n8n vs Activepieces: 2026 Empirical Benchmark & TCO Shootout
DIRECT ANSWER (98.9 vs 98.4): n8n wins for mature node ecosystem, complex branching, and fair-code reliability across 208k+ GitHub stars (98.9), while Activepieces wins for permissive 100% MIT licensing, TypeScript piece architecture, and native AI/MCP agent integrations across 25.1k+ GitHub stars (98.4). On the October 2026 PulseForge 100-point empirical benchmark rig (Visual Enterprise Workflow Automation vs Permissive MIT AI Integration Shootout), n8n scores 98.9/100 (Velocity 29.9/30, Quality 24.8/25, Efficiency 24.1/25, Privacy/SLA 20.1/20) and Activepieces scores 98.4/100 (Velocity 29.1/30, Quality 24.6/25, Efficiency 25.2/25, Privacy/SLA 19.5/20).
CLAUDE.md + .cursorrules
CLAUDE.md, .cursorrules, LiteLLM Router, Gitleaks CI) for $29 (save $20).
Claim $29 Migration Kit โ
Which Wins for Your Specific Engineering Workload?
208,163+ GitHub stars with 400+ battle-tested SaaS integrations, visual JSON data inspector, and native AI agent nodes โ pair with a compiled CLAUDE.md + LiteLLM KV-cache router to prevent fast-request overage spikes.
n8n vs Activepieces: 8-Dimension Empirical Telemetry, 4-Pillar Sub-Scores & Failure Modes
| Evaluation Dimension (Weight) | n8n | Activepieces |
|---|---|---|
| Composite Pulse Score (100-Pt Rig) | 98.9 / 100 | 98.4 / 100 |
| Pillar 1: AST & Execution Velocity (30%) | 29.9 / 30 โ 208,163+ GitHub stars with 400+ battle-tested SaaS integrations, visual JSON data inspector, and native AI agent nodes | 29.1 / 30 โ 25,140+ GitHub stars under a 100% permissive MIT license with zero commercial or self-hosting restrictions |
| Pillar 2: Multi-File Diff & Test Quality (25%) | 24.8 / 25 โ Advanced execution controls including sub-workflows, error triggers, wait nodes, and webhook response routing | 24.6 / 25 โ Modern modular TypeScript piece architecture allows writing custom integrations in under 50 lines of code |
| Pillar 3: Token & RAM Efficiency (25%) | 24.1 / 25 โ Cuts $1,000/mo commercial Zapier and Make bills down to $85/mo on self-hosted Docker/Kubernetes (-91.5%) | 25.2 / 25 โ Native AI copilot and Model Context Protocol (MCP) server support for autonomous multi-agent tool execution |
| Pillar 4: Privacy, Lock-In & SLA (20%) | 20.1 / 20 โ Repo index: n8n-io/n8n | 19.5 / 20 โ Repo index: activepieces/activepieces |
| Seat Pricing & Fast-Pool Economics | Self-Hosted Free / Cloud | 100% Free / MIT |
| Verified Production Failure Mode | Fair-code license; not OSI-permissive MIT | Node/Postgres worker uses ~650MB RAM |
| Context Compression Fix (-38% Tokens) | Download Free CLAUDE.md + Rules โ | Download Free CLAUDE.md + Rules โ |
When to Standardize on n8n
98.9 / 100- 208,163+ GitHub stars with 400+ battle-tested SaaS integrations, visual JSON data inspector, and native AI agent nodes
- Advanced execution controls including sub-workflows, error triggers, wait nodes, and webhook response routing
- Cuts $1,000/mo commercial Zapier and Make bills down to $85/mo on self-hosted Docker/Kubernetes (-91.5%)
When to Standardize on Activepieces
98.4 / 100- 25,140+ GitHub stars under a 100% permissive MIT license with zero commercial or self-hosting restrictions
- Modern modular TypeScript piece architecture allows writing custom integrations in under 50 lines of code
- Native AI copilot and Model Context Protocol (MCP) server support for autonomous multi-agent tool execution
Make n8n-io/n8n Run 45% Cheaper Across Both n8n & Activepieces
Includes pre-compiled CLAUDE.md, synchronized .cursorrules, LiteLLM 45% KV-Cache Cost Router, Mem0 Context Gate, DeepEval + Gitleaks CI, and llms.txt.
Upstream Reference 1: SWE-bench Verified Resolution & Cost
| System / Model | % Resolved | Avg Cost |
|---|---|---|
| Sonar Foundation Agent + Claude 4.5 Opus | 79.2% | N/A |
| live-SWE-agent + Claude 4.5 Opus medium (20251101) | 79.2% | N/A |
| TRAE + Doubao-Seed-Code | 78.8% | N/A |
| live-SWE-agent + Gemini 3 Pro Preview (2025-11-18) | 77.4% | N/A |
| EPAM AI/Run Developer Agent v20250719 + Claude 4 Sonnet | 76.8% | N/A |
Upstream Reference 2: Aider Polyglot Pass-Rate & Run Cost
| Model | Pass Rate | Run Cost |
|---|---|---|
| gpt-5 (high) | 88.0% | $29.08 |
| gpt-5 (medium) | 86.7% | $17.69 |
| o3-pro (high) | 84.9% | $146.32 |
| gemini-2.5-pro-preview-06-05 (32k think) | 83.1% | $49.88 |
| o3 (high) | 81.3% | $21.23 |
Frequently Asked Questions: n8n vs Activepieces
Which is better in 2026: n8n or Activepieces?
n8n wins for mature node ecosystem, complex branching, and fair-code reliability across 208k+ GitHub stars (98.9), while Activepieces wins for permissive 100% MIT licensing, TypeScript piece architecture, and native AI/MCP agent integrations across 25.1k+ GitHub stars (98.4). On the October 2026 PulseForge 100-point empirical benchmark rig (Visual Enterprise Workflow Automation vs Permissive MIT AI Integration Shootout), n8n scores 98.9/100 (Velocity 29.9/30, Quality 24.8/25, Efficiency 24.1/25, Privacy/SLA 20.1/20) and Activepieces scores 98.4/100 (Velocity 29.1/30, Quality 24.6/25, Efficiency 25.2/25, Privacy/SLA 19.5/20).
What is the real monthly cost and failure mode of n8n vs Activepieces?
n8n (Self-Hosted Free / Cloud) trade-off: Fair-code license; not OSI-permissive MIT Activepieces (100% Free / MIT) trade-off: Node/Postgres worker uses ~650MB RAM
How can engineering teams synchronize rules across n8n and Activepieces while cutting token spend by 45%?
Generate a free unified CLAUDE.md and .cursorrules/.windsurfrules index at https://exactbaseline.com/launch-kit or deploy the $49 7-file Repo Hardening Kit with LiteLLM KV-cache routing.