Gumloop vs Flowise
A detailed comparison to help you choose between Gumloop and Flowise.
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Verdict: Flowise wins
Flowise scores 4.0/5, edging out Gumloop at 3.6/5. Developers and technical teams who want visual control over LLM pipelines and are happy to self-host or manage their own production runtime.
Gumloop Build AI agents with no-code workflows and API integrations | Flowise Visual LLM app builder with drag and drop | |
|---|---|---|
| Rating | 3.6 (1 review) | 4.0 (1 review) |
| Pricing Model | freemium | freemium |
| Starting Price | Free tier available | Free tier available |
| Best For | Teams that want non-engineers building AI-shaped automations — research, scraping, summarization — under centralized IT control and spend oversight. | Developers and technical teams who want visual control over LLM pipelines and are happy to self-host or manage their own production runtime. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | no codefree tier | open sourceno code |
| Visit Gumloop → | Visit Flowise → |
Gumloop
Pros
- + Fastest AI-flow building I tested: scrape-summarize-extract agent went up in ~40 minutes, with a model swap as a drop-down change
- + IT control features are real on Pro (agent-scoped connector policies, shared credentials, usage analytics) and org-wide on Enterprise
- + Unlimited agents, seats, and teams on Pro from $37/mo — no per-seat tax, unlike most rivals (gumloop.com/pricing)
- + Hosted scraping node handled a JS-heavy site my plain HTTP attempt failed on
- + Well funded for its age: $17M Series A (Nexus) and a $50M Series B, with named customers like Shopify and Instacart
Cons
- - No free plan — 14-day trial only — and the 8% orchestration fee on top of credits makes heavy usage hard to predict
- - Credit costs vary by node and model; my scrape-heavy flow cost roughly triple the targeted version before I tuned it
- - Shallow for engineers: no code steps with real package access, no self-hosting (Enterprise VPC only), thin connector breadth versus Zapier/Make
- - Agent memory is flow-scoped — persistent cross-run context is early despite the self-improving-agent marketing
- - Pro concurrency caps (5 workflow runs, 25 agent chats) queued my bulk jobs; throughput is not the strong suit yet
Flowise
Pros
- + Node canvas gives LangChain-level control over retrieval, agents, and tools without writing code — my retrieval agent took one sitting
- + Self-host path is real: npm or Docker, minutes to localhost:3000, Apache 2.0 core license
- + Human-in-the-loop review nodes make the agents-propose-humans-release pattern easy to wire
- + Wide model and vector-store support (100+ LLMs, embeddings, vector DBs per the vendor) keeps you off proprietary lock-in
- + Evaluations, metrics, and run observability are built into the builder rather than bolted on
Cons
- - Node picker presumes you understand embeddings, chains, and retrieval strategies — beginners are lost quickly
- - Production self-host means doing your own persistence, secrets, queue/workers, and uptime — time not visible in the free price
- - Enterprise identity and permission features live under a commercial license inside the same repo
- - Cloud free tier (100 predictions/month) is too small to judge real performance
- - Fast-moving node surface and uneven community templates mean upgrades can break flows
Frequently Asked Questions
Which is better, Gumloop or Flowise?▼
Flowise scores higher at 4.0/5 vs 3.6/5 for Gumloop, making it the better-rated option in our comparison.
What is the difference between Gumloop and Flowise?▼
Gumloop: Gumloop is a no-code builder for AI agents and automations, where teams connect models and apps on a visual canvas. It is aimed at companies that want non-engineers to build automations under IT control. Flowise: Flowise is an open-source visual builder for LLM applications and agents, wiring models, tools and data sources together on a canvas.
Is Gumloop or Flowise more affordable?▼
Gumloop starts at €0/mo, Flowise starts at €0/mo. Check the comparison table above for current pricing.
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