# Modal vs n8n

Modal records 1,196,021 monthly visits with +30.2% month-over-month growth and Freemium, Contact for Pricing pricing. n8n records 4,522,449 monthly visits with -7.4% growth and Freemium pricing.

| Metric | [Modal](https://openaitools.app/tool/modal-com) | [n8n](https://openaitools.app/tool/n8n) |
| :--- | :--- | :--- |
| Website URL | https://modal.com | https://n8n.io |
| Categories | AI Developer Tools, AI API, Large Language Models (LLMs), AI Models | AI Workflow, AI Agent, No-Code&Low-Code, AI Developer Tools |
| Pricing Model | Freemium, Contact for Pricing | Freemium |
| Monthly Visits | 1,196,021 | 4,522,449 |
| MoM Growth Rate | +30.2% | -7.4% |
| Primary Market | United States | India |
| Direct Visits | 845,636 | 1,565,199 |
| Review Score | 4.8 | 4.7 |
| Saved Count | 3 | 4 |
| Supported Platforms | Website | Website |

## Modal

Modal provides cloud infrastructure aimed squarely at AI and data teams. The core idea is that developers write ordinary Python, decorate functions or define container images, and Modal takes care of the underlying compute: scheduling containers, attaching GPUs, autoscaling from zero and back, and exposing endpoints over HTTPS. Infrastructure concerns like networking, storage, and capacity management are abstracted away, so a workload that runs on a laptop can run the same way across a fleet.

The platform is organised around a few primitives. Functions handle serverless compute and can fan out across thousands of GPUs for parallel or batch work. Sandboxes provide isolated environments for coding agents, reinforcement learning rollouts, and other untrusted code, with sub-second start times and support for very high concurrency. Training covers fine-tuning, reinforcement learning, and evaluation on single or multi-node GPU capacity. On the inference side, Modal offers OpenAI-compatible endpoints for open-weight models and lets teams deploy custom stacks and tune endpoints to match their traffic shape.

Underneath, Modal runs its own container runtime and image system designed for large images and fast GPU scheduling, along with a distributed filesystem for fast access to model weights and datasets. Capacity is drawn from a multi-cloud pool spanning many regions, with automatic routing to available hardware and continuous fleet health checks. Billing is usage-based, charged by the second while code runs, with granular cost controls. The company offers a free starting allowance and scalable paid usage, and markets to enterprises with SOC 2 Type II compliance and HIPAA readiness.

**Pricing & Plans:** Modal uses usage-based pricing billed by the second: a free monthly compute allowance gets you started, then you pay for the CPU, memory, and GPU resources your workloads consume. Enterprise plans and startup credits are available, and custom pricing can be discussed with sales.

- **Serverless Python functions:** Write plain Python, attach GPUs or containers, and deploy HTTPS endpoints that autoscale with traffic and scale to zero when idle.
- **Sandboxes for agents:** Launch isolated, secure environments for coding agents, RL rollouts, and untrusted code, with sub-second starts and support for over a million concurrent sandboxes.
- **Training and fine-tuning on demand:** Run fine-tunes, LoRA, full training, and reinforcement learning on elastic single or multi-node GPU capacity with no quota requests.
- **Model inference and endpoints:** Serve LLMs and image, video, or audio models through OpenAI-compatible endpoints, or bring your own inference stack and let Modal handle the infrastructure.
- **Fast storage and multi-cloud capacity:** A distributed filesystem loads large images and model weights at full bandwidth, while a pool spanning 20+ clouds routes workloads to the right hardware and region.

**Strengths:** Python-native developer experience with almost no infrastructure boilerplate; Scales from zero to thousands of GPUs with per-second, usage-based billing; Sandboxes are well suited to agentic and untrusted-code workloads; Multi-cloud capacity spans many regions with out-of-the-box observability and enterprise compliance

**Limitations:** Billed by real usage, so heavy GPU workloads can get expensive quickly without cost controls; Some advanced inference and enterprise features require working with the team rather than self-serve signup; The serverless model can feel less familiar to teams used to managing their own VMs or Kubernetes clusters

[Profile (Markdown)](https://openaitools.app/tool/modal-com.md)

## n8n

n8n is a workflow automation platform built for technical teams who want automation they can actually read and audit. Rather than hiding logic behind opaque configuration, every step stays open: you can see what a node does and explain the whole flow to whoever runs it. It combines a drag-and-drop visual builder with the ability to drop into code at any point, so simple tasks stay simple while complex ones remain possible.

