Dify
Open-source LLM app development platform for building agents, chatbots, and workflows.
Dify is an open-source platform for building LLM applications, designed to bundle the many moving parts of an AI product into one coherent stack. Building on top of large language models normally means stitching together model access, prompt engineering, retrieval, agent logic, and monitoring from a dozen separate tools. Dify replaces that fragmented toolchain with a single self-hostable environment, accessible through an intuitive web interface, so teams can go from prototype to production without writing the underlying orchestration plumbing.
At its center is a visual workflow builder where you assemble multi-step AI applications on a canvas, combining language models, web search, code execution, and your own APIs with branching logic. Alongside it sits a Prompt IDE for crafting and comparing prompts across models, and a built-in RAG pipeline that handles the whole retrieval flow: ingesting documents like PDFs and slides, chunking and embedding them, storing them in a vector database, and retrieving and reranking the right context at query time. This Knowledge surface is a first-class part of the product, giving teams a concrete place to manage data and grounding rather than rebuilding retrieval in every app.
Dify is firmly model-agnostic. It connects to hundreds of proprietary and open-source models across many inference providers, from commercial APIs to locally hosted models, and lets you switch the model behind an application without changing code. Its agent capabilities let you define agents using function calling or a reasoning-and-acting loop, equip them with dozens of built-in tools or your own, and connect external tools through the Model Context Protocol, with the option to turn a finished Dify workflow into an MCP server itself.
Rounding out the platform are LLMOps features for monitoring logs and performance and improving prompts and datasets from real usage, native integrations with observability tools, and a backend-as-a-service layer that exposes every app as an API for embedding into existing software. Dify can be run as a managed cloud service or self-hosted for full data control, which makes it a common choice for teams with privacy, compliance, or requirements who still want a fast path to shipping chatbots, copilots, and agents.
Vendor details
Canonical URL
https://dify.ai
Category
Agent builder
Company status
independent
Use cases & customers
Target customers
Deployment options
In practice
You want a support chatbot grounded in your own documentation without assembling a RAG stack yourself. Dify's built-in Knowledge pipeline ingests, chunks, embeds, and retrieves your docs, and you wire it into a workflow visually.
Your team is stitching together model access, prompts, retrieval, and monitoring from separate tools. Dify combines workflow building, a Prompt IDE, RAG, agents, and observability in one self-hostable platform from prototype to production.
You need to keep data on your own infrastructure and stay free to switch models. Dify is open source and self-hostable, connects to hundreds of commercial and local models, and exposes every app as an API.
Agentic Index coverage score
9.5 / 14 capabilities · 68%
| Integrations & Tool CallingAgent Features research report + JSON Feature Rubric | Full |
|---|---|
| Workflow OrchestrationAgent Features research report + JSON Feature Rubric | Full |
| Knowledge Grounding & RAGAgent Features research report + JSON Feature Rubric | Full |
| Human Oversight & GuardrailsAgent Features research report + JSON Feature Rubric | Unable to verify |
| Security, Identity & GovernanceAgent Features research report + JSON Feature Rubric | Partial |
| Observability & AuditabilityAgent Features research report + JSON Feature Rubric | Full |
| Memory & State PersistenceAgent Features research report + JSON Feature Rubric | Partial |
| Deployment & Data ResidencyAgent Features research report + JSON Feature Rubric | Full |
| Prebuilt Agents, Templates & PacksAgent Features research report + JSON Feature Rubric | Partial |
| Triggers & Channel CoverageAgent Features research report + JSON Feature Rubric | Partial |
| Model Flexibility & RoutingAgent Features research report + JSON Feature Rubric | Full |
| APIs, SDKs & MCP ExtensibilityAgent Features research report + JSON Feature Rubric | Full |
| Testing, Debugging & OptimizationAgent Features research report + JSON Feature Rubric | Partial |
| Browser & Computer UseAgent Features research report + JSON Feature Rubric | Unable to verify |
The Agentic Index coverage score grades every vendor Full, Partial or Unable to verify against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Recent platform changes
Dify released version 1.16.1, adding a Tool Multi-Select Input for configuring multiple tool parameters simultaneously and a Workflow Node Locator that links run-log errors directly to the corresponding canvas node. The update also shifts the default OpenAI plugin API from Chat Completions to Responses to support the newly released GPT-5.6 model family.
