Compare DeepSeek and Open WebUI on pricing, features, platforms, and ratings — both AI Chatbots tools, Freemium (free chat app; pay-per-token API) vs Freemium…
At a Glance
DeepSeek
Open WebUI
Primary category
AI Chatbots
AI Chatbots
Rating
Not documented
Not documented
Pricing model
Freemium (free chat app; pay-per-token API)
Freemium
Starting price
Free
Free (open source); Enterprise plan available at custom pricing
Free plan
Yes
Yes
Free trial
Not documented
Not documented
Platforms
Web, iOS, Android
Mac, Windows
Team collaboration
Not documented
Not documented
AI features
Yes
Yes
Public API
Yes
Yes
Pricing Compared
Starting price reflects the lowest paid tier, not the full cost for every team size or usage level.
DeepSeek
Chat App — Free N/A
API - DeepSeek-V3 — $0.27 per 1M input tokens / $0.40 per 1M output tokens Pay-as-you-go
API - DeepSeek-R1 — $0.80 per 1M input/output tokens Pay-as-you-go
Open WebUI
Community Edition (Open Source) — Free N/A
Enterprise — Custom Annual/Custom
Pros & Cons
DeepSeek
Pros
Extremely competitive API pricing versus Western frontier labs
Open-weight models allow self-hosting and fine-tuning
Free consumer chat app with a dedicated reasoning mode
Strong benchmark performance on coding and math relative to cost
Cons
Data handling and China-based infrastructure raise governance/privacy concerns for some enterprises and governments
Some governments and organizations restrict or ban the official app on official devices
Less mature ecosystem of official enterprise support compared to OpenAI, Anthropic, or Google
Unofficial third-party 'DeepSeek' apps in app stores can mislead users into paying for features the real app offers free
Open WebUI
Pros
Core software is completely free and open source with no artificial feature limits
Works with virtually any LLM backend, local or cloud-based, rather than locking users into one provider
Extremely feature-rich, covering RAG, voice/video, image generation, and tool calling in one interface
Large and active open-source community with frequent releases
Full data control through self-hosting, appealing to privacy-conscious users and organizations
Cons
Self-hosting requires Docker or server administration knowledge
Fast-moving feature set can mean occasional instability between releases
Branding-preservation terms in the Open WebUI License add licensing nuance compared to fully permissive open-source licenses
Enterprise support tier pricing is not publicly listed and requires custom sales contact
Feature breadth can make initial setup and configuration more involved than a simple chat frontend
Use Cases
DeepSeek
Cost-sensitive AI application development — Build LLM-powered features at a fraction of the token cost of leading closed models.
Self-hosted enterprise LLM deployment — Download open weights and run models on private infrastructure for data control.
General AI assistant — Use the free chat app for research, writing, and coding help.
Open WebUI
Self-hosted ChatGPT-style interface — Individuals and teams run Open WebUI on their own infrastructure to get a full-featured chat interface for local or cloud LLMs without sending data to a third party.
Enterprise internal AI assistant — Organizations deploy Open WebUI with role-based access control and RAG to give employees a controlled, document-aware internal AI assistant.
Multi-model development and testing — Developers use Open WebUI's multi-backend support to compare outputs across different local and cloud LLM providers from one interface.