DagsHub

Free plan APILinuxMacSelf-hostedWebWindows

What DagsHub is

DagsHub helps developers and teams manage machine-learning work from data collection and dataset curation through annotation, experimentation, and model management. Its workspace can bring code, data, experiments, models, pipelines, and annotations together. The platform is designed for text, images, audio, video, documents, medical imaging, and binary files. For experiment tracking, it supports run comparisons, metrics and parameter visualization, real-time progress monitoring, and reproducibility. Data Engine provides curation, visualization, quality review, lineage, hard-example mining, labeling, auto-labeling, and data streaming. Integrations include GitHub, Google Colab, DVC, MLflow, Jenkins, Label Studio, Google Drive, Weights & Biases, Hugging Face, and others; hosted projects also have full support for MLflow and Label Studio APIs. DagsHub hosts data but does not supply compute, so projects use local, cloud, or edge infrastructure. The Individual plan is free with limits including 100 private tracked experiments, two private collaborators, and 20GB storage. Paid pricing starts at $99/user/mo billed annually, and a 14-day trial is available.

Who it suits

It suits developers and teams organizing multimodal machine-learning datasets, experiments, annotations, and models. Users need separate local, cloud, or edge infrastructure for compute.

What it does well

Brings code, data, experiments, and models together.
Supports multimodal datasets including video and medical imaging.
Data Engine includes lineage and hard-example mining.
Provides MLflow and Label Studio API support.
Offers a free Individual plan.

What to know first

DagsHub does not provide compute resources.
Free private experiments are limited to 100.
Free storage is limited to 20GB.

Limits

The free Individual plan allows up to 100 tracked experiments in private repositories, two private collaborators, and 20GB of DagsHub Storage. The Team plan lists 1TB or 2 million files.

Plans

Plan	Billed and limits	Price
Individual	$0 per user/month · Unlimited public repositories and collaborators · unlimited private repositories for non-commercial use · 100 private tracked experiments · 2 private-project collaborators · 20GB storage	Free
Individual	$0 per user/month · Unlimited public repositories and collaborators · unlimited private repositories for non-commercial use · 100 private tracked experiments · 2 private-project collaborators · 20GB storage	Free
Team	$119 per user/month · Unlimited private repositories · multimodal annotation and auto-labeling · own-storage connections · Label Studio compatibility · team RBAC · priority support · 1TB or 2 million files	$119 a month
Team	$99 per user/month · Unlimited private repositories · multimodal annotation and auto-labeling · own-storage connections · Label Studio compatibility · team RBAC · priority support · 1TB or 2 million files	$99 a month
Enterprise	Custom quote · Petabyte-scale data · cluster model deployment · VPC/air-gapped on-premise installation · SSO/LDAP/OIDC RBAC · OpenShift · resource controls · SLA and enterprise support	On request

As dagshub.com lists them, read 15 Oct 2026. The maker's own page has the final word.

Getting started

Open the DagsHub website.
Choose web, API, or a self-hosted deployment route.
Start with the free Individual plan or use the 14-day trial.
Bring project code, data, experiments, models, pipelines, and annotations into the workspace.
Connect tools such as GitHub, DVC, MLflow, or Label Studio as needed.

Verdict

DagsHub provides a shared workspace for machine-learning data and project lifecycle management, with curation and experiment tools. Its free tier has stated private-use limits, and compute must come from separate infrastructure.

Questions

Is DagsHub free?

Yes. Its Individual plan is free and includes unlimited public repositories and unlimited private repositories for non-commercial use, alongside limits of 100 private tracked experiments, two private collaborators, and 20GB storage.

How much does DagsHub cost?

Paid pricing starts at $99/user/mo billed annually. The listed Team plan is $119 a month; Enterprise uses a custom quote.

Is there a free trial?

Yes. DagsHub offers a 14-day trial.

Which platforms does DagsHub support?

The listed platforms are API, self-hosted, and web.

Does DagsHub provide compute?

No. DagsHub hosts data, while compute uses the customer's local, cloud, or edge infrastructure.

What integrations does DagsHub offer?

