The short answer: none of these four options is "best." They solve problems at different layers. Dify and Coze are application development platforms, Alibaba Cloud Bailian is a model and agent cloud, and LingHarness is a private execution engine. The selection order should be data boundary, then team capability, then system integration, then price. A feature-list comparison gets the order wrong.
This article uses only official pricing, licenses, and product documentation available on 24 October 2026. Prices are list prices and exclude tax, model calls, implementation, and operations. The "fits" and "does not fit" judgments are editorial, not a vendor ranking.
If business users will build agents themselves and SaaS or a self-hosted community edition is acceptable, start with Dify or Coze. If you want Alibaba Cloud and Qwen with managed or dedicated resources, look at Bailian. If the agent must stay private, embed in ERP/MES/OA, remain model-agnostic, and be auditable, look at LingHarness. With no engineering team and a budget below RMB 100,000, use SaaS first. Do not self-host.
Are Dify, Coze, Bailian, and LingHarness the same kind of product?
No. Dify and Coze are application development platforms. Bailian is a model and agent cloud service. LingHarness is an execution engine that can be embedded in a private environment. Separate the layers before comparing features.
It is easy to put all four into one feature table, tick boxes, and conclude that the product with the most features is best. That is the wrong conclusion. They address different layers. An application platform builds the agent. A model cloud supplies the models and compute. An execution engine makes the agent run reliably inside enterprise systems.
| Layer | Examples | What you are buying | Main users |
|---|---|---|---|
| Application development platform | Dify / Coze | Visual workflows, agents, RAG, plugins, and publishing channels | Business teams, low-code and product teams |
| Model and agent cloud | Alibaba Cloud Bailian | Model APIs, RAG, agent orchestration, dedicated deployment resources | Companies already on Alibaba Cloud, AI application teams |
| Execution engine / base | LingHarness | ReAct loop, middleware, MCP tools, model routing, audit, and embedding | Enterprise engineering and platform teams |
On a phone, swipe the table sideways to see all columns. In this article, "base" means the execution layer that hosts the agent runtime. It is not the model itself, and it is not a visual application platform. The three layers can be combined; they are not mutually exclusive.
Who does each option fit, and who does it not fit?
Dify suits teams that want an open-source, visual way to build. Coze suits teams that want a bot quickly. Bailian suits Alibaba Cloud and Qwen users. LingHarness suits engineering teams that need a private, embedded layer inside ERP/MES/OA.
| Option | Fits | Does not fit |
|---|---|---|
| Dify | Teams that want to build workflows, RAG, and agents quickly with the open-source or cloud edition; multi-model access; basic engineering capability | Multi-tenant SaaS without a commercial license; deep ERP/MES write-back with no integration capability |
| Coze | Fast customer service, content, and office bots; teams inside the ByteDance or Volcano Engine ecosystem; business users involved in building | Fully offline private deployment; agents deeply embedded in legacy systems with field-level permissions |
| Bailian | Companies already using Alibaba Cloud; mainly Qwen or DeepSeek; managed RAG, agents, or dedicated inference resources | Model-agnostic or multi-cloud requirements; data that cannot go to Alibaba Cloud; fully offline intranet operation |
| LingHarness | Data cannot leave the intranet; agents must embed in ERP/MES/OA; model-agnostic with MCP, audit, and human confirmation; an engineering team exists | No engineering or platform team; drag-and-drop bot building only; budget below RMB 100,000; a standard customer service bot is enough |
This is not a ranking of "who is stronger." It is a map of "who fits your constraints." One company may use Dify for front-end applications and LingHarness as the intranet execution layer.
What do they cost in October 2026?
Dify Community is free, and Dify Cloud is USD 590 or 1,590 per workspace per year. Coze enterprise plans start at RMB 980 or 8,980 per month. Bailian dedicated deployment is RMB 432–1,008 per hour. LingHarness is quoted per project.
