Comparison of Byte Button between Dify and Alibaba Bailian, which domestic AI Agent platform is better to use in 2026?

In 2026, domestic AI Agent platforms are flourishing, with ByteDance's Coze, Alibaba's Bailian, and Dify being the three most-watched representatives. They all let you build AI workflows, connect to private knowledge bases, and publish external services without writing code. Their positioning looks very similar, but a closer look reveals significant differences. This article does a horizontal comparison across 5 angles—product positioning, capability differences, pricing strategy, fitting scenarios, and on-premises deployment—to tell you which to pick for different needs.

1. The Three Platforms Have Different Roots

Although all are "low-code AI Agent platforms," their underlying DNA differs.

ByteDance's Coze was launched by ByteDance in 2024, with the backend deeply integrated with the Doubao large model and the Lark ecosystem. It is positioned as "an AI Agent building tool that ordinary users and small teams can both use," with the most core scenario being publishing AI Bots to traffic entry points like Lark, Douyin, and WeChat mini-programs.

Alibaba's Bailian is a large-model application development platform launched by Alibaba Cloud, with the Tongyi Qianwen large model on the backend, positioned more toward the enterprise level. It emphasizes integration with Alibaba Cloud's storage, database, and security products, suiting enterprises already in the Alibaba Cloud ecosystem who want to develop AI applications.

Dify is an open-source AI application development platform from a Shanghai startup that gained popularity in the developer community starting in 2023. Dify's feature is being model-agnostic, able to connect to OpenAI, Anthropic, Alibaba, Zhipu, DeepSeek, and other models, and supporting enterprise on-premises deployment. It is positioned as a developer-friendly "open-source LangChain + Bot platform."

In short, Coze's advantage is traffic distribution, Bailian's advantage is the enterprise cloud ecosystem, and Dify's advantage is being open-source and controllable.

2. Comparison of Core Capability Differences

All three provide core capabilities like AI conversation, knowledge bases, workflow orchestration, and tool calling, but the depth differs.

For workflow orchestration, Dify's visual editor is the most mature, with a rich variety of nodes and support for complex branching and loops. Coze has rounded out its workflow capabilities in recent versions, but it is still simplified relative to Dify. Bailian offers workflows but the development experience is closer to writing config files—friendly to programmers, unfriendly to operations staff.

For knowledge base capabilities, Bailian relies on Alibaba Cloud's vector database and document parsing services, suiting large-scale enterprise knowledge bases. Coze's knowledge base targets lightweight scenarios. Dify's knowledge base is flexible but you have to manage the vector store configuration yourself.

For model selection, Dify is the most open, supporting basically all mainstream large models. Bailian is bound to the Tongyi series, but Tongyi itself is capable and performs well in some scenarios. Coze is bound to the Doubao series; its ecosystem is relatively closed, but Doubao's capabilities have noticeably improved in the past year.

For tool calling (Function Call), all three support basic tools like HTTP, databases, and email. In ecosystem richness, Dify has the most plugins thanks to open-source community contributions.

3. Detailed Analysis of Pricing Strategies

Cost structure is key to selection.

ByteDance's Coze is currently basically free for individual users and small teams, with the Doubao token consumption of model calls covered by the Coze platform; whether large-scale commercial use is entirely free depends on the latest official policy. Developers publishing Bots to channels like Lark and Douyin pay no platform fee, with the traffic value carried by the ByteDance ecosystem.

Alibaba's Bailian bills by the number of API calls + large-model token usage, with a fairly generous free trial quota, but a medium-scale production application can easily cost hundreds to thousands of yuan per month, depending on usage intensity.

Dify offers a cloud SaaS version with a free plan + paid subscription tiers, with specific prices per the official public page. Dify's real cost advantage lies in on-premises deployment: run Docker on your own server and pay only for the server and model API fees, with no platform fee.

For individual creators and small studios, Coze is the most economical. For mid-to-large enterprises already on Alibaba Cloud, Bailian integrates most smoothly. For enterprises pursuing data autonomy with high compliance requirements, Dify's on-premises deployment fits best.

4. Fitting Scenario One: Content Creation and Publishing

If you do content creation + multi-platform distribution, Coze has a clear advantage.

Coze's Bots can be published with one click to multiple entry points like Lark bots, Douyin mini-programs, Doubao apps, and web plugins. For creators making Xiaohongshu and Douyin content, you can build an "auto-generate viral titles" Bot embedded in the Douyin workbench.

Bailian can also build content-generation Bots, but its channel integration is less convenient than Coze's, relying mainly on integrating into external applications via API yourself.

Dify suits building backend services for content generation; build your own website connecting to the Dify API for maximum freedom, but you need technical know-how.

If you are a content creator who wants to see traffic results quickly, Coze is the first choice.

5. Fitting Scenario Two: Enterprise Knowledge Assistant

If you build an internal enterprise knowledge assistant (customer service, HR Q&A, technical document retrieval), all three can do it, but via different paths.

Bailian suits mid-to-large enterprises best, because it integrates Alibaba Cloud's document parsing (supporting PDF, Word, and scanned-document OCR), vector databases (Lingjun vector store or OpenSearch), enterprise SSO login, and audit logs. It builds a one-stop retrieval-augmented generation (RAG) system, with operations handled by Alibaba Cloud.

Dify suits small-to-medium enterprises or teams with high data-autonomy requirements. After on-premises deployment, all data stays within the company network, and models can be Claude or GPT or a local large model. The open-source version is completely free, and commercial support is paid as needed.

Coze's knowledge base feature is lightweight, suiting individual creators or small teams with a few hundred documents; a large-scale enterprise knowledge base is not its strength.

6. Fitting Scenario Three: Automated Workflows

For embedding AI into business processes for automation (such as handling customer emails, auto-summarizing meeting minutes, or batch-generating marketing copy), Dify is the strongest of the three.

