Free / Open-sourceThe global standard open-source AI hub offering vastly larger model and dataset repositories than ModelScope.

Captum records 4,464 monthly visits with -42.7% month-over-month growth and Free pricing. ModelScope records 3,085,423 monthly visits with +5.1% growth and Free pricing.
Open-source model interpretability for PyTorch
| Dimension / Metric | ||
|---|---|---|
| Official Domain | captum.ai | modelscope.cn |
| Pricing Model | Free | Free |
| Monthly Visits | 4.46K (4,464) | 3.09M (3,085,423) |
| MoM Traffic Delta | -3.33K (-42.7%) |
| +149.05K (+5.1%) |
| Primary Market & Share | 🇺🇸 United States (97.2%) | 🇨🇳 China (82.3%) |
|---|
| Direct Visits / mo | 1.56K | 2.11M |
|---|
| User Rating | 4.7 | 4.5 |
|---|
| Supported Platforms | Website | Website |
|---|
Open-source model interpretability for PyTorch
Integrated Gradients, GradientShap, Saliency, Occlusion, DeepLIFT and related methods behind a single consistent interface.
Works across vision, text and other modalities, so the same interpretability workflow applies to different model types.
Supports most PyTorch model architectures and requires little or no modification to the original network.
An open-source, generic library for interpretability research where new algorithms can be implemented and benchmarked.
Open-source model and dataset hub with one-click online demos
Browse and download thousands of pretrained models and datasets across NLP, vision, audio, and multimodal tasks.
Try models directly in the browser through hosted inference demos without local setup.
Run training and fine-tuning in cloud notebooks with complimentary GPU and CPU resources.
Integrate ModelScope models into your own pipelines using the official Python package and APIs.
Free / Open-sourceThe global standard open-source AI hub offering vastly larger model and dataset repositories than ModelScope.

SpecialistConvenient API gateway for multi-model access, but does not provide ModelScope's open-source model repository or dataset hosting.
#2Free / Open-sourceStreamlined local CLI runtime for running LLMs, but lacks ModelScope's web-based model hosting and dataset discovery.
#3SpecialistSuperior community hub specifically for generative image and media models, but lacks ModelScope's broad NLP and code support.

Robust cloud infrastructure for running open-source models via API, but lacks ModelScope's community-driven model discovery and demo workspace.
Free / Open-sourceBuild, train, and deploy computer vision for the physical world

Free / Open-sourceFeature-rich self-hosted chat interface for local models, but lacks ModelScope's comprehensive repository of raw model weights and datasets.
SpecialistThe data, evaluations and systems behind AI that has to be right.

SpecialistTrack, evaluate, and ship AI models and agents in one connected environment.

Free / Open-sourceUser-friendly desktop app for local model execution, but focuses on client-side running rather than cloud model hubs.

One universal API for 500+ AI models and 1,000+ agentic tools

Free / Open-sourceLabel any data. Evaluate any AI.
Free / Open-sourceThe global standard open-source AI hub offering vastly larger model and dataset repositories than ModelScope.
SpecialistConvenient API gateway for multi-model access, but does not provide ModelScope's open-source model repository or dataset hosting.
Free / Open-sourceStreamlined local CLI runtime for running LLMs, but lacks ModelScope's web-based model hosting and dataset discovery.
Robust cloud infrastructure for running open-source models via API, but lacks ModelScope's community-driven model discovery and demo workspace.
Free / Open-sourceBuild, train, and deploy computer vision for the physical world
Free / Open-sourceFeature-rich self-hosted chat interface for local models, but lacks ModelScope's comprehensive repository of raw model weights and datasets.
SpecialistThe data, evaluations and systems behind AI that has to be right.
SpecialistTrack, evaluate, and ship AI models and agents in one connected environment.
Free / Open-sourceUser-friendly desktop app for local model execution, but focuses on client-side running rather than cloud model hubs.