| Option | Public price (24 October 2026) | Unit | Included / not included |
|---|---|---|---|
| Dify Community | RMB 0 | Self-hosted | Software license is free; servers, models, implementation, and operations are not included. Modified Apache 2.0 with restrictions |
| Dify Cloud | Professional USD 590 / Team USD 1,590 | Workspace / year | Excludes tax; includes message quota and document/application quotas; overages billed separately |
| Dify Enterprise | Custom | Contract | Private deployment, commercial license, SSO, multiple workspaces, SLA; contact sales |
| Coze Studio | RMB 0 | Self-hosted | Apache 2.0; servers, models, implementation, and operations are not included |
| Coze Enterprise | Standard from RMB 980 / month; Flagship from RMB 8,980 / month | Month | Includes 5 or 30 seats and credits; cloud service; VPC, SSO, and KMS mainly on Flagship |
| Bailian dedicated deployment | RMB 432 / hour or RMB 208,944 / month; RMB 1,008 / hour or RMB 480,576 / month | Model spec / duration | DeepSeek-v4-Flash MU1×8; DeepSeek-v3.2 MU2×16 with PD (prefill-decode) separation; varies by model and region |
| LingHarness | Project quote | Contract | Private deployment, license, implementation; servers and models are separate |
Dify Cloud is a USD list price; the others are in RMB. All exclude tax, model calls, implementation, and operations. Coze prices took effect on 14 July 2026 and may change with promotions. Bailian prices vary by model, specification, and region; the official page prevails.
The table is easy to misread as "Dify and Coze are cheaper than LingHarness." Platform subscription is only a small part of first-year spending. Integration, data governance, and operations are the larger lines. The next sections separate private deployment from integration.
How far can private deployment actually go?
Dify Community can be self-hosted and Dify Enterprise can be private. Coze's commercial edition is not fully private; use Coze Studio for a self-built deployment. Bailian offers dedicated resources on Alibaba Cloud. LingHarness is private-first.
| Option | Private deployment path | Data boundary | Operations owner | Key limitation |
|---|---|---|---|---|
| Dify Community | Self-hosted with Docker | The company's own servers or private cloud | Company | Modified Apache 2.0: multi-tenant use needs a commercial license; logo and copyright notices cannot be removed |
| Dify Enterprise | Vendor-supported private deployment | Company private environment | Vendor plus company | Custom quote; commercial license, SSO, SLA |
| Coze Studio | Open-source self-hosting | The company's own servers or private cloud | Company | Apache 2.0; some commercial-edition features are missing; public deployment needs security hardening |
| Coze Enterprise | Cloud service plus VPC private connection | On Volcano Engine cloud | Vendor | Official FAQ: the commercial Coze programming product does not currently support private deployment; use Coze Studio for full offline operation |
| Bailian | Dedicated deployment / dedicated resources | On Alibaba Cloud, resources exclusive | Vendor plus company | Not local or offline; billed by model specification and duration |
| LingHarness | Private, intranet, embedded | The company's own servers or intranet | Vendor plus company | Requires an engineering or platform team; not a no-code builder |
"Can be private" does not mean "works out of the box." The open-source edition brings the software license to zero, but the company still carries servers, models, security hardening, upgrades, and operations.
What changes when you integrate with ERP/MES/OA?
Dify and Coze rely on APIs, plugins, and webhooks. Bailian relies on cloud APIs. LingHarness embeds through a Go module and MCP. The hard part is not the interface. It is the legacy system, permissions, and write-back.
| Option | Integration method | Practical integration depth | Main effort |
|---|---|---|---|
| Dify | HTTP API, plugins, webhooks, external knowledge base | Read/write interfaces, knowledge base, approval queries | Custom connectors, permission mapping, exception handling |
| Coze | Plugins, API, Chat SDK | Customer service, office, and content workflows | Plugin configuration, system connection, cloud permissions |
| Bailian | Cloud API, RAG, agents/workflows, connectors | Cloud data and model calls | Cloud account and network, data sync, interface adaptation |
| LingHarness | Go module, MCP, OpenAI protocol, SSE | Embedding in existing systems, tool calls, human confirmation, audit | Systems engineering, legacy adaptation, permission and audit design |
No platform solves master data. When a legacy system has no API, middleware, screen-level automation, or RPA, those costs must be budgeted separately. Field-level permissions, write-back, and audit are usually harder than "connecting a model."
What does a 50-person company spend in year one?
For 50 people, two scenarios, and 500 million tokens a year, platform fees are usually only 10–30% of first-year spending. Integration, data, and operations dominate. The common first-year total is RMB 200,000–800,000.
