---
title: "FastChat vs generative-ai-for-beginners"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/lm-sys-fastchat-vs-microsoft-generative-ai-for-beginners"
tools: ["lm-sys-fastchat", "microsoft-generative-ai-for-beginners"]
---

# FastChat vs generative-ai-for-beginners

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick FastChat when fastChat is primarily Python; generative-ai-for-beginners is Jupyter Notebook; pick generative-ai-for-beginners when generative-ai-for-beginners is primarily Jupyter Notebook; FastChat is Python.

[FastChat](https://github.com/lm-sys/FastChat) reports 39k GitHub stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. [generative-ai-for-beginners](https://github.com/microsoft/generative-ai-for-beginners) has 113k stars, 61k forks, and 7 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [FastChat's repository](https://github.com/lm-sys/FastChat) and [generative-ai-for-beginners's repository](https://github.com/microsoft/generative-ai-for-beginners).

| | [FastChat](/tools/lm-sys-fastchat.md) | [generative-ai-for-beginners](/tools/microsoft-generative-ai-for-beginners.md) |
| --- | --- | --- |
| Tagline | An open platform for training, serving, and evaluating large language models | 21 Lessons, Get Started Building with Generative AI |
| Stars | 39,490 | 112,866 |
| Forks | 4,788 | 60,628 |
| Open issues | 1,027 | 7 |
| Language | Python | Jupyter Notebook |
| 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 | Apache-2.0 | MIT |
| Categories | Model Training, LLM Frameworks, Inference & Serving, Evaluation & Observability | LLM Frameworks, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [FastChat](/tools/lm-sys-fastchat.md) | [generative-ai-for-beginners](/tools/microsoft-generative-ai-for-beginners.md) |
| --- | --- | --- |
| Maintenance | Steady (60%) | Very active (96%) |
| Days since push | 71d | 2d |
| Open issues (now) | 1.0k | 7 |
| Full report | [trust report](/tools/lm-sys-fastchat/trust.md) | [trust report](/tools/microsoft-generative-ai-for-beginners/trust.md) |

## 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 FastChat if…

- FastChat is primarily Python; generative-ai-for-beginners is Jupyter Notebook.
- License: FastChat is Apache-2.0, generative-ai-for-beginners is MIT.
- Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving.
- Also covers Inference & Serving, Evaluation & Observability.
- - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.

### Choose generative-ai-for-beginners if…

- generative-ai-for-beginners is primarily Jupyter Notebook; FastChat is Python.
- License: generative-ai-for-beginners is MIT, FastChat is Apache-2.0.
- Tags unique to generative-ai-for-beginners: generativeai, dall-e, ai, generative-ai.

## 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.

## When NOT to use generative-ai-for-beginners

- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

## Common questions

### What is the difference between FastChat and generative-ai-for-beginners?

FastChat: An open platform for training, serving, and evaluating large language models. generative-ai-for-beginners: 21 Lessons, Get Started Building with Generative AI. See the comparison table for live GitHub stats and shared categories.

### When should I choose FastChat over generative-ai-for-beginners?

Choose FastChat over generative-ai-for-beginners when FastChat is primarily Python; generative-ai-for-beginners is Jupyter Notebook; License: FastChat is Apache-2.0, generative-ai-for-beginners is MIT; Tags unique to FastChat: evaluation system, large-language-models, chatbots, distributed serving; Also covers Inference & Serving, Evaluation & Observability; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.

### When should I choose generative-ai-for-beginners over FastChat?

Choose generative-ai-for-beginners over FastChat when generative-ai-for-beginners is primarily Jupyter Notebook; FastChat is Python; License: generative-ai-for-beginners is MIT, FastChat is Apache-2.0; Tags unique to generative-ai-for-beginners: generativeai, dall-e, ai, generative-ai.

### 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 generative-ai-for-beginners?

LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

### Is FastChat or generative-ai-for-beginners more popular on GitHub?

generative-ai-for-beginners has more GitHub stars (112,866 vs 39,490). Stars measure visibility, not whether either tool fits your constraints.

### Are FastChat and generative-ai-for-beginners open source?

Yes - both are open-source projects on GitHub (FastChat: Apache-2.0, generative-ai-for-beginners: MIT).

### Where can I find alternatives to FastChat or generative-ai-for-beginners?

GraphCanon lists graph-backed alternatives at [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) and [generative-ai-for-beginners alternatives](/tools/microsoft-generative-ai-for-beginners/alternatives) ([FastChat markdown twin](/tools/lm-sys-fastchat/alternatives.md), [generative-ai-for-beginners markdown twin](/tools/microsoft-generative-ai-for-beginners/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/lm-sys-fastchat-vs-microsoft-generative-ai-for-beginners.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, FastChat or generative-ai-for-beginners?

FastChat: Steady. generative-ai-for-beginners: Very active. 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 generative-ai-for-beginners?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FastChat trust report](/tools/lm-sys-fastchat/trust); [generative-ai-for-beginners trust report](/tools/microsoft-generative-ai-for-beginners/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=lm-sys-fastchat`](/api/graphcanon/graph?tool=lm-sys-fastchat)
- 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/_