Bears on: Workflow orchestration
View sourceDify 1.15.0 shipped difyctl, a CLI for running apps and workflows from the terminal or CI/CD, alongside a redesigned role-based access control system, improved human-in-the-loop forms, and a patch for the CVE-2026-41948 path traversal flaw.
Bears on: MCP / tool calling / API
View sourceDify released v1.14.2 with security hardening, workflow and HITL reliability fixes, RAG and document-processing improvements, knowledge-base stability updates, tracing reliability, and self-hosted deployment and runtime changes.
Bears on: Security / enterprise
View sourcePricing
From $59/mo · Sandbox free demo + free self-host
credits
Included quota
Sandbox (free): 200 ONE-TIME message credits (not renewable), 1 workspace, 1 user, 5 apps, 50 knowledge documents, ~50MB storage, 30-day logs, 5,000 API calls/mo, community support. Professional ($59/mo): 5,000 credits/mo, 3 seats, 50 apps, 500 documents, 5GB storage, 20,000 trigger events/mo, unlimited logs, no API rate limit, 10 custom tools, priority email. Team ($159/mo): 10,000 credits/mo, 50 seats, 200 apps, 1,000 documents, 20GB storage, 1,000 knowledge req/min, unlimited triggers + custom tools, Langfuse/Langsmith integration, SSO, white-label, priority email+chat. Enterprise: SOC2 Type II, self-host/dedicated cloud, role management, branding, dedicated support.
What is public
Dify (dify.ai, by LangGenius - open-source LLM app-development platform: visual builder for agents, chatbots, RAG pipelines, workflows) has four cloud tiers metered by MESSAGE CREDITS, plus a free self-hosted Community Edition. Sandbox: free (200 ONE-TIME message credits, 1 user, ~5 apps, 50 docs - a demo, not production). Professional: $59/mo ($590/yr, ~$49/mo annual) - 5,000 credits/mo, 3 seats, 50 apps. Team: $159/mo ($1,590/yr, ~$132/mo annual) - 10,000 credits/mo, 50 seats, 200 apps, SSO, Langfuse/Langsmith. Enterprise: custom (SOC2, self-host/dedicated cloud). You bring your own model providers and pay them separately for LLM usage.
Billing mechanics
Fixed monthly cloud tiers + included MESSAGE CREDITS (predictable, not pure usage billing). A credit = one LLM API call via DIFY-HOSTED models, and consumption scales with model choice - ~1 credit per GPT-3.5 message vs ~10 per GPT-4 message (a 10:1 spread), so 'budget 3-5x what you'd naively expect.' Critically, if you configure your OWN API key (BYOK), you BYPASS the credit system entirely and pay your provider directly - your Dify subscription then just covers the platform. Tiers also differ by seats, apps, knowledge storage/documents, and rate limits. Annual billing saves ~17%.
