# Arize AI vs Open WebUI

Arize AI records 249,028 monthly visits with +3.2% month-over-month growth and Paid, Contact for Pricing pricing. Open WebUI records 804,534 monthly visits with -2.8% growth and Freemium pricing.

| Metric | [Arize AI](https://openaitools.app/tool/arize-com) | [Open WebUI](https://openaitools.app/tool/open-webui) |
| :--- | :--- | :--- |
| Website URL | https://arize.com | https://openwebui.com |
| Categories | Large Language Models (LLMs), AI Agent, AI Monitor, AI Developer Tools | Large Language Models (LLMs), AI Chatbot, Open Source AI Models, AI Developer Tools |
| Pricing Model | Paid, Contact for Pricing | Freemium |
| Monthly Visits | 249,028 | 804,534 |
| MoM Growth Rate | +3.2% | -2.8% |
| Primary Market | United States | United States |
| Direct Visits | 107,838 | 299,835 |
| Review Score | 4.6 | 4.4 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## Arize AI

Arize is an AI engineering platform built for teams that run generative AI in production. It is split into two products: Arize AX, a managed environment for agent observability, evaluation, and experimentation, and Phoenix, an open-source tracing and evaluation library that teams can self-host when they need full data control. Both rely on OpenInference, the open-source semantic convention for generative AI tracing that the Arize team founded and that is built on OpenTelemetry.

The workflow follows three questions. Observe answers what an agent actually did by capturing every span, trace, and session; Evaluate answers whether quality is improving or regressing using span-level, trace-level, and session-level evals; Learn answers whether a proposed change will help by letting teams test prompts and harnesses before rollout. A datastore for GenAI traces (ADB) keeps data in open formats that connect to warehouses such as BigQuery, Databricks, and Snowflake, and an in-app AI engineering agent named Alyx surfaces issues and drafts review-ready fixes.

The platform integrates with dozens of models, frameworks, and tools, including OpenAI, Anthropic, Google, Amazon Bedrock, LangChain, LangGraph, LlamaIndex, CrewAI, and DSPy. Arize publishes compliance certifications including SOC 2 Type II, ISO 27001, PCI DSS, HIPAA, and GDPR, and supports cloud, hybrid, and self-hosted deployment.

**Pricing & Plans:** Arize uses a paid model with a free entry point: teams can start free or book a demo, while enterprise-scale usage, deployment options, and support are quoted through a contact-sales process. The open-source Phoenix project is free to self-host.

- **End-to-end tracing:** Capture spans, traces, and sessions across agents and LLM calls using OpenInference conventions built on OpenTelemetry, so instrumentation stays portable.
- **Scalable evaluation framework:** Run evaluations at span, trace, and session level to grade retrieval quality, tool use, and final answers across large production datasets.
- **Alyx AI engineering agent:** An in-product agent that inspects traces, diagnoses likely root causes, and proposes fixes that engineers can review before shipping.
- **Phoenix open-source toolkit:** Self-host the leading open-source tracing and eval tool when you need to keep trace data inside your own infrastructure.
- **Warehouse-native trace storage:** ADB stores traces in open formats that connect natively to BigQuery, Databricks, or Snowflake for joint analytics with business data.

**Strengths:** Covers the full loop of observe, evaluate, and improve rather than stopping at dashboards; Backed by OpenInference and OpenTelemetry standards, limiting vendor lock-in on trace formats; Strong enterprise posture with SOC 2, ISO 27001, HIPAA, and GDPR coverage plus self-hosting options; Integrates with a very wide set of models, frameworks, and agent SDKs

**Limitations:** Self-serve pricing is not published, so cost requires a sales conversation; The breadth of features can be overwhelming for small teams shipping their first LLM feature; Full value depends on disciplined instrumentation across the whole application

[Profile (Markdown)](https://openaitools.app/tool/arize-com.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 Arize AI and Open WebUI compare in monthly traffic?

Arize AI has 249,028 monthly visits, while Open WebUI has 804,534. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Arize AI has a month-over-month growth rate of +3.2%; Open WebUI has -2.8%.

### How does pricing compare?

Arize AI: Paid, Contact for Pricing. Arize uses a paid model with a free entry point: teams can start free or book a demo, while enterprise-scale usage, deployment options, and support are quoted through a contact-sales process. The open-source Phoenix project is free to self-host. 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 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Excels at experiment tracking and model registry workflows, but is less purpose-built for real-time LLM production observability. | [.md](https://openaitools.app/tool/prompts.md) |
| 10 | [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) |

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

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