timestamped`](/api/graphcanon/graph?tool=linto-ai-whisper-timestamped) - 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/_