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Home/Compare/FastChat vs llms-tools

Comparison

FastChat vs llms-tools

Verdict

Pick FastChat when tags unique to FastChat: evaluation system, large-language-models, distributed serving; pick llms-tools when tags unique to llms-tools: data-science, chat-bot, llm, ai.

Markdown twin · FastChat alternatives · llms-tools alternatives

GraphCanon updated today

FastChat logo

FastChat

lm-sys/FastChat

★ 39kpushed May 1, 2026
vs
llms-tools logo

llms-tools

PetroIvaniuk/llms-tools

★ 319pushed Jun 1, 2026

Trust & integrity

SignalFastChatllms-tools
Maintenance
Steady (71d since push)
As of today · github_public_v1
Steady (39d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none
FastChat trust reportllms-tools trust reportTrust methodology

Tagline

FastChat
An open platform for training, serving, and evaluating large language models
llms-tools
A list of LLMs Tools & Projects

Stars

FastChat
39k
llms-tools
319

Forks

FastChat
4.8k
llms-tools
46

Open issues

FastChat
1.0k
llms-tools
3

Language

FastChat
Python
llms-tools
-

Adopt for

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
llms-tools
-

Persona

FastChat
-
llms-tools
-

Runtime

FastChat
-
llms-tools
-

License

FastChat
Apache-2.0
llms-tools
Apache-2.0

Last pushed

FastChat
May 1, 2026
llms-tools
Jun 1, 2026

Categories

FastChat
LLM Frameworks, Model Training, Inference & Serving, Evaluation & Observability
llms-tools
LLM Frameworks, Evaluation & Observability

Trust and health

Days since push

FastChat
71d
llms-tools
39d

Open issues (now)

FastChat
1.0k
llms-tools
3

Owner type

FastChat
Organization
llms-tools
User

Full report

FastChat
Trust report
llms-tools
Trust report

Choose FastChat if…

  • Tags unique to FastChat: evaluation system, large-language-models, distributed serving.
  • Also covers Model Training, 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

Choose llms-tools if…

  • Tags unique to llms-tools: data-science, chat-bot, llm, ai.
  • More recently updated (last pushed Jun 1, 2026).

When NOT to use llms-tools

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
GitHubDetails

Explore

FastChat trust report →llms-tools trust report →LLM Frameworks category →Model Training category →Inference & Serving category →Evaluation & Observability 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: FastChat 39k · llms-tools 319 (synced Jul 11, 2026).

Common questions

What is the difference between FastChat and llms-tools?
FastChat: An open platform for training, serving, and evaluating large language models. llms-tools: A list of LLMs Tools & Projects. See the comparison table for live GitHub stats and shared categories.
When should I choose FastChat over llms-tools?
Choose FastChat over llms-tools when Tags unique to FastChat: evaluation system, large-language-models, distributed serving; Also covers Model Training, Inference & Serving; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.
When should I choose llms-tools over FastChat?
Choose llms-tools over FastChat when Tags unique to llms-tools: data-science, chat-bot, llm, ai; More recently updated (last pushed Jun 1, 2026).
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.
When should I avoid llms-tools?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Is FastChat or llms-tools more popular on GitHub?
FastChat has more GitHub stars (39,490 vs 319). Stars measure visibility, not whether either tool fits your constraints.
Are FastChat and llms-tools open source?
Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, llms-tools: Apache-2.0).
Where can I find alternatives to FastChat or llms-tools?
GraphCanon lists graph-backed alternatives at FastChat alternatives and llms-tools alternatives (FastChat markdown twin, llms-tools 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, FastChat or llms-tools?
FastChat: Steady. llms-tools: 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 FastChat and llms-tools?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FastChat trust report; llms-tools trust report.