# ClearML vs ModelScope

ClearML records 20,123 monthly visits with -60.9% month-over-month growth and Contact for Pricing pricing. ModelScope records 3,085,423 monthly visits with +5.1% growth and Free pricing.

| Metric | [ClearML](https://openaitools.app/tool/clear-ml) | [ModelScope](https://openaitools.app/tool/modelscope-community) |
| :--- | :--- | :--- |
| Website URL | https://clear.ml | https://www.modelscope.cn |
| Categories | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Workflow | Open Source AI Models, AI Models, AI Developer Tools, Large Language Models (LLMs) |
| Pricing Model | Contact for Pricing | Free |
| Monthly Visits | 20,123 | 3,085,423 |
| MoM Growth Rate | -60.9% | +5.1% |
| Primary Market | Germany | China |
| Direct Visits | 6,667 | 2,108,104 |
| Review Score | 4.3 | 4.5 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## ClearML

ClearML packages the operational side of AI into one platform. The Infrastructure Control Plane connects and manages GPU resources across on-premises, cloud, and hybrid environments, adding multi-tenancy, role-based access control, quota management, fractional GPUs, priority-based scheduling, and usage-based billing for chargebacks. The goal is straightforward: raise utilization of the hardware a company already owns and make GPU-as-a-Service practical for internal teams.

The AI Development Center is the builder-facing half. It provides a workbench with an integrated development environment for coding, testing, and deploying models, plus data integration, experiment tracking, automation, dashboards, pipelines, a model repository, and CI/CD hooks. Because it is cloud-agnostic and silicon-agnostic, teams can keep their existing tooling while gaining a consistent workflow from research through production.

The GenAI App Engine handles deployment of large language models onto those same clusters. ClearML manages networking, authentication, access control, and monitoring so a team can launch a secure LLM API with minimal setup, fine-tune an off-the-shelf model, or wire up data ingestion and vector databases. The platform is sold on an enterprise model — demos and quotes rather than self-serve checkout — and it publishes an annual State of AI Infrastructure report.

**Pricing & Plans:** ClearML is sold as an enterprise platform with demo-led and quote-based pricing; a free starting tier is advertised alongside Request Demo calls to action. Specific seat, GPU, or usage rates are not published, so buyers should contact sales for a quote.

- **Infrastructure Control Plane:** Connect and govern GPU clusters across on-prem, cloud, and hybrid setups with multi-tenancy, RBAC, quota management, fractional GPUs, and priority-based scheduling.
- **AI Development Center:** A builder workbench with an integrated development environment plus experiment tracking, data integration, dashboards, pipelines, model repository, and CI/CD integration.
- **GenAI App Engine:** Deploy LLMs onto existing clusters with handled networking, authentication, and security, so teams can launch secure model APIs with minimal manual configuration.
- **Usage-based billing and chargebacks:** Granular cost tracking by compute hours, storage, and API calls lets IT teams allocate spend back to the projects and departments that consume it.
- **Vendor- and cloud-agnostic design:** Works across different silicon, clouds, and environments, avoiding lock-in while keeping one consistent workflow from experimentation to production.

**Strengths:** One platform covers cluster management, MLOps, and LLM deployment rather than stitching three vendors together; Strong GPU utilization, scheduling, and chargeback features aimed squarely at cost control; Cloud-, silicon-, and vendor-agnostic, which limits lock-in for mixed infrastructure; Meaningful adoption footprint with enterprise references, documentation, and training guides

**Limitations:** Enterprise, quote-based sales means no transparent public pricing and a longer procurement cycle; The breadth of the platform can be heavy to adopt for small teams that only need experiment tracking; Self-hosting and cluster integration work assumes real infrastructure and platform engineering capacity

[Profile (Markdown)](https://openaitools.app/tool/clear-ml.md)

## ModelScope

ModelScope, also known as the Magic Model community, is an open-source AI model and dataset hub built and maintained with Alibaba. It gathers models for natural language processing, computer vision, speech, multimodal generation, and more, letting researchers and developers browse, download, and evaluate them in one place. Each model typically ships with documentation, a model card, and an interactive online demo so you can try it directly in the browser before installing anything.

