Flowise vs Baseten
Side-by-side comparison to help you choose the best tool.
Flowise
freeFlowise is an open-source, low-code tool for building LLM-powered applications visually. Similar to Langflow, it provides a drag-and-drop interface for composing LangChain and LlamaIndex components into chains, agents, and chatbots. With an embedded chatbot widget, API endpoints, and broad model support, Flowise lets developers go from idea to deployed AI application in minutes.
Baseten
freemiumBaseten is a machine learning model serving platform that enables teams to deploy any AI model - including custom fine-tuned models and open-source LLMs - as production-grade APIs with autoscaling, GPU support, and sub-100ms latency for latency-sensitive applications. It provides Truss, an open-source model packaging format, for defining model serving environments as code, along with capable features like A/B testing, canary deployments, and detailed performance monitoring. Baseten is used by AI-native companies that require reliable, high-performance inference infrastructure at scale.
| Feature | Flowise | Baseten |
|---|---|---|
| Pricing | free | freemium |
| Category | - | - |
| Rating | 4.4 | 4.3 |
| Best For | Developers and indie builders who want to build and deploy LLM applications and chatbots with no code, for free | AI engineering teams at scale-ups and enterprises needing reliable, low-latency model serving infrastructure for production AI applications. |
| Views | 161 | 115 |
| Attribute | Flowise | Baseten |
|---|---|---|
| Pricing Type | free ✓ | freemium |
| Free Trial | No | No |
| API Available | No | No |
| Mobile App | No | No |
| Rating | 4.4 ✓ | 4.3 |
| Founded | - | - |
| Team Size | - | - |
| Deployment | - | - |
| Popularity (Views) | 161 ✓ | 115 |
Pros
- Completely free and open-source
- Easiest path from concept to deployed AI chatbot
- Large library of pre-built nodes
Cons
- Less polished than commercial alternatives
- Community support only on free tier
Pros
- Handles complex model serving requirements with production-grade reliability
- Truss framework standardises model packaging across teams
- Advanced deployment features like A/B testing for ML experimentation
Cons
- Higher complexity than simpler serverless alternatives
- Pricing is consumption-based and can be unpredictable at scale
- Drag-and-drop LLM app builder
- LangChain & LlamaIndex node library
- Embeddable chatbot widget
- REST API & Embed SDK
- Self-hostable with Docker
- Deploy any ML model as a production API
- Truss open-source model packaging format
- Sub-100ms inference latency with GPU optimisation
- A/B testing and canary deployment support
- Detailed performance monitoring and analytics
Want to compare Flowise with another tool?
Compare another tool