# LangWatch vs Open WebUI

LangWatch records 52,098 monthly visits with +73% month-over-month growth and Contact for Pricing pricing. Open WebUI records 804,534 monthly visits with -2.8% growth and Freemium pricing.

| Metric | [LangWatch](https://openaitools.app/tool/langwatch) | [Open WebUI](https://openaitools.app/tool/open-webui) |
| :--- | :--- | :--- |
| Website URL | https://www.langwatch.ai | https://openwebui.com |
| Categories | Large Language Models (LLMs), AI Monitor, AI Agent, AI Testing | Large Language Models (LLMs), AI Chatbot, Open Source AI Models, AI Developer Tools |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 52,098 | 804,534 |
| MoM Growth Rate | +73% | -2.8% |
| Primary Market | United States | United States |
| Direct Visits | 28,986 | 299,835 |
| Review Score | 4.6 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## LangWatch

LangWatch started as an open-source LLM observability tool and has grown into an end-to-end platform for AI platform teams. The tracing layer is OpenTelemetry-native, so agents built with LangChain, LangGraph, CrewAI, Mastra, Pydantic AI or the Vercel AI SDK send spans without a rewrite. Traces carry tokens, cost and cache data, can be explored as waterfalls, flame graphs, topology or sequence diagrams, and are searchable through saved views, plain-language search and automatic topic clustering.

On top of tracing, LangWatch layers evaluation and testing. Teams can score a single output or a whole conversation with an LLM judge, custom code or a full workflow; run evals from a notebook or the shared UI; and evaluate live production traffic. Agentic testing simulates realistic text and voice users that push the agent turn by turn, while red-teaming runs adversarial simulations to surface jailbreaks, policy breaks and unsafe tool calls before users do.

More recent additions target day-to-day operations: an AI Gateway routes every provider call (OpenAI, Anthropic, Google, Bedrock, Mistral) through one endpoint with per-person, per-team and per-customer budgets and minimal overhead; coding agents such as Claude Code and Codex can be brought onto the same observability standard with a single command; and Langy turns a product manager's plain-language goal into a scenario test plan and then into pull requests. LangWatch offers cloud, self-hosted and hybrid deployments and states ISO 27001 certification, GDPR compliance and EU data residency options.

**Pricing & Plans:** LangWatch publishes a dedicated pricing page alongside a book-a-demo path, with plans that scale from individual and team use to enterprise. Self-hosting is available as an option, and the project has open-source roots, but specific tier prices, seat limits and credit allowances should be confirmed on the vendor's current pricing page.

- **OpenTelemetry-native tracing:** Full GenAI spec support means traces from LangChain, LangGraph, CrewAI, Mastra, Pydantic AI, the Vercel AI SDK and any OTel-compatible stack land in the same view, with tokens, cost and cache accounted per span.
- **Offline and online evaluations:** Score single outputs or entire conversations with an LLM judge, custom code or a workflow, run evals from a notebook or UI, and evaluate live production traffic in real time.
- **Agentic testing and simulations:** Simulated text and voice users push agents turn after turn in realistic scenarios, runnable locally and in CI, with tools, skills and MCP servers traced and mockable.
- **AI Gateway and budgets:** Route OpenAI, Anthropic, Google, Bedrock, Mistral and other providers through one endpoint using your own keys, with budgets per person, team and customer and around 11 microseconds of overhead.
- **Red-teaming and prompt management:** Adversarial simulations probe for jailbreaks and unsafe tool calls, while prompts are versioned, deployed and A/B tested as code with full history and GitHub sync.

**Strengths:** OpenTelemetry-native with broad framework support, so adoption usually requires no rewrite; Combines tracing, evals, agentic testing, gateway and red-teaming rather than covering only one layer; Self-hosted, hybrid and cloud deployment options plus ISO 27001 and GDPR statements for security reviews; Open-source roots and an active community make the tracing layer approachable for individual developers

**Limitations:** The expanding surface area (gateway, Langy, coding-agent tracking) means more to configure and learn; Enterprise-grade governance features require a sales conversation rather than self-serve signup; Value depends on instrumenting your stack; teams without tracing in place will need setup work

[Profile (Markdown)](https://openaitools.app/tool/langwatch.md)

## Open WebUI

Open WebUI is an open-source, self-hosted interface for working with AI models. Instead of renting access to a single vendor's chatbot, you run the interface on your own hardware or cloud tenancy, then connect whatever models you want: local runtimes such as Ollama, OpenAI-compatible endpoints, Anthropic, or a mix of local and remote. Everything a team produces — conversations, prompts, models, skills and tools — stays in an environment you administer.