Beyond hosting files, ModelScope functions as a full model-as-a-service workspace. Users get free online notebooks with GPU and CPU resources for training and fine-tuning, plus hosted inference endpoints and a Python library that integrates with common deep learning frameworks. Community features such as model collections, benchmarks, competitions, and discussion boards make it a social hub as much as a repository.

The platform is free to use, with compute credits and hosted serving tied to account usage. Its close association with Alibaba Cloud means it also serves as a practical gateway for teams who want to move from experimentation to production deployment within a familiar cloud ecosystem.

**Pricing & Plans:** Free to use. Browsing, downloading models and datasets, and running online demos are free; free GPU/CPU notebook credits and hosted inference are available, with additional cloud resources tied to Alibaba Cloud services.

- **Model & Dataset Hub:** Browse and download thousands of pretrained models and datasets across NLP, vision, audio, and multimodal tasks.
- **One-click Online Demos:** Try models directly in the browser through hosted inference demos without local setup.
- **Free Notebook Compute:** Run training and fine-tuning in cloud notebooks with complimentary GPU and CPU resources.
- **Python Library & SDK:** Integrate ModelScope models into your own pipelines using the official Python package and APIs.
- **Community & Benchmarks:** Join competitions, publish model cards, and compare results through community benchmarks and leaderboards.

**Strengths:** Huge, free catalog of models and datasets; Built-in online demos require no installation; Complimentary GPU/CPU notebook compute; Strong integration with Alibaba Cloud for scaling

**Limitations:** Much of the documentation is Chinese-first; Hosted features may require an account and regional access; Interface can feel dense for newcomers

[Profile (Markdown)](https://openaitools.app/tool/modelscope-community.md)

## Frequently Asked Questions

### How do ClearML and ModelScope compare in monthly traffic?

ClearML has 20,123 monthly visits, while ModelScope has 3,085,423. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

ClearML has a month-over-month growth rate of -60.9%; ModelScope has +5.1%.

### How does pricing compare?

ClearML: Contact for Pricing. ClearML is sold as an enterprise platform with demo-led and quote-based pricing; a free starting tier is advertised alongside Request Demo calls to action. Specific seat, GPU, or usage rates are not published, so buyers should contact sales for a quote. ModelScope: Free. Free to use. Browsing, downloading models and datasets, and running online demos are free; free GPU/CPU notebook credits and hosted inference are available, with additional cloud resources tied to Alibaba Cloud services.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Hugging Face](https://openaitools.app/tool/hugging-face) | 31,232,542 | +0.1% | Freemium, Paid | The global standard open-source AI hub offering vastly larger model and dataset repositories than ModelScope. | [.md](https://openaitools.app/tool/hugging-face.md) |
| 2 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Convenient API gateway for multi-model access, but does not provide ModelScope's open-source model repository or dataset hosting. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 3 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Streamlined local CLI runtime for running LLMs, but lacks ModelScope's web-based model hosting and dataset discovery. | [.md](https://openaitools.app/tool/ollama.md) |
| 4 | [Civitai](https://openaitools.app/tool/civitai) | 6,963,136 | +12.8% | Freemium | Superior community hub specifically for generative image and media models, but lacks ModelScope's broad NLP and code support. | [.md](https://openaitools.app/tool/civitai.md) |
| 5 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Robust cloud infrastructure for running open-source models via API, but lacks ModelScope's community-driven model discovery and demo workspace. | [.md](https://openaitools.app/tool/together-ai.md) |
| 6 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Feature-rich self-hosted chat interface for local models, but lacks ModelScope's comprehensive repository of raw model weights and datasets. | [.md](https://openaitools.app/tool/open-webui.md) |
| 7 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | AI data infrastructure for building production-grade models | [.md](https://openaitools.app/tool/super-annotate.md) |
| 8 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 9 | [Jan](https://openaitools.app/tool/jan) | 291,894 | -9.6% | Free | User-friendly desktop app for local model execution, but focuses on client-side running rather than cloud model hubs. | [.md](https://openaitools.app/tool/jan.md) |
| 10 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) |

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Source: https://openaitools.app/compare/clear-ml-vs-modelscope-community

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)