Comparison
LlamaFactory vs FastChat
Verdict
Pick LlamaFactory if llamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization; 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.
Markdown twin · LlamaFactory alternatives · FastChat alternatives
GraphCanon updated today
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Trust & integrity
| Signal | LlamaFactory | FastChat |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1d · github_public_v1 | Steady (71d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1d · github_public_v1 | Not a fork · Organization account As of 1d · github_public_v1 |
| Security (OSV) | No lockfile As of 1d · none | No lockfile As of 1d · none |
Tagline
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
- FastChat
- An open platform for training, serving, and evaluating large language models
Stars
- LlamaFactory
- 73k
- FastChat
- 39k
Forks
- LlamaFactory
- 8.9k
- FastChat
- 4.8k
Open issues
- LlamaFactory
- 1.1k
- FastChat
- 1.0k
Language
- LlamaFactory
- Python
- FastChat
- Python
Adopt for
- LlamaFactory
- LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.
- 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
- LlamaFactory
- -
- FastChat
- -
Runtime
- LlamaFactory
- -
- FastChat
- -
License
- LlamaFactory
- Apache-2.0
- FastChat
- Apache-2.0
Last pushed
- LlamaFactory
- Jul 10, 2026
- FastChat
- May 1, 2026
Categories
- LlamaFactory
- LLM Frameworks, Model Training
- FastChat
- Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- FastChat
- Steady (60%)
Days since push
- LlamaFactory
- 0d
- FastChat
- 71d
Open issues (now)
- LlamaFactory
- 1.1k
- FastChat
- 1.0k
Owner type
- LlamaFactory
- User
- FastChat
- Organization
Full report
- LlamaFactory
- Trust report
- FastChat
- Trust report
Choose LlamaFactory if…
- Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning.
- When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
- More GitHub stars (73k vs 39k) - visibility, not fit.
When NOT to use LlamaFactory
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
- If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
Choose FastChat if…
- Tags unique to FastChat: chatbots, distributed serving, evaluation system.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hiyouga/LlamaFactory) · observed Jul 11, 2026
- GitHub forks (hiyouga/LlamaFactory) · observed Jul 11, 2026
- Last push (hiyouga/LlamaFactory) · observed Jul 10, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (lm-sys/FastChat) · observed Jul 11, 2026
- GitHub forks (lm-sys/FastChat) · observed Jul 11, 2026
- Last push (lm-sys/FastChat) · observed May 1, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LlamaFactory 73k · FastChat 39k (synced Jul 11, 2026).
Common questions
- What is the difference between LlamaFactory and FastChat?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. 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 LlamaFactory over FastChat?
- Choose LlamaFactory over FastChat when Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA; More GitHub stars (73k vs 39k) - visibility, not fit.
- When should I choose FastChat over LlamaFactory?
- Choose FastChat over LlamaFactory when Tags unique to FastChat: chatbots, distributed serving, evaluation system; 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 LlamaFactory?
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
- 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 LlamaFactory or FastChat more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 39,490). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and FastChat open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, FastChat: Apache-2.0).
- Where can I find alternatives to LlamaFactory or FastChat?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and FastChat alternatives (LlamaFactory 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, LlamaFactory or FastChat?
- LlamaFactory: Very active. 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 LlamaFactory and FastChat?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; FastChat trust report.