A major focus of the current product is AI agents. You can connect any model, watch an agent work step by step in the same workflow view, open past runs, and constrain behaviour with structured inputs and outputs, rule-based automation and human-in-the-loop approval gates. That makes it practical to put agents into processes like refund handling, alert triage, lead qualification and security investigation without losing control.

n8n is open source and can be self-hosted on-prem or with Docker to keep data in your own environment, or used as a hosted service. Enterprise capabilities add SSO with SAML and LDAP, RBAC, encrypted secret stores, audit logs, log streaming to SIEM systems, isolated environments and Git-based control. Integrations span 500+ native services, arbitrary HTTP APIs and MCP connections to agents and coding assistants.

**Pricing & Plans:** n8n offers a free self-hosted open-source edition, a paid cloud service with a free trial, tiered paid plans, and enterprise pricing on request. Feature limits scale with plan tier, so check the official pricing page for current details.

- **Visual builder with code escape hatch:** Build automations with a visual node editor, then insert JavaScript or Python code nodes when you need custom logic.
- **500+ integrations and any API:** Connect to 500+ native services, any REST API via HTTP nodes, and any agent or coding assistant through MCP.
- **AI agents you can follow and trust:** Run agents alongside regular steps, inspect every decision, and add structured inputs, guardrails and human approval steps.
- **Observability and reproducible runs:** Watch workflows execute live, open past runs, replay a run with mocked data and re-run just the step that failed.
- **Self-host or cloud with governance:** Deploy on your own infrastructure with Docker or on-prem, or use the hosted cloud product, with version history and RBAC.

**Strengths:** Open source and self-hostable, keeping data in your own environment; Visual builder plus full code access for complex workflows; Strong observability: live runs, past-run inspection and step-level retries; 500+ integrations and generic HTTP nodes cover almost any service

[Profile (Markdown)](https://openaitools.app/tool/n8n.md)

## Frequently Asked Questions

### How do Modal and n8n compare in monthly traffic?

Modal has 1,196,021 monthly visits, while n8n has 4,522,449. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Modal has a month-over-month growth rate of +30.2%; n8n has -7.4%.

### How does pricing compare?

Modal: Freemium, Contact for Pricing. Modal uses usage-based pricing billed by the second: a free monthly compute allowance gets you started, then you pay for the CPU, memory, and GPU resources your workloads consume. Enterprise plans and startup credits are available, and custom pricing can be discussed with sales. n8n: Freemium. n8n offers a free self-hosted open-source edition, a paid cloud service with a free trial, tiered paid plans, and enterprise pricing on request. Feature limits scale with plan tier, so check the official pricing page for current details.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Unmatched ecosystem of app connectors and reliability, but significantly more expensive and lacks n8n's self-hosting freedom. | [.md](https://openaitools.app/tool/zapier-com.md) |
| 2 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Extremely fast serverless execution optimized specifically for generative media models rather than general Python code. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 3 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | Provides flexible GPU infrastructure and serverless endpoints, though less focused on pure Python function decorators. | [.md](https://openaitools.app/tool/runpod.md) |
| 4 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 5 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Focuses heavily on managed open-source model inference APIs rather than arbitrary custom container execution. | [.md](https://openaitools.app/tool/together-ai.md) |
| 6 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Rent cloud GPUs by the second from a global marketplace | [.md](https://openaitools.app/tool/vast-ai.md) |
| 7 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | Delivers robust enterprise GPU clusters and managed inference, requiring more infrastructure setup than Modal's serverless approach. | [.md](https://openaitools.app/tool/nebius.md) |
| 8 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Easier model packaging via Cog, but offers less arbitrary serverless Python container execution than Modal. | [.md](https://openaitools.app/tool/replicate-ai.md) |
| 9 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Outstanding open-source visual canvas for RAG pipelines and LLM agents, but less suited for general API integrations. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 10 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Multiplayer AI where people and agents work side by side | [.md](https://openaitools.app/tool/dust.md) |

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Source: https://openaitools.app/compare/modal-com-vs-n8n

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