Dify's workflow orchestration can do conditional branching, loops, error handling, human review, and external tool calls, approaching the capabilities of enterprise-grade BPM (business process management) products. Combined with Dify's API service, you can trigger an entire workflow from external systems for unattended automation.

Coze has simplified many nodes in its workflows, suiting simple processes like the linear "user asks a question → AI answers → calls a function when necessary." It struggles with complex multi-step scenarios that require rollback and retry.

Bailian's workflows lean more toward developers, with a weaker visual experience than Dify. But within the Alibaba Cloud ecosystem, it can directly call cloud functions, message queues, and object storage, which is an advantage Dify lacks.

7. Fitting Scenario Four: API Integration Development

If you are a developer who wants to embed AI capabilities into your own product, you care about the API, SDK, and documentation quality.

Dify scores highest on API friendliness. Dify's API documentation is clear, all visually-built applications automatically expose a REST API externally, and after on-premises deployment, integrating into your own system is effortless. Multi-language SDKs cover Python, Node.js, Java, and more.

Bailian offers a complete API based on the Alibaba Cloud OpenAPI system, with Java/Python/JavaScript SDKs all available, suiting developers familiar with Alibaba Cloud.

Coze also has an API, but it is positioned more toward mini-program integration and chat access, with weaker support for enterprise-grade API orchestration than the other two.

8. On-Premises Deployment Comparison

Whether data should leave the premises is a point many enterprises agonize over.

Dify is fully open-source; start a full set of services with Docker Compose to run in your own data center or private cloud, with data never leaving the premises. Models can be cloud APIs like Anthropic/OpenAI, or you can connect to local Ollama to run open-source models, which is compliance-friendly.

Bailian is Alibaba Cloud-managed, with data stored on Alibaba Cloud, relying for compliance on Alibaba Cloud's MLPS, ISO, and other certifications, suiting enterprises that accept cloud hosting. Alibaba Cloud has a dedicated-cloud option for private deployment, but the cost is not low.

Coze currently goes mainly through cloud SaaS, with limited on-premises deployment capability. Private deployment is mainly negotiated for large customers, and ordinary users can basically only use the cloud version.

For high-compliance scenarios involving classified information, finance, or healthcare, Dify's on-premises version is almost mandatory.

9. Ecosystem and Long-Term Sustainability

When choosing a platform, you should also consider the resources and ongoing investment of the company behind it.

ByteDance's Coze is backed by ByteDance, with ample traffic and model resources and a low probability of shutting down. But the product direction follows ByteDance's strategy, and there is a risk of being passively dragged along for independent creators.

Alibaba's Bailian is Alibaba Cloud's official product, with the most assured long-term sustainability. But during Alibaba Cloud's transition period, the pace of product iteration is not fast, and new features sometimes lag behind leading rivals.

Dify is a startup, but it has a strong open-source community, with GitHub attention leading among domestic peers. You can fork and maintain the open-source version yourself, so even if the company changes direction, it does not affect your already-deployed system. This is the "long-term controllability" that enterprises value.

Frequently Asked Questions (FAQ)

What is the relationship between Coze and Lark bots

Coze is an independent AI Agent platform under ByteDance, while Lark bots are conversational tools within the Lark ecosystem. The relationship is: a Bot built in Coze can be published with one click as a Lark bot, i.e., invoked by @-mention in a Lark group, which is one of the most common publishing channels. But Coze itself does not serve only Lark; it also supports publishing to multiple endpoints like Douyin, Doubao, web, and HTTP API. So Coze's capabilities are broader than Lark bots—you can think of it as "ByteDance's version of the GPTs Store + Make."

Are the hardware requirements for Dify's private deployment high

Not really. The Dify main program + Postgres database + Redis cache + vector database (Weaviate by default) running as a full set is fine on a Linux server with 16GB of RAM. If you switch the vector store to an external PostgreSQL pgvector or Qdrant, deployment is even lighter. If you also want to run an open-source large model locally, GPU VRAM becomes the big item—see the earlier discussion of Ollama's hardware requirements. A small-to-medium enterprise can run a full AI workflow with one ordinary cloud server plus one inference machine with a GPU.

Can Bailian connect to non-Alibaba models

It can, but the cost will not be discounted. Bailian supports calling models like OpenAI and Anthropic, but it goes through an OpenAI relay or your own externally-obtained API credentials. In this case you lose Bailian's model-cost advantage, more like using Bailian as a RAG orchestration platform. If your main demand is to use other companies' models, Dify is the more natural choice. Bailian's real value lies in deep integration with Tongyi Qianwen + the Alibaba Cloud ecosystem.

Do all three platforms support the MCP protocol

As of this writing, MCP (Model Context Protocol) is the protocol championed by Anthropic, and its ecosystem is still evolving. Dify's latest version has begun integrating MCP support, allowing an MCP Server to be called as a tool. Coze's and Bailian's official MCP support should be checked against the latest documentation, as this area updates frequently. If MCP is your core demand, Dify is currently the most actively supportive. The other two may follow more slowly for product-strategy reasons.

I have high data-compliance requirements—which should I choose

Consider it by sensitivity from low to high. Low sensitivity (such as internal office automation): all three work, choose the ecosystem you are most familiar with. Medium sensitivity (involving users' personal information but already anonymized): Alibaba Cloud customers choosing Bailian have better compliance assurance; otherwise choose Dify. High sensitivity (classified information, financial accounts, medical records): Dify on-premises deployment + connecting to a local large model via Ollama is recommended, with data never leaving the company network. Extremely high sensitivity (national cryptography compliance scenarios): you need a vendor with national-cryptography qualifications to customize a solution; none of these three is the optimal choice.