Comet.ml Alternatives (January 2026)

Track, compare, and reproduce your ML experiments with Comet's machine learning platform. Leverage insights to build better models, faster.

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1.
Weights & Biases: The AI Developer Platform
https://wand
.ai/

Weights & Biases is the leading AI developer platform to train and fine-tune models, manage models from experimentation to production, and track and evaluate GenAI applications powered by LLMs.

2.
Distributed Deep Learning and Hyperparameter Tuning Platform | Determined AI
https://determine
.ai/

Open source deep learning training platform that enables data scientists to train better models, with built-in hyperparameter tuning and distributed training

3.
Seldon, MLOps for the Enterprise.
http://www.seldo
.io/

Serve, Monitor, Manage and Scale your machine learning operations with our enterprise ready MLOps tools. Get a demo or start a trial today. %

4.
neptune.ai | The experiment tracker for foundation model training
https://neptun
.ai/

Monitor months-long jobs and visualize massive amounts of data in almost real-time — with 100% accuracy. Without crashing the UI.

5.
AI Observability & LLM Evaluation Platform | ML Model Monitoring & ML Infrastructure
https://ariz
.com/

Increase model velocity and improve AI outcomes with Arize AI’s ML observability platform. Discover issues, diagnose problems, and improve performance.

6.
Valohai | The Scalable MLOps Platform
https://valoha
.com/

The Valohai MLOps platform enables CI/CD for ML and pipeline automation on-prem and any-cloud.

7.
Edge Impulse - The Leading Edge AI Platform
https://www.edgeimpuls
.com/

Edge Impulse is the leading development platform for machine learning on edge devices.

8.
Saturn Cloud | #1 Rated ML Platform
https://saturnclou
.io/

Data science and machine learning in the cloud in seconds—Use R and Python with GPUs, Dask clusters, and more

9.
Hugging Face – The AI community building the future.
https://huggingfac
.co/

We’re on a journey to advance and democratize artificial intelligence through open source and open science.