Comparison
ColossalAI vs FastChat
Verdict
Pick ColossalAI if colossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models; 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 · ColossalAI alternatives · FastChat alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | ColossalAI | FastChat |
|---|---|---|
| Maintenance | Steady (46d since push) As of today · github_public_v1 | Steady (71d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- ColossalAI
- Making large AI models cheaper, faster and more accessible
- FastChat
- An open platform for training, serving, and evaluating large language models
Stars
- ColossalAI
- 41k
- FastChat
- 39k
Forks
- ColossalAI
- 4.5k
- FastChat
- 4.8k
Open issues
- ColossalAI
- 501
- FastChat
- 1.0k
Language
- ColossalAI
- Python
- FastChat
- Python
Adopt for
- ColossalAI
- ColossalAI is a Python library that leverages advanced parallelism techniques for more efficient and cost-effective development of large-scale AI models.
- 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
- ColossalAI
- -
- FastChat
- -
Runtime
- ColossalAI
- -
- FastChat
- -
License
- ColossalAI
- Apache-2.0
- FastChat
- Apache-2.0
Last pushed
- ColossalAI
- May 25, 2026
- FastChat
- May 1, 2026
Categories
- ColossalAI
- Inference & Serving, Model Training
- FastChat
- Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
Trust and health
Days since push
- ColossalAI
- 46d
- FastChat
- 71d
Open issues (now)
- ColossalAI
- 501
- FastChat
- 1.0k
Full report
- ColossalAI
- Trust report
- FastChat
- Trust report
Shared compatibility
- Python · ColossalAI: Python runtime · FastChat: Python runtime
Choose ColossalAI if…
- Tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning.
- You require handling extremely large AI models with massive context windows, such as over 2M tokens.
- More GitHub stars (41k vs 39k) - visibility, not fit.
When NOT to use ColossalAI
- You are working in an environment that does not support Linux OS, as ColossalAI currently offers no support for other operating systems.
- Your current CUDA version is less than 11.0 or your GPU compute capability is below 7.0 (pre-V100/RTX20 series).
- You cannot satisfy the minimum hardware and software requirements specified, such as PyTorch >= 2.2 and Python >= 3.7.
Choose FastChat if…
- Tags unique to FastChat: chatbots, distributed serving, evaluation system, large-language-models.
- Also covers Evaluation & Observability, LLM Frameworks.
- - 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 (hpcaitech/ColossalAI) · observed Jul 11, 2026
- GitHub forks (hpcaitech/ColossalAI) · observed Jul 11, 2026
- Last push (hpcaitech/ColossalAI) · observed May 25, 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: ColossalAI 41k · FastChat 39k (synced Jul 11, 2026).
Common questions
- What is the difference between ColossalAI and FastChat?
- ColossalAI: Making large AI models cheaper, faster and more accessible. 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 ColossalAI over FastChat?
- Choose ColossalAI over FastChat when Tags unique to ColossalAI: ai, big-model, data-parallelism, deep-learning; You require handling extremely large AI models with massive context windows, such as over 2M tokens; More GitHub stars (41k vs 39k) - visibility, not fit.
- When should I choose FastChat over ColossalAI?
- Choose FastChat over ColossalAI when Tags unique to FastChat: chatbots, distributed serving, evaluation system, large-language-models; Also covers Evaluation & Observability, LLM Frameworks; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.
- When should I avoid ColossalAI?
- You are working in an environment that does not support Linux OS, as ColossalAI currently offers no support for other operating systems. Your current CUDA version is less than 11.0 or your GPU compute capability is below 7.0 (pre-V100/RTX20 series). You cannot satisfy the minimum hardware and software requirements specified, such as PyTorch >= 2.2 and Python >= 3.7.
- 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 ColossalAI or FastChat more popular on GitHub?
- ColossalAI has more GitHub stars (41,408 vs 39,490). Stars measure visibility, not whether either tool fits your constraints.
- Are ColossalAI and FastChat open source?
- Yes - both are open-source projects on GitHub (ColossalAI: Apache-2.0, FastChat: Apache-2.0).
- Where can I find alternatives to ColossalAI or FastChat?
- GraphCanon lists graph-backed alternatives at ColossalAI alternatives and FastChat alternatives (ColossalAI 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, ColossalAI or FastChat?
- ColossalAI: Steady. 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 ColossalAI and FastChat?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ColossalAI trust report; FastChat trust report.