The decision
Should you choose Dify?
Dify earns a shortlist for teams that need a broad visual AI application layer and can govern it like production software. Use Sandbox for a narrow proof, calculate total provider cost, and threat-model plugins and tools before launch.
Best for
Teams prototyping AI applications; Builders needing visual orchestration and APIs.
Choose something else if
Unowned production agents with write access; Teams unwilling to inspect license and provider paths
Evidence
Editorial research pending · 8.0/10
Pricing checked
From $59 · 2026-09-01
Free access is available, with limits.
Yes. Sandbox includes limited credits, one member, five apps, and a small knowledge allowance; the Community edition can be self-hosted under its current license.
In this guide
Short answer
Dify is worth testing for product and operations teams that want to prototype model-backed apps without hand-coding every orchestration layer. Its visual builder and self-hosted option are useful, but the platform can concentrate prompts, secrets, knowledge, tools, and production actions in one control plane. Governance must arrive before scale.
Best for
- Teams prototyping AI applications
- Builders needing visual orchestration and APIs
- Organizations comparing cloud and self-hosted deployment
Look elsewhere if
- Unowned production agents with write access
- Teams unwilling to inspect license and provider paths
- Buyers expecting credits to equal predictable outcomes
What Dify verifiably does
Official pages describe chat, agent, text-generation, and workflow applications; visual orchestration; model-provider choice; retrieval knowledge bases; plugins; triggers; APIs; logs; annotation; evaluation; cloud hosting; and self-hosted Community and Enterprise editions.
Important limitations
Message credits are model-dependent and can be exhausted before workflow demand is understood. External model, embedding, plugin, and data-source providers receive selected content. Self-hosting requires secret management, tenant isolation, patching, backups, rate limits, and license review. Visual workflows can hide retries, branching costs, and dangerous tool permissions.
Pricing snapshot
Dify Cloud lists Sandbox free, Professional at $59 per workspace per month on monthly billing, and Team at $159 per workspace per month; annual totals are advertised at $590 and $1,590. Plans differ by credits, members, apps, knowledge storage, triggers, processing, and history. Community self-hosting is free under the Dify Open Source License; Enterprise is custom. Reviewed September 1, 2026.
A fair buyer test
Build one bounded workflow with a synthetic knowledge base, two models, a failing API tool, prompt-injection cases, and a human approval step. Measure accepted outcomes, retrieval misses, tool errors, retries, credit and API cost, log exposure, permission separation, export portability, and recovery after an upgrade.
Final verdict
Dify earns a shortlist for teams that need a broad visual AI application layer and can govern it like production software. Use Sandbox for a narrow proof, calculate total provider cost, and threat-model plugins and tools before launch.
This is a research-based assessment, not a claim of hands-on product testing. Product, pricing, privacy, security, licensing, and usage claims were checked against the first-party sources below on September 1, 2026. Verify current terms and run the proposed test with approved data before adoption.
Transparency
How this guide was checked
Editorial accountability
Who checked this guide
- Evaluation type
- Hands-on evaluation
- Last materially checked
- Evidence
- 4 listed sources
Hands-on testing is identified explicitly. Research-based coverage uses cited product documentation and other named sources; it does not imply every paid plan was used. Read the full methodology.
Editorial freshness
Pricing and material product claims were checked September 1, 2026.
Review evidence
What this guidance is based on
- Editorial basis
- Current first-party product, pricing, documentation, privacy, security, and license material
- Review type
- Research-based product assessment
- Material review date
- September 1, 2026
- Buyer test
- Controlled workflow test with evidence, correction, cost, permission, privacy, and ownership checks
Important limits
- • DiscoverAI did not complete the proposed long-term paid deployment for this research-based review.
- • Features, prices, limits, security controls, privacy terms, licensing, and provider data paths can change; verify the linked first-party pages before purchase.
Standardized benchmark coverage
How this review maps to the research benchmark
Citation accuracy
Eligible · not yet runThis review describes source-grounded research, retrieval, or document work. A controlled product run is required before scoring.
Read protocol v2026.10-v1 →Thematic analysis
Not applicableThe reviewed workflow is not qualitative evidence analysis, so a thematic-analysis score would be misleading.
Read protocol v2026.10-v1 →Eligibility is not a product score. DiscoverAI publishes results only after output collection, blinded adjudication, reproducibility checks, and severe-error review.
Open the optional evaluation worksheet
Reusable trial worksheet
Test Dify before you commit
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Teams prototyping AI applications; Builders needing visual orchestration and APIs; Organizations comparing cloud and self-hosted deployment
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Build one bounded workflow with a synthetic knowledge base, two models, a failing API tool, prompt-injection cases, and a human approval step. Measure accepted outcomes, retrieval misses, tool errors, retries, credit and API cost, log exposure, permission separation, export portability, and recovery after an upgrade.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: Dify Cloud lists Sandbox free, Professional at $59 per workspace per month on monthly billing, and Team at $159 per workspace per month; annual totals are advertised at $590 and $1,590. Plans differ by credits, members, apps, knowledge storage, triggers, processing, and history. Community self-hosting is free under the Dify Open Source License; Enterprise…
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.2/5; AI quality 4.0/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: OpenAI, Anthropic, Gemini, Webhooks, API, Plugins
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Credits vary by model; Plugins and tools widen the security boundary; Self-hosting requires mature operations
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Community evidence
How verified users put Dify to work
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
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Community choice
Recommend Dify
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Sources and verification
Product details and claims were checked against the following primary sources.
Frequently asked questions
Is Dify free?
Yes. Dify offers a limited free Sandbox and a self-hosted Community edition under its current license.
How much is Dify Professional?
Dify lists Professional at $59 per workspace monthly, or $590 annually, before tax and separate provider usage after included credits.
Can Dify be self-hosted?
Yes. Community and enterprise self-hosted paths are documented; infrastructure, model services, security, and maintenance remain buyer responsibilities.
Does Dify include model usage?
Cloud plans include message credits for selected models. Credit consumption varies, and users can switch to their own provider key after credits run out.
Recommended tool
Use Dify if this workflow fits your team
Broad app and workflow builder
Tools mentioned in this article
Dify
A visual platform for building model-agnostic AI apps, agents, workflows, and knowledge systems
Dify combines visual AI workflows, agents, knowledge retrieval, plugins, logs, and APIs across cloud and self-hosted editions, but credit rules, licensing, provider data paths, and production governance deserve scrutiny.
Flowise
An open-source visual builder for LLM flows, assistants, and multi-agent systems
Flowise offers drag-and-drop AI orchestration, APIs, evaluations, and self-hosting, but public exposure, credential handling, tool permissions, and production ownership determine whether a flow is safe.
Langfuse
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Langfuse unifies traces, costs, prompts, datasets, and evaluation with cloud and self-hosted options, but telemetry sensitivity, retention, operational load, and fast-rising plan costs demand a scoped pilot.
Open WebUI
A self-hosted multi-user AI interface for local, private, and third-party models
Open WebUI gives teams one customizable interface for local and hosted models, knowledge, tools, permissions, and enterprise deployment, but security, licensing, operator access, and model data paths remain the deployer's responsibility.
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