Listed integrations include GitHub, Google Colab, DVC, MLflow, Jenkins, Label Studio, Google Drive, Weights & Biases, Hugging Face, Apple MLX-LM, PyCaret, Giskard, and New Relic.

Facts from DagsHub's own pages

Annotation: The platform supports multimodal annotation and auto-labeling, with Label Studio compatibility on the Team plan. · dagshub.com, 15 Oct 2026
API: DagsHub publishes an API with interactive endpoint testing, token authentication and Basic Authentication using a username and token. · dagshub.com, 15 Oct 2026
API support: DagsHub offers full support for the MLflow and Label Studio APIs for projects hosted on DagsHub. · dagshub.com, 30 Sept 2026
CLI: The client supplies a dagshub command-line interface for login, repository creation, upload, download, DVC setup and version reporting. · dagshub.com, 15 Oct 2026
Client licence: The public DagsHub client repository is marked MIT licensed. · github.com, 15 Oct 2026
Company founders: Crunchbase names Dean Pleban as co-founder and CEO and Guy Smoilovsky as CTO and co-founder. · crunchbase.com, 15 Oct 2026
Company headquarters: LinkedIn lists San Francisco as headquarters, while Crunchbase lists Tel Aviv, Israel. · linkedin.com, 15 Oct 2026
Company legal name: Crunchbase identifies the legal entity as DagsHub Inc. · crunchbase.com, 15 Oct 2026
Company size: LinkedIn lists DagsHub as privately held with 11–50 employees. · linkedin.com, 15 Oct 2026
Compute limitation: The documentation says DagsHub does not provide compute resources, so training and deployment run on infrastructure supplied by the customer. · dagshub.com, 15 Oct 2026
Data and code versioning: The product combines Git and DVC-based versioning so code and large data files can be managed together. · github.com, 15 Oct 2026
Data Engine: Data Engine provides APIs and tools for connecting sources, enriching metadata, querying, visualizing, annotating and producing dataloaders. · dagshub.com, 15 Oct 2026
Deployment options: Enterprise installations can run on-premises, in a VPC, in air-gapped environments, and in OpenShift environments. · dagshub.com, 30 Sept 2026
Documentation and support: DagsHub provides quick starts, feature guides, API reference, Python client reference, CLI reference, tutorials, FAQ material and Discord/community support. · dagshub.com, 15 Oct 2026
Enterprise security: DagsHub states that it adheres to ISO 27001 and ISO 9001 standards and supports custom OIDC and LDAP authentication for SSO. · dagshub.com, 30 Sept 2026
Experiment tracking: Experiments can be tracked with Git, DVC experiments or MLflow, including metrics, parameters and artifacts. · github.com, 15 Oct 2026
Free-plan limits: The Individual plan allows up to 100 tracked experiments in private repositories, up to 2 private collaborators, and 20GB of DagsHub Storage. · dagshub.com, 30 Sept 2026
Funding: CB Insights reports $4.5 million raised across five rounds, including a $2.5 million seed round dated March 1, 2022. · cbinsights.com, 15 Oct 2026
Generated API clients: DagsHub links auto-generated clients for multiple languages but warns that they have not been fully tested. · dagshub.com, 15 Oct 2026
GitHub synchronization: GitHub repositories can sync through webhooks, while GitHub pull requests and issues are shown in DagsHub and vice versa. · dagshub.com, 15 Oct 2026
Hosted scope: DagsHub hosts data but does not currently provide compute resources, relying on the user's local, cloud, or edge infrastructure. · dagshub.com, 30 Sept 2026
Independent API limitation: The same evaluation reported that MLflow run information stored in DagsHub could not then be retrieved programmatically through a Python API. · smiffy.de, 15 Oct 2026
Independent documentation finding: The evaluation described the getting-started guide and Discord as useful but said users often need DVC and MLflow documentation as well. · smiffy.de, 15 Oct 2026
Independent performance finding: A university evaluation reported that logging 1,000 MLflow metrics to DagsHub took 291 seconds, or 11 seconds in batch mode. · smiffy.de, 15 Oct 2026