The platform has grown well beyond a chat window. Retrieval-augmented generation, web search, document understanding, voice input and output, and vision are built in, and Python tools, functions and pipelines let developers script custom behaviour and share it. On the operations side it offers enterprise features such as SSO, role-based access control, audit logs, data residency options, and on-premises, hybrid or fully air-gapped deployment for regulated environments. White-labeling and custom branding are also available for organizations that want their own look.

Open WebUI is distributed free of charge under an open-source license and can be installed with a single pip or Docker command, with no account required to get running. A separate enterprise offering is available for organizations that want commercial support, compliance guarantees and managed rollout help, which is quoted on contact. A large community maintains a public hub of prompts, models, tools and functions, so much of what teams need is already shared and ready to install.

**Pricing & Plans:** The core platform is free and open source, installable via pip or Docker with no account required. An enterprise tier with support, compliance and deployment assistance is quoted on contact.

- **Any Model, Any Endpoint:** Connect local runtimes like Ollama alongside OpenAI-compatible and Anthropic APIs, and switch between them inside one interface.
- **Retrieval and Search Built In:** RAG over your own documents, web search and citation-aware answers come standard, so responses are grounded in real sources.
- **Python Tools, Functions and Pipelines:** Extend the platform with Python code to add custom tooling, preprocessing, and multi-step pipelines, then share them with others.
- **Enterprise Controls:** SSO, RBAC, audit logs, data residency, and on-premises, hybrid or air-gapped deployment for organisations with strict requirements.
- **Community Hub:** Browse and install prompts, models, skills and tools contributed by hundreds of thousands of community members.

**Strengths:** Free and open source with no account needed to install; Works with local and cloud models through a single interface; Strong privacy posture: your data and models stay on your infrastructure; Extensive enterprise features including SSO, RBAC and audit logs

**Limitations:** Self-hosting requires you to handle servers, updates and backups; Some enterprise capabilities and support sit behind a paid, quote-based tier; Feature depth means a learning curve for non-technical administrators; Local model performance depends heavily on your own hardware

[Profile (Markdown)](https://openaitools.app/tool/open-webui.md)

## Frequently Asked Questions

### How do LangWatch and Open WebUI compare in monthly traffic?

LangWatch has 52,098 monthly visits, while Open WebUI has 804,534. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

LangWatch has a month-over-month growth rate of +73%; Open WebUI has -2.8%.

### How does pricing compare?

LangWatch: Contact for Pricing. LangWatch publishes a dedicated pricing page alongside a book-a-demo path, with plans that scale from individual and team use to enterprise. Self-hosting is available as an option, and the project has open-source roots, but specific tier prices, seat limits and credit allowances should be confirmed on the vendor's current pricing page. Open WebUI: Freemium. The core platform is free and open source, installable via pip or Docker with no account required. An enterprise tier with support, compliance and deployment assistance is quoted on contact.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Functions primarily as a lightweight CLI runtime for local models rather than a full-featured chat interface. | [.md](https://openaitools.app/tool/ollama.md) |
| 2 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 3 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | A free, open-source personal AI agent that learns your projects and works across every messaging app. | [.md](https://openaitools.app/tool/hermes-agent-1.md) |
| 4 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant that runs on your own machine and works from chat apps | [.md](https://openaitools.app/tool/clawdbot.md) |
| 5 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Specializes in visual workflow building and RAG pipelines rather than serving purely as a chat interface. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 6 | [LobeHub](https://openaitools.app/tool/lobehub) | 654,548 | -25% | Freemium | Focuses on collaborative team AI workspaces and plugins, but shares similar open-source architectural goals. | [.md](https://openaitools.app/tool/lobehub.md) |
| 7 | [AnythingLLM](https://openaitools.app/tool/anythingllm) | 512,269 | +12.9% | Freemium | Focuses heavily on privacy-first document chat and local RAG pipelines, but offers fewer general-purpose chat UI features. | [.md](https://openaitools.app/tool/anythingllm.md) |
| 8 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Offers robust multi-provider support and advanced user permission management, but has a slightly different configuration setup. | [.md](https://openaitools.app/tool/librechat.md) |
| 9 | [Jan](https://openaitools.app/tool/jan) | 291,894 | -9.6% | Free | Delivers a desktop-native application for running local models offline easily, but lacks Open WebUI's server-centric multi-user features. | [.md](https://openaitools.app/tool/jan.md) |
| 10 | [Activepieces](https://openaitools.app/tool/activepieces) | 258,553 | +1.5% | Freemium | Open-source AI automation that unifies agents, flows and 770+ app integrations | [.md](https://openaitools.app/tool/activepieces.md) |

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Source: https://openaitools.app/compare/langwatch-vs-open-webui

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