Flowise vs E2B
A detailed comparison to help you choose between Flowise and E2B.
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Verdict: E2B wins
E2B scores 4.1/5, edging out Flowise at 4.0/5. AI engineers whose agents execute generated or untrusted code and who want isolated, metered-by-the-second sandboxes instead of running that code on production servers.
Flowise Visual LLM app builder with drag and drop | E2B Secure cloud sandbox environment for AI agent execution and testing | |
|---|---|---|
| Rating | 4.0 (1 review) | 4.1 (1 review) |
| Pricing Model | freemium | freemium |
| Starting Price | Free tier available | Free tier available |
| Best For | Developers and technical teams who want visual control over LLM pipelines and are happy to self-host or manage their own production runtime. | AI engineers whose agents execute generated or untrusted code and who want isolated, metered-by-the-second sandboxes instead of running that code on production servers. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | open sourceno code | free tierapi accessopen source |
| Visit Flowise → | Visit E2B → |
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
E2B
Pros
- + Sub-second sandbox startup in my quickstart runs — create, execute, and read files felt like spawning a process, not provisioning infrastructure
- + Firecracker microVM isolation with outbound network controls kept agent-generated code away from my credentials and services
- + Per-second billing with storage included and a public workload estimator — I could model my ~$166/month usage case before adding the Pro base fee
- + Hobby tier is a real evaluation: $0 with a one-time $100 usage credit, no credit card, 20 concurrent sandboxes
- + Python and JavaScript SDKs with pause/resume persistence and prebuilt dependency templates shorten integration to an afternoon
Cons
- - No local-only mode — the core product assumes cloud connectivity, which fails airgapped requirements without an enterprise deal
- - Per-second CPU/RAM billing punishes sloppy sandbox lifecycle management; idle open sandboxes keep metering
- - Concurrency ceilings (20 on Hobby, 100 on Pro) require paid add-ons for larger fleets — up to 1,100 concurrent on Pro+
- - Deliberately narrow: no agent orchestration, memory, or model routing included — bring your own framework
- - Some integrations (the Vercel AI SDK 7 sandbox package) were marked experimental in the docs at time of writing
Frequently Asked Questions
Which is better, Flowise or E2B?▼
E2B scores higher at 4.1/5 vs 4.0/5 for Flowise, making it the better-rated option in our comparison.
What is the difference between Flowise and E2B?▼
Flowise: Flowise is an open-source visual builder for LLM applications and agents, wiring models, tools and data sources together on a canvas. E2B: E2B gives each AI agent an isolated cloud sandbox to run code, browse and use tools, hosted by E2B or in your own AWS or GCP account.
Is Flowise or E2B more affordable?▼
Flowise starts at €0/mo, E2B starts at €0/mo. Check the comparison table above for current pricing.
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