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Comparison

FlagAI vs FastChat

Verdict

Pick FlagAI if flagAI is identified by its fast and scalable toolkit designed for managing large-scale AI models in Python, under an Apache-2.0 license; pick FastChat if 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.

Markdown twin · FlagAI alternatives · FastChat alternatives

GraphCanon updated 5d

FlagAI logo

FlagAI

FlagAI-Open/FlagAI

★ 3.9kpushed Jul 13, 2026
vs
FastChat logo

FastChat

lm-sys/FastChat

★ 40kpushed May 1, 2026

Trust & integrity

SignalFlagAIFastChat
Maintenance
Steady (33d since push)
As of 5d · github_public_v1
Slowing (98d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 5d · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1
FlagAI trust reportFastChat trust reportTrust methodology

Tagline

FlagAI
Fast, easy-to-use framework for large-scale AI models.
FastChat
An open platform for training, serving, and evaluating large language models

Stars

FlagAI
3.9k
FastChat
40k

Forks

FlagAI
416
FastChat
4.8k

Open issues

FlagAI
22
FastChat
1.0k

Language

FlagAI
Python
FastChat
Python

Adopt for

FlagAI
FlagAI is identified by its fast and scalable toolkit designed for managing large-scale AI models in Python, under an Apache-2.0 license.
FastChat
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

FlagAI
-
FastChat
-

Runtime

FlagAI
-
FastChat
-

License

FlagAI
Apache-2.0
FastChat
Apache-2.0

Last pushed

FlagAI
Jul 13, 2026
FastChat
May 1, 2026

Categories

FlagAI
LLM Frameworks, Model Training
FastChat
Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training

Trust and health

Maintenance

FlagAI
Steady (60%)
FastChat
Slowing (36%)

Days since push

FlagAI
33d
FastChat
98d

Open issues (now)

FlagAI
22
FastChat
1.0k

Stars delta

FlagAI
+2 (30d)
FastChat
Unknown

Open issues delta

FlagAI
0 (30d)
FastChat
Unknown

Full report

FlagAI
Trust report
FastChat
Trust report

Shared compatibility

  • Python · FlagAI: Python runtime · FastChat: Python runtime

Choose FlagAI if…

  • Tags unique to FlagAI: extensible, fast, large-scale models.
  • FlagAI ships Docker support for self-hosted deployment.
  • When you prioritize speed and extensibility during the development of large-scale AI models with a focus on easy-to-use interfaces.

When NOT to use FlagAI

  • If your project necessitates a deep level of customization that might not be supported by FlagAI's framework.
  • If you are working with smaller datasets, the overhead provided by FlagAI’s scalability features could be unnecessary and potentially inefficient.
GitHubDetails

Choose FastChat if…

  • Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models.
  • Also covers Evaluation & Observability, Inference & Serving.
  • - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.

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.
GitHubDetails

Explore

FlagAI trust report →FastChat trust report →LLM Frameworks category →Model Training category →Evaluation & Observability category →Inference & Serving category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: FlagAI 3.9k · FastChat 40k (synced Aug 15, 2026).

Common questions

What is the difference between FlagAI and FastChat?
FlagAI: Fast, easy-to-use framework for large-scale AI models.. 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 FlagAI over FastChat?
Choose FlagAI over FastChat when Tags unique to FlagAI: extensible, fast, large-scale models; FlagAI ships Docker support for self-hosted deployment; When you prioritize speed and extensibility during the development of large-scale AI models with a focus on easy-to-use interfaces.
When should I choose FastChat over FlagAI?
Choose FastChat over FlagAI when Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models; Also covers Evaluation & Observability, Inference & Serving; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.
When should I avoid FlagAI?
If your project necessitates a deep level of customization that might not be supported by FlagAI's framework. If you are working with smaller datasets, the overhead provided by FlagAI’s scalability features could be unnecessary and potentially inefficient.
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 FlagAI or FastChat more popular on GitHub?
FastChat has more GitHub stars (39,517 vs 3,870). Stars measure visibility, not whether either tool fits your constraints.
Are FlagAI and FastChat open source?
Yes - both are open-source projects on GitHub (FlagAI: Apache-2.0, FastChat: Apache-2.0).
Where can I find alternatives to FlagAI or FastChat?
GraphCanon lists graph-backed alternatives at FlagAI alternatives and FastChat alternatives (FlagAI markdown twin, FastChat markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, FlagAI or FastChat?
FlagAI: Steady. FastChat: 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 FlagAI and FastChat?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FlagAI trust report; FastChat trust report.

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