AI Agent Index

Kilo Code vs Refact.ai (2026)

Side-by-side comparison of Kilo Code vs Refact.ai — pricing, capabilities, integrations, deployment complexity, and ratings. Last updated May 2026.

Data sourced from The AI Agent Index · Updated daily

Kilo Code logo

Kilo Code

by Kilo Code

Open-source AI coding agent for VS Code, JetBrains, and CLI with parallel agents, multi-model comparisons, and 500+ models including Claude, GPT-5, and Gemini through transparent BYOK pricing.

freemiumB2B
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Refact.ai logo

Refact.ai

by Refact

Open-source AI coding agent with self-hosted deployment, BYOK model support, and custom fine-tuning. Free open-source; Enterprise custom. NOTE: Refact Cloud shutting down — self-hosted/Enterprise only.

freeENTERPRISE
Visit Refact.ai
Kilo Code
Refact.ai
Pricing model
freemium
free
Starting price
Free
Free
Customer segment
B2B
ENTERPRISE
Deployment
cloud
ide, self-hosted
Setup difficulty
easy
moderate
Avg setup time
5 minutes
2-8 weeks for self-hosted deployment (provision infrastructure, deploy Refact, configure LLM access, fine-tune on private codebase); custom for Enterprise
Editorial rating
4.5 / 5
3.8 / 5

Capabilities

Kilo Code

code-generationagentic-codingautonomousidemulti-file-editingautocompleteterminal-agentbyokopen-source

Refact.ai

autocompletecode-generationbyokopen-sourcemulti-file-editing

Pros & Limitations

Editorial assessment

Kilo Code

Pros

  • Open-source MIT-licensed and model-agnostic, connect any of 500+ models including Claude, GPT-5, and Gemini through BYOK with no markup
  • Multi-mode architecture (Architect, Code, Debug, Ask, Orchestrator) handles planning and execution as separate concerns with auditable workflows
  • Trusted by engineering teams at Meta, Amazon, Airbnb, PayPal, Square, and Red Hat with $8M seed funding and 2M+ developer users

Limitations

  • Enterprise governance features (SSO, granular audit logs, RBAC) are less mature than GitHub Copilot or Cursor for procurement-heavy organizations
  • Setup complexity for advanced features (Memory Bank, custom modes, MCP tools) has a real learning curve
  • Local model performance depends heavily on hardware, expect uneven results without sufficient compute for larger LLMs

Refact.ai

Pros

  • On-premise deployment with private fine-tuning addresses regulated industry needs — Refact runs entirely within enterprise infrastructure with custom model training on private codebases, materially better than hosted-only AI coding tools for financial services, healthcare, and government
  • Open-source under permissive licensing — code is auditable, forkable, self-hostable, and protected from vendor lock-in concerns that block proprietary AI coding tools at security-conscious organizations
  • BYOK and multi-LLM support — pay only for actual API usage rather than fixed subscriptions, with full flexibility to switch between Claude, GPT, Gemini, and local models based on cost and capability needs

Limitations

  • Refact Cloud shutting down creates uncertainty for hosted-tier users — users who relied on the cloud service must migrate to self-hosted deployments or Enterprise contracts, which is a transition cost that doesn't exist with stable hosted alternatives (Cursor, Copilot)
  • Self-hosted deployment requires meaningful operational investment — running Refact on-premise means provisioning infrastructure, managing model deployments, and operating the AI stack in-house, which is overhead that hosted alternatives avoid entirely
  • Smaller installed base than Cursor or Copilot — Refact has solid niche positioning for security-conscious enterprises but lags broader AI coding tool adoption, which means fewer community resources, integration examples, and learning materials

Frequently asked questions

What is the difference between Kilo Code vs Refact.ai?

See the full comparison above.

Which is best for my team — Kilo Code vs Refact.ai?

How does pricing compare between Kilo Code vs Refact.ai?

Kilo Code uses a freemium model, starting at $0 per month. Refact.ai uses a free model, starting at $0 per month.

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