Aryan Agarwal
Dify and Gravity get compared a lot, but they are not the same kind of product. Dify is a Swiss army knife for LLM-powered apps, with chat, RAG, and agents under one roof. Gravity is a focused runtime for operational agents that take action in the world.
I will be honest about the overlap and the gap.
What Dify is, and where it actually shines
Dify is an open-source LLMOps platform. The product gives you a visual builder for prompt apps, a workflow canvas for chains, a RAG pipeline with document ingestion, and an agent surface. You can self-host with Docker or use Dify Cloud.
It shines for:
- Building chatbots and customer-support assistants that need RAG.
- Document Q-and-A products where the heavy lifting is retrieval.
- Teams that want to manage prompts as first-class artifacts.
- Companies that need self-hosting for data residency.
- Mixed teams of engineers and product managers who can collaborate on the canvas.
The community is large, the project ships fast, and the platform packs a lot of capability for an OSS tool.
What Gravity does differently
Gravity is built for a different job. The job is operational agents that run forever and take action. Inbox triage. Lead qualification. Failed-payment recovery. Competitor monitoring. The agent has goals, tools, schedules, and stop conditions.
A Gravity prompt looks like:
"Every Monday at 8am IST, check our Stripe dashboard for failed payments from the last 7 days. Email each customer a friendly retry link. Wait 48 hours, then escalate to me if no resolution. Stop at 50 emails per week."
That sentence becomes a schedule, a Stripe pull, a customer email loop, a wait, an escalation, and a rate limit. No canvas. No code. The runtime composes the work. Describing outcomes is the entire interface.
Side-by-side capability comparison
| Capability | Dify | Gravity |
|---|---|---|
| Primary job | Chatbots, RAG, prompt apps | Action-taking operational agents |
| Setup model | Canvas plus prompt editor | One sentence |
| Hosting | Self-hosted or Dify Cloud | Fully hosted only |
| RAG depth | Strong, first-class document ingestion | Available via connectors, not the focus |
| Schedule and triggers | External or workflow nodes | First-class in the prompt |
| Approval queues | You build them as nodes | Built into the runtime |
| Observability | Built-in app analytics | Built-in run history |
| Open source | Yes, with usage clauses | No |
| Pricing model | Free OSS plus infra, or Cloud tiers | Bundled monthly fee |
The chat-first vs ops-first split
If your agent is a conversation, Dify is excellent. The product was designed around chat, document retrieval, and prompt iteration. It does those things well.
If your agent is a process that runs while nobody is watching, the design centre of gravity is different. You need scheduling, idempotency, rate limits, replans, escalations, and audit trails. Gravity puts those at the centre. Dify can do them with effort, but they are not the design centre.
The deciding question: does your agent talk or does it act? If it talks, Dify. If it acts, Gravity. Many teams need both.
Pricing reality
- Dify OSS: Free. Add infra, vector store, and LLM spend.
- Dify Cloud: Tiered. Sandbox is free. Higher tiers scale with usage.
- Gravity: Bundled monthly fee, runtime plus observability included.
Total cost of ownership depends on whether you have infra already, how many agents you ship, and how often you change them. How to estimate agent cost before deploying walks through the math.
When Dify is the right choice
- Your agent is mostly a conversational app or RAG product.
- You need self-hosting for compliance.
- You manage prompts as artifacts versioned by your team.
- You want a generous OSS surface area and a busy community.
- You have engineers who enjoy the canvas.
When Gravity is the right choice
- Your agent is operational, scheduled, action-taking.
- You want approval queues, escalations, and stop conditions out of the box.
- Your operator is not technical.
- You want one place to see what went wrong on every run.
- You change the agent's behaviour weekly.
Migration: what changes if you switch
Most operational agents migrate cleanly. Conversational and RAG products need more work because the indexing layer in Dify does not have a direct equivalent in Gravity. Steps:
- Write the outcome sentence.
- Reconnect OAuths in Gravity.
- Run a dry run, compare outputs to the Dify app.
- Cut over.
- For RAG, prefer keeping Dify for the chat surface and using Gravity for action-taking around it.
Frequently asked questions
Is Dify open source?
Yes. Dify is open source under a permissive license with some commercial-use clauses. You can self-host it, fork it, or use the Dify Cloud offering.
Is Dify a chatbot platform or an agent platform?
Both, by design. Dify started as an LLMOps tool for chatbots and RAG, and has added agent primitives over time. The strength is still in chat-like applications and document Q-and-A.
Where does Gravity fit relative to Dify?
Gravity targets operational agents that run on a schedule, take actions in third-party tools, and need replanning. Dify targets conversational and retrieval-heavy applications. Different jobs, sometimes overlapping.
Which is cheaper to run at scale?
Dify can be cheaper if you self-host on existing infra. Gravity tends to be cheaper if you measure engineer hours per agent per month rather than platform sticker.
Can I switch from Dify to Gravity quickly?
Yes, for most operational use cases. You write the outcome sentence, connect the same OAuths, run a dry run, and cut over. RAG-heavy apps need more work because the document indexing layer is different.
Three takeaways before you close this tab
- Dify is broad. Gravity is focused. Both can be the right tool depending on the job.
- If your agent talks, pick Dify. If your agent acts, pick Gravity.
- You can run both. Many real stacks use Dify for chat and Gravity for action.
Sources
- Dify. "Official documentation." docs.dify.ai
- GitHub. "Dify repository." github.com/langgenius/dify
- Dify. "Pricing page." dify.ai/pricing