--- title: "StreamSpeech vs FastChat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ictnlp-streamspeech-vs-lm-sys-fastchat" tools: ["ictnlp-streamspeech", "lm-sys-fastchat"] --- # StreamSpeech vs FastChat *GraphCanon updated Jul 11, 2026* ## Verdict Pick StreamSpeech when license: StreamSpeech is MIT, FastChat is Apache-2.0; pick FastChat when license: FastChat is Apache-2.0, StreamSpeech is MIT. [StreamSpeech](https://ictnlp.github.io/StreamSpeech-site/) reports 1.3k GitHub stars, 103 forks, and 14 open issues, last pushed Jun 29, 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 [StreamSpeech's repository](https://github.com/ictnlp/StreamSpeech) and [FastChat's repository](https://github.com/lm-sys/FastChat). | | [StreamSpeech](/tools/ictnlp-streamspeech.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Tagline | StreamSpeech is an “All in One” seamless model for offline and simultaneous speech recognition, speech translation and speech synthesis. | An open platform for training, serving, and evaluating large language models | | Stars | 1,276 | 39,490 | | Forks | 103 | 4,788 | | Open issues | 14 | 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, Speech & Audio, Evaluation & Observability | LLM Frameworks, Model Training, Inference & Serving, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [StreamSpeech](/tools/ictnlp-streamspeech.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 377d | 71d | | Open issues (now) | 14 | 1.0k | | Full report | [trust report](/tools/ictnlp-streamspeech/trust.md) | [trust report](/tools/lm-sys-fastchat/trust.md) | ## Shared compatibility - **Python**: [StreamSpeech](/tools/ictnlp-streamspeech.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 StreamSpeech if… - License: StreamSpeech is MIT, FastChat is Apache-2.0. - Tags unique to StreamSpeech: all-in-one, asr, speech, non-autoregressive. - Also covers Speech & Audio. ### Choose FastChat if… - License: FastChat is Apache-2.0, StreamSpeech is MIT. - Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving. - Also covers LLM Frameworks, Inference & Serving. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ## When NOT to use StreamSpeech - Last GitHub push was 378 days ago (dormant maintenance, Jun 29, 2025). Validate activity before betting a new project on StreamSpeech. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## 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 StreamSpeech and FastChat? StreamSpeech: StreamSpeech is an “All in One” seamless model for offline and simultaneous speech recognition, speech translation and speech synthesis.. 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 StreamSpeech over FastChat? Choose StreamSpeech over FastChat when License: StreamSpeech is MIT, FastChat is Apache-2.0; Tags unique to StreamSpeech: all-in-one, asr, speech, non-autoregressive; Also covers Speech & Audio. ### When should I choose FastChat over StreamSpeech? Choose FastChat over StreamSpeech when License: FastChat is Apache-2.0, StreamSpeech is MIT; Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving; Also covers LLM Frameworks, Inference & Serving; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I avoid StreamSpeech? Last GitHub push was 378 days ago (dormant maintenance, Jun 29, 2025). Validate activity before betting a new project on StreamSpeech. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### 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 StreamSpeech or FastChat more popular on GitHub? FastChat has more GitHub stars (39,490 vs 1,276). Stars measure visibility, not whether either tool fits your constraints. ### Are StreamSpeech and FastChat open source? Yes - both are open-source projects on GitHub (StreamSpeech: MIT, FastChat: Apache-2.0). ### Where can I find alternatives to StreamSpeech or FastChat? GraphCanon lists graph-backed alternatives at [StreamSpeech alternatives](/tools/ictnlp-streamspeech/alternatives) and [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) ([StreamSpeech markdown twin](/tools/ictnlp-streamspeech/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/ictnlp-streamspeech-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, StreamSpeech or FastChat? StreamSpeech: 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 StreamSpeech and FastChat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [StreamSpeech trust report](/tools/ictnlp-streamspeech/trust); [FastChat trust report](/tools/lm-sys-fastchat/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ictnlp-streamspeech`](/api/graphcanon/graph?tool=ictnlp-streamspeech) - 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/_