OpenCode ZenOpenCode
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Related Products
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About
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.
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About
OpenCode Zen is an AI gateway that gives coding agents access to a curated set of reliable, optimized AI models tested and verified by the OpenCode team. It is designed to solve the inconsistency that comes from the large number of available models and the different ways providers configure and serve them, which can lead to varying performance and quality. The team tests a select group of models, works directly with model teams and providers to determine how they should be run, verifies that they are served correctly, and benchmarks each model-provider combination before recommending it. Zen works like any other provider in OpenCode: users connect with an API key and can view the recommended model list directly in the interface. It is completely optional and can also be used with other coding agents, helping developers avoid lock-in while still accessing validated model configurations.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Companies looking for an open source platform solution for the machine learning lifecycle
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Audience
Developers and coding-agent users seeking to access tested, benchmarked AI models with consistent performance across providers and tools
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationMLflow
Founded: 2018
United States
mlflow.org
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Company InformationOpenCode
Founded: 2025
United States
opencode.ai/zen
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Alternatives |
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Categories |
Categories |
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Integrations
Apache Spark
Supported
Aporia
Supported
Axolotl
Supported
Azure Data Science Virtual Machines
Supported
Azure Machine Learning
Supported
Determined AI
Supported
Docker
Supported
HoneyHive
Supported
Kimi K3
Not Supported
Kubernetes
Supported
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Integrations
Apache Spark
Not Supported
Aporia
Not Supported
Axolotl
Not Supported
Azure Data Science Virtual Machines
Not Supported
Azure Machine Learning
Not Supported
Determined AI
Not Supported
Docker
Not Supported
HoneyHive
Not Supported
Kimi K3
Supported
Kubernetes
Not Supported
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