# LiteLLM vs ModelScope LiteLLM records 576,967 monthly visits with +7.9% month-over-month growth and Freemium, Contact for Pricing pricing. ModelScope records 3,085,423 monthly visits with +5.1% growth and Free pricing. | Metric | [LiteLLM](https://openaitools.app/tool/litellm) | [ModelScope](https://openaitools.app/tool/modelscope-community) | | :--- | :--- | :--- | | Website URL | https://litellm.ai | https://www.modelscope.cn | | Categories | AI API, Large Language Models (LLMs), AI Developer Tools, Open Source AI Models | Open Source AI Models, AI Models, AI Developer Tools, Large Language Models (LLMs) | | Pricing Model | Freemium, Contact for Pricing | Free | | Monthly Visits | 576,967 | 3,085,423 | | MoM Growth Rate | +7.9% | +5.1% | | Primary Market | United States | China | | Direct Visits | 228,967 | 2,108,104 | | Review Score | 4.8 | 4.5 | | Saved Count | 5 | 0 | | Supported Platforms | Website | Website | ## LiteLLM LiteLLM is an open-source AI gateway and Python SDK designed to remove vendor lock-in from LLM applications. The SDK lets you call models from OpenAI, Anthropic, Google Vertex AI, Bedrock, Mistral, Azure and dozens of other providers using the same OpenAI-style request format, so switching models is a configuration change rather than a code rewrite. The same project ships an AI Gateway (often called the proxy) that turns that abstraction into a shared service for an entire organization. That gateway is where most platform teams find the value. It issues virtual keys scoped by team, project or application, tracks spend per key against budgets, applies rate limits (TPM and RPM), and exposes dashboards for request volume, token usage and cost per model. Routing features include load balancing across deployments, automatic fallbacks when a provider fails, retries and budget-based rerouting, plus guardrails for PII masking, prompt-injection detection and secret detection. The project is genuinely open source with the code on GitHub (BerriAI/litellm) and a very active community. Enterprise features add SSO, audit logs, and support for agents and MCP servers through the same gateway. Notably, LiteLLM supports day-zero access to new models so teams can adopt them as soon as they ship, and it can also serve self-hosted, fine-tuned and internal models behind the same key. Companies cited on the site include NVIDIA, Netflix, Okta, Lemonade and AT&T. **Pricing & Plans:** Freemium and open source. The self-hosted LiteLLM gateway and SDK are free under an open-source licence, and a free tier lets you get started immediately. Enterprise plans with SSO, audit logs, SLAs and advanced support are quoted on request via the sales team. - **OpenAI-compatible API for 100+ LLMs:** Call 100+ providers and 1,800+ models using one request format, so you can swap models without changing application code. - **Virtual keys, teams and budgets:** Issue scoped keys per team, project or app, set monthly spend caps and see exactly who is driving usage and cost. - **Routing, load balancing and fallbacks:** Distribute traffic across deployments, retry on failure and automatically fall back to another model or provider when one goes down. - **Observability and spend tracking:** Dashboards for request volume, tokens and cost per model, with support for logging and analytics integrations. - **Guardrails and policy controls:** Plug in PII masking, prompt-injection detection and secret-detection guardrails, and manage policies centrally instead of in every app. **Strengths:** Truly open source with a large GitHub community and self-hosting option; Very broad provider coverage with an OpenAI-compatible interface; Enterprise-grade controls: virtual keys, budgets, rate limits and audit logs; Day-zero support for new models and easy fallback when providers fail **Limitations:** Self-hosting means you own deployment, upgrades and uptime; Feature depth varies between the free open-source version and enterprise plan; The breadth of configuration options can be overwhelming for small projects [Profile (Markdown)](https://openaitools.app/tool/litellm.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 LiteLLM and ModelScope compare in monthly traffic? LiteLLM has 576,967 monthly visits, while ModelScope has 3,085,423. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? LiteLLM has a month-over-month growth rate of +7.9%; ModelScope has +5.1%. ### How does pricing compare? LiteLLM: Freemium, Contact for Pricing. Freemium and open source. The self-hosted LiteLLM gateway and SDK are free under an open-source licence, and a free tier lets you get started immediately. Enterprise plans with SSO, audit logs, SLAs and advanced support are quoted on request via the sales team. 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 | [OrcaRouter](https://openaitools.app/tool/orcarouter) | 975,300 | -5.2% | Freemium | Delivers automated model failover and budget governance through an API gateway, but with less open-source customization. | [.md](https://openaitools.app/tool/orcarouter.md) | | 7 | [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) | | 8 | [ZenMux](https://openaitools.app/tool/zenmux) | 444,394 | +16.7% | Freemium, Paid | Unified LLM gateway with failover and analytics, but offers less robust open-source developer SDK support. | [.md](https://openaitools.app/tool/zenmux.md) | | 9 | [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) | | 10 | [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) | --- Source: https://openaitools.app/compare/litellm-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)