Clear.ml vs Hugging Face (2026): Pricing, Features & Which to Choose

Who comes out ahead

Based only on the facts in our directory. The right pick still depends on the job you need done.

Lower starting price
Hugging Face
From $9/mo against from $15/mo
Free plan
Tie
Both have one
Higher rating
Hugging Face
4.3 against 4.5
Same job?
Yes
Both are AI Infrastructure & Agent Tooling tools

Side by side

Compared on	Clear.ml	Hugging Face
Our rating	4.3	4.5Better
Starts at	$15/mo	$9/moBetter
Free plan	Yes	Yes
Category	AI Infrastructure & Agent Tooling	AI Infrastructure & Agent Tooling
Plans	From $15/mo	Hub$0 PRO$9/mo Team$20 per user/mo EnterpriseFrom $50 per user/mo, through sales with an annual commitment Storage$12/TB/mo public, $18/TB/mo private; cheaper from 50TB
Key features	Automatic experiment tracking (code, hyperparameters, datasets, artifacts) Data versioning on top of existing object storage Pipeline orchestration for MLOps and LLMOps workflows Model-serving infrastructure for production deployment GPU resource management via an infrastructure control plane	Public hub hosting hundreds of thousands of open models, datasets, and Spaces Transformers library, a widely-used open-source toolkit for NLP and multimodal models Inference Providers and Inference Endpoints for deploying models without managing GPU infrastructure Spaces for hosting interactive model demos on shared or dedicated hardware Team and Enterprise plans adding SSO, audit logs, and private storage
Pros	Free, self-hostable open-source core avoids vendor lock-in entirely Five-module coverage spans the full ML lifecycle instead of experiment tracking Near decade of operating history and enterprise customers (NVIDIA, Samsung, Bosch) back its stability	Free, open Hub remains the default place the ML community publishes models, so discovery and community trust come built in Transformers library compatibility means most open models work with existing code with minimal changes Inference pricing scales from a $9/month individual plan up to per-GPU-hour enterprise deployment, covering hobbyists through production teams
Cons	Five-module breadth means a learning curve to use the platform to its full extent Self-hosting the open-source version requires infrastructure and DevOps effort a hosted competitor wouldn't Enterprise and Scale tier pricing isn't published, requiring a sales conversation	GPU-backed Inference Endpoints get higher-priced fast at higher-tier hardware, with H100 at $10/GPU/hour Sheer scale of the Hub, with largely unmoderated uploads, makes model quality and licensing inconsistent across listings Enterprise-grade support and compliance features sit behind the $50/user/month Enterprise tier
Company	ClearML, founded 2016	Hugging Face, Inc., founded 2016

Prices come from each vendor's pricing page, last checked 20260810. Check the vendor before you buy.

FAQ

Questions people ask

Is Clear.ml better than Hugging Face?

In our reviews Clear.ml scores 4.3 and Hugging Face scores 4.5. The better pick depends on the job. Clear.ml: Open-source MLOps platform tracking experiments, managing data, and orchestrating pipelines across the ML lifecycle. Hugging Face: Open platform for hosting, sharing, and deploying machine learning models.

Which is cheaper, Clear.ml or Hugging Face?

Hugging Face has the lower starting price: from $15/mo for Clear.ml and from $9/mo for Hugging Face.

Do Clear.ml and Hugging Face have free plans?

Yes, both have a free plan.

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