Start with a calculation anyone can repeat. At 500 million tokens a year and RMB 20–60 per million tokens, the API bill is about RMB 10,000–30,000. Add ERP/MES/OA interfaces, knowledge-base cleanup, permissions, evaluation, training, and operations, and the first-year total usually reaches RMB 200,000–800,000. That range is an editorial estimate, not a quote.
| Cost line | Typical share | Notes |
|---|---|---|
| Platform / software | 10–30% | Subscription, license, or commercial edition |
| Model / compute | 10–30% | Tokens, GPUs, or dedicated deployment |
| Implementation / integration | 30–50% | ERP/MES/OA, data, permissions, evaluation |
| Operations | 15–30% | One or two people per year, including upgrades, security, and incidents |
The shares are an empirical range for a 50-person, two-scenario private deployment. They move with the number of systems, data quality, and compliance requirements. They are not any vendor's formal quote.
When should you not choose LingHarness?
Do not choose LingHarness if you have no engineering or platform team, if you only want drag-and-drop bot building, if the budget is below RMB 100,000, or if a standard customer service bot is enough. SaaS is more economical in those cases.
LingHarness is an execution engine, not a no-code application builder. It fits scenarios where data cannot leave the intranet, the agent must embed in existing systems, the model must be replaceable, and every step must be auditable. When those constraints do not exist, Dify Cloud, Coze, or Bailian's managed capabilities will go live faster and cost less in year one.
Conversely, if the company has already decided to connect AI to ERP/MES/OA, enforce field-level permissions, preserve model choice, trace every tool call, and require human confirmation for critical actions, then "buy a visual platform first" usually means rework at the integration stage. Define the execution layer first, then choose the application layer.
Why do enterprise selections fail?
Treating a demo as production, ignoring master data, having no evaluation set, and underestimating operations are four failures no platform can fix.
| Failure | How it shows up | How to avoid it |
|---|---|---|
| Treating a demo as production | Answers look good in the demo; after launch they answer the wrong question and tool calls fail | Build 200–500 evaluation cases from real tasks; record task success rate, cost per task, and P95 latency |
| Ignoring master data | Multiple material codes, BOMs, and customer names; the agent finds contradictory records | Unify master data and permissions before discussing agents; the platform does not fix data governance |
| No acceptance standard | Nobody uses it after launch, or it is only used for demos | Agree adoption rate, task completion rate, human takeover rate, and enquiry or ticket conversion before launch |
| Underestimating operations | The open-source edition is deployed and never upgraded; a model or plugin change breaks it | Assign at least one or two administrators, or buy managed support; put operations in the three-year budget |
These four issues are independent of whether you choose Dify, Coze, Bailian, or LingHarness. Changing platforms does not automatically fix data, process, or organizational problems.
Can the four options be combined?
Yes, and it is common. Dify or Coze runs front-end applications, Bailian or a self-hosted model supplies inference, and LingHarness acts as the intranet execution layer. Clear boundaries are the condition.
A practical combination: business teams use Dify or Coze to build customer service, content, and reporting applications; models run through Bailian APIs or the company's own inference; tasks involving drawings, process parameters, and financial data go to LingHarness on the intranet, which calls tools through MCP or the OpenAI protocol. This keeps the low-code learning curve while leaving sensitive data and core systems inside the intranet.
The condition is clear boundaries. Do not let three systems each maintain their own permissions, knowledge base, and user directory. Otherwise "combination" becomes three times the integration and operations cost.
A decision table: choose by your constraints
Answer four questions first: can data leave the intranet, is there an engineering team, is deep ERP/MES/OA integration required, and what is the first-year budget? Those four answers usually narrow the choice to one option.
| Your constraint | Look first at | Why |
|---|---|---|
| Data cannot leave the intranet, and you have an engineering team | LingHarness / Dify Enterprise / self-hosted Coze Studio | The private path is clear; LingHarness leans toward execution and embedding, Dify and Coze toward application building |
| Data cannot leave the intranet, and you have no engineering team | A vendor-managed private cloud | Pure self-hosting leaves operations risk with the business team; buy managed service and implementation first |
| Business users build, and speed to launch matters | Dify Cloud / Coze | Visual builders, templates, and plugins are mature; no need to build an execution layer first |
| Already on Alibaba Cloud/Qwen, and need dedicated resources | Bailian | Models, RAG, agents, and billing sit on one cloud; dedicated deployment provides resource isolation |
| Must embed in ERP/MES/OA, with audit and model independence | LingHarness | The execution layer can be embedded and tool calls traced; the application layer can be chosen separately |
| Only need a customer service or content bot, with a low budget | Coze / Dify Cloud | Highly standardized; self-hosting does not pay back |
One company can combine them: Dify or Coze for front-end applications, Bailian for models, LingHarness for the intranet execution layer. Selection is not about picking a side. It is about layers.
After choosing a platform, the next step is implementation and acceptance. The Chinese edition of our guide to taking an enterprise AI agent from POC to production is in the Insights archive. For the private deployment budget behind these numbers, read What private AI deployment really costs in 2026.
FAQ
Can Dify Community be used commercially?
Yes, but Dify Community uses a modified Apache 2.0 license. Multi-tenant services require a commercial license, and the logo and copyright notices in the front-end console and applications cannot be removed. Dify Enterprise adds a commercial license, SSO, multiple workspaces, and an SLA.
Can Coze's commercial edition be deployed privately?
The commercial Coze programming product does not currently support private deployment. The official FAQ recommends self-hosting the Apache 2.0 Coze Studio open-source edition when private deployment is required. Coze Enterprise Flagship provides VPC private connections, SSO, and KMS, but it remains a cloud service.
How much does Bailian dedicated deployment cost?
Pricing depends on the model and specification. Using official DTU prices on 24 October 2026: DeepSeek-v4-Flash MU1×8 is RMB 432 per hour or RMB 208,944 per month; DeepSeek-v3.2 MU2×16 with PD (prefill-decode) separation is RMB 1,008 per hour or RMB 480,576 per month.
What is the difference between LingHarness and Dify?
Dify is a visual LLM application development platform. LingHarness is an agent execution engine and base that can be embedded in enterprise systems. It emphasizes private deployment, model independence, MCP tools, audit, and human confirmation. It is not a replacement for a no-code application builder.
What does a 50-person company spend in year one?
For an estimate of 50 people, two scenarios, and 500 million tokens a year, platform subscription is usually 10–30% of first-year spending. Including integration, data, and operations, the common first-year total is RMB 200,000–800,000. The exact figure depends on whether deployment is private and how many systems are connected.
Can the open-source edition remove the software cost?
The software license can be zero, but servers, model calls, integration, security hardening, upgrades, and operations still cost money. Without one or two administrators, pure self-hosting is not advisable. Open source saves the license fee, not total cost of ownership.
Dify and Coze solve "how do we build the agent," Bailian solves "where do the models and compute come from," and LingHarness solves "how does the agent run reliably on the enterprise intranet, embed in existing systems, and stay auditable." Settle the data boundary and team capability before discussing price.
Sources and caveats
Research cut-off: 24 October 2026. Prices are official list prices and exclude tax, model calls, implementation, and operations. Dify Cloud is priced in USD; Coze and Bailian are in RMB. Promotions, exchange rates, regions, and model versions all affect the actual price. The layer model, fit judgments, cost shares, and failure list are editorial analysis, not vendor claims or a quote.
- Dify pricing, cloud, community, and enterprise editions, accessed 24 October 2026. dify.ai/zh/pricing; enterprise edition: dify.ai/zh/pricing/dify-enterprise.
- Dify open-source license, modified Apache 2.0 with multi-tenant and logo restrictions, accessed 24 October 2026. github.com/langgenius/dify.
- Coze subscription plans and enterprise billing, effective 14 July 2026. docs.coze.cn/guides_edition; Enterprise billing rules.
- Coze private deployment FAQ, accessed 24 October 2026. docs.coze.cn/guides_FAQ. The commercial Coze programming product does not currently support private deployment; use the Coze Studio open-source edition.
- Coze Studio open-source repository, Apache 2.0, accessed 24 October 2026. github.com/coze-dev/coze-studio.
- Alibaba Cloud Bailian DTU and dedicated deployment pricing, accessed 24 October 2026. help.aliyun.com/zh/model-studio/dtu-model-deployment.
- LingHarness product page, private deployment, PipelineLoop, MCP, and audit, accessed 24 October 2026. czlytech.com/ly-harness.html.