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Comparison

determined vs FastChat

Verdict

Pick determined if determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications; 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 · determined alternatives · FastChat alternatives

GraphCanon updated 2w

determined logo

determined

determined-ai/determined

3.2kpushed Mar 20, 2025
vs
FastChat logo

FastChat

lm-sys/FastChat

40kpushed May 1, 2026

Trust & integrity

SignaldeterminedFastChat
Maintenance
Dormant (501d since push)
As of 3w · github_public_v1
Slowing (98d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
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

Tagline

determined
An open-source machine learning platform for distributed training and resource management.
FastChat
An open platform for training, serving, and evaluating large language models

Stars

determined
3.2k
FastChat
40k

Forks

determined
373
FastChat
4.8k

Open issues

determined
108
FastChat
1.0k

Language

determined
Go
FastChat
Python

Adopt for

determined
Determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications.
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

determined
-
FastChat
-

Runtime

determined
-
FastChat
-

License

determined
Apache-2.0
FastChat
Apache-2.0

Last pushed

determined
Mar 20, 2025
FastChat
May 1, 2026

Categories

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

Trust and health

Maintenance

determined
Dormant (18%)
FastChat
Slowing (36%)

Days since push

determined
501d
FastChat
98d

Open issues (now)

determined
108
FastChat
1.0k

OSV dependency advisories

determined
Published findings
FastChat
No lockfile (source not queried)

Full report

determined
Trust report
FastChat
Trust report

Shared compatibility

  • Python · determined: Python runtime · FastChat: Python runtime

Choose determined if…

  • determined is primarily Go; FastChat is Python.
  • Pricing: The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here..
  • Requirements: Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`..
  • Tags unique to determined: data-science, deep-learning, distributed-training, hyperparameter-optimization.
  • You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks.

When NOT to use determined

  • Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow.
  • Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed.

Choose FastChat if…

  • FastChat is primarily Python; determined is Go.
  • Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models.
  • Also covers Inference & Serving, 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 on cards: determined 3.2k · FastChat 40k (synced Aug 4, 2026).

Common questions

What is the difference between determined and FastChat?
determined: An open-source machine learning platform for distributed training and resource management.. 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 determined over FastChat?
Choose determined over FastChat when determined is primarily Go; FastChat is Python; Pricing: The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here.; Requirements: Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via det deploy.; Tags unique to determined: data-science, deep-learning, distributed-training, hyperparameter-optimization; You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks.
When should I choose FastChat over determined?
Choose FastChat over determined when FastChat is primarily Python; determined is Go; Tags unique to FastChat: chatbots, distributed-serving, evaluation system, large language models; Also covers Inference & Serving, LLM Frameworks; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench.
When should I avoid determined?
Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow. Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed.
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 determined or FastChat more popular on GitHub?
FastChat has more GitHub stars (39,517 vs 3,227). Stars measure visibility, not whether either tool fits your constraints.
Are determined and FastChat open source?
Yes - both are open-source projects on GitHub (determined: Apache-2.0, FastChat: Apache-2.0).
Where can I find alternatives to determined or FastChat?
GraphCanon lists graph-backed alternatives at determined alternatives and FastChat alternatives (determined 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, determined or FastChat?
determined: Dormant. 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 determined and FastChat?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: determined trust report; FastChat trust report.

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