💻

Dify

ai-coding-tools
dify.ai
★★★★★ 4.6 / 5
VS

Make

ai-productivity-tools
make.com
★★★★★ 4.6 / 5
⚔️ Head-to-Head Comparison · Updated July 2026

Dify vs Make — Which is Better in 2026?

By AsmiAI Editorial Team · Last updated July 2026

Quick Verdict: Dify edges ahead with a 4.6/5 rating vs Make's 4.6/5. Both tools serve similar use cases — the best choice depends on your specific workflow, budget, and feature priorities. Read our full comparison below.

Quick Comparison Table

FeatureDifyMake
Free Plan✓ Yes✓ Yes
PricingFree / $59/moFree / $9–$29/mo
Rating★★★★★ 4.6★★★★★ 4.6
Key Feature 1Visual workflow builderVisual workflow builder
Key Feature 2RAG pipeline1,500+ app connectors
Key Feature 3Multi-model supportError handling
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Dify vs Make: Which Should You Choose?

Dify and Make are rated almost identically by users (4.6 vs 4.6), so the right pick comes down to feature fit rather than overall quality. Both Dify and Make offer free plans, so you can test both before committing. Both tools are widely used by programmers, startups, agencies — the deciding factor is usually which specific feature set matches your existing workflow.

Dify vs Make: Full Analysis

Dify versus Make is one of the more common decisions buyers face — Dify is built around coding tools while Make leans toward productivity tools. Dify is best known for visual workflow builder, whereas Make stands out for visual workflow builder. Both land at 4.6/5 with users, so the right pick comes down to fit rather than raw quality.

Where Dify pulls clearly ahead is building a customer-facing chatbot with RAG over your own documentation. A frequent plus in reviews: Open-source codebase — self-host for full data control, audit the code, or contribute to the community. Make, by contrast, is the stronger choice for building complex multi-branch automation with conditional logic. In its favour: More powerful than Zapier — especially for visual workflow builder workflows where Make consistently outperforms manual approaches. The feature checklists overlap, but the day-to-day experience does not.

Dify is the strongest open-source option for teams building production LLM applications who need more control than no-code tools but less overhead than building from scratch. Make is the right automation tool for anyone who has hit Zapier's complexity ceiling. For most teams the deciding factor is existing workflow and budget, not a marginal feature gap.

Who Should Use Each Tool

Choose Dify if you are focused on developers and technical teams who want to build and deploy LLM-powered applications — chatbots, RAG pipelines, AI agents, and internal tools — without writing backend AI infrastructure from scratch, or if a big part of your week goes to creating internal AI tools that query your company knowledge base. Its free tier also lets you validate the fit before paying.

Choose Make if your priority is technical users, developers, and operations teams who need complex automation with branching logic, data transformation, and multi-step processes — and who find Zapier too simple, especially for transforming and mapping data between apps with custom formulas. A free plan is available, so you can trial the workflow at zero cost first.

Real-World Performance

In day-to-day use, Dify feels strongest at building a customer-facing chatbot with RAG over your own documentation, while Make is more at home with building complex multi-branch automation with conditional logic.

Learning curve is worth weighing. Dify has a known trade-off — Steeper learning curve than no-code tools. On Make's side: Steeper learning curve — worth evaluating before committing if this is central to your use case. Whichever one slots into your current stack with the least friction tends to win in the long run.

Pricing & Value for Money

Both tools offer a free plan, so you can trial each side by side before spending anything. Paid plans start at $59/mo for Dify (Professional (Cloud)) and $9/mo for Make (Core), making Make the cheaper entry point at $9/mo versus $59/mo. The extra spend on Dify only pays off if you need what its higher tier unlocks. The sticker price rarely tells the whole story — check seat counts and usage limits before you commit.

🚀 Ready to decide? Try both free and see which fits your workflow.

About Dify

Dify is an open-source platform for building production-ready AI applications and agents without deep engineering expertise. Its visual work… Read the full Dify review →

About Make

Make (formerly Integromat) is a visual automation platform connecting 1,800+ apps through a drag-and-drop scenario builder. Unlike Zapier's … Read the full Make review →

Performance Comparison

Dify Scores

Ease of Use84%
Features92%
Value for Money88%

Make Scores

Ease of Use93%
Features90%
Value for Money86%

Pros & Cons

✅ Dify Pros

• Open-source codebase — self-host for full data control, audit the code, or contribute to the community

• Supports all major AI models

• Visual builder, no deep coding needed

• Strong RAG and agent capabilities

❌ Cons

• Steeper learning curve than no-code tools

• Self-hosting requires server setup — worth evaluating before committing if this is central to your use case

✅ Make Pros

• More powerful than Zapier — especially for visual workflow builder workflows where Make consistently outperforms manual approaches

• Practical free tier that lets you validate the tool before committing to paid plans

• Highly customizable and flexible, allowing users to create complex automations tailored to their specific needs

• Cost-effective for high-volume automations, with a pricing model based on operations rather than tasks

❌ Cons

• Steeper learning curve — worth evaluating before committing if this is central to your use case

• UI can be complex — worth evaluating before committing if this is central to your use case

🏆 Final Verdict — When to Use Each

Use Dify ifYou need visual workflow builder and prefer Free / $59/mo pricing.
Use Make ifYou need visual workflow builder and the Free / $9–$29/mo plan fits your budget.
Overall WinnerDify edges ahead with a 4.6/5 rating, broader feature set, and strong user satisfaction scores.