Cost watchouts
Sandbox's 200 credits are ONE-TIME (lifetime), not monthly - it's a demo, not a free production tier; message credits meter MODEL CALLS not user messages, and GPT-4-class models burn ~10x the credits of GPT-3.5 (budget 3-5x); LLM inference is NEVER included (pay your provider separately - often the largest cost); SSO is gated high (Team/Enterprise depending on source); the modified Apache-2.0 license BANS multi-tenant resale - embedding self-hosted Dify in a SaaS you sell requires a commercial license from LangGenius
Variable cost rationale
The Dify platform fee is fixed/predictable per tier, but real cost is driven by LLM provider usage - either via Dify credits (model-call-metered, model-choice-sensitive) or BYOK (you pay the provider directly); credits give predictability while BYOK shifts cost off Dify entirely
Additional watchouts
The license is the real story - 'Apache 2.0' but a multi-tenant restriction means you CAN'T legally run self-hosted Dify as a customer-facing multi-tenant SaaS without a commercial license; Sandbox is a one-time demo (not a free production tier); credit budgeting is model-sensitive (GPT-4 ~10x GPT-3.5); self-hosting is free but carries Docker/ops/monitoring overhead; LLM costs (separate) usually exceed the platform fee
Overage / add-ons
When monthly credits run out, you upgrade a tier OR configure your own LLM API key (BYOK) to bypass credits entirely (paying the provider directly); Professional resources (vector storage, seats) can be topped up independently. Self-hosted Community Edition has NO credit system at all. Enterprise is custom.
Sales call required
Mixed (some tiers require a call)
Free / trial
Free
Lowest paid plan
$59/mo or $49.17/mo AE
Commercial notes
One of the most-starred open-source AI-app platforms (~139K GitHub stars per the most recent sources; 60K-139K cited across older ones), 1M+ deployed apps; combines visual workflow builder + RAG + agent framework + model management + observability as a Backend-as-a-Service; modified Apache 2.0 (multi-tenant-restricted, functionally Sustainable Use for resellers); competes with LangChain (code-first), Flowise/Langflow (visual OSS), n8n; pairs with model routers for multi-model access
Key ambiguities
Sandbox credit details vary (200 one-time vs '200/month'; 5 vs 10 apps; 15- vs 30-day logs); SSO availability is cited inconsistently (Team per some sources, Enterprise-only per others); Enterprise pricing is custom (AWS Marketplace shows ~$150K/yr as a starting point); per-action credit rates beyond the GPT-3.5/GPT-4 example aren't fully published; GitHub-star counts are cited in a 60K-139K range across sources (~139K per the most recent)
Cancellation / refund
Sandbox free (no card, one-time credits); Professional/Team self-serve monthly or annual (annual ~17% cheaper; corporate payment methods supported); top up vector space/seats on Professional independently; Enterprise custom-contracted; self-hosted Community Edition is free (open-source, no contract - but multi-tenant commercial use needs a LangGenius license); students/educators free
Support SLA / resale
Community support (Sandbox/self-host); priority email (Professional); priority email + chat (Team); dedicated support (Enterprise); SSO on Team/Enterprise; white-label/branding on Team/Enterprise; SOC2 Type II + role management on Enterprise; connects to OpenAI/Anthropic/Google/xAI + local models (Ollama/LocalAI) + any OpenAI-compatible API; MCP support; self-hosted multi-tenant resale requires a commercial license from LangGenius
Missing data
Sandbox credit renewal (one-time vs monthly), app/log limits, and SSO tier placement are cited inconsistently; Enterprise is custom (~$150K/yr AWS Marketplace starting point); GitHub-star counts vary (~139K most recent). Seed 'Sandbox free (200 credits); Professional $59/mo ($590/yr); Team $159/mo ($1,590/yr); self-hosted separate' is accurate and current - note the 200 Sandbox credits are ONE-TIME, credits meter model calls (BYOK bypasses), and the modified-Apache-2.0 license restricts multi-tenant commercial self-hosting.
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Alternatives to Dify
The closest documented capability profiles to Dify among agent builders tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Langflow10.0 / 14Adds documented Browser & Computer UseDify vs Langflow →
- Altilia11.5 / 14Adds documented Human Oversight & Guardrails
- AutoGPT10.5 / 14Adds documented Human Oversight & Guardrails
- StackAI11.5 / 14Adds documented Human Oversight & GuardrailsDify vs StackAI →
- StackBlitz Bolt8.5 / 14Adds documented Human Oversight & Guardrails
- Superblocks11.5 / 14Adds documented Human Oversight & Guardrails
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded