CleanSlop vs Magnitude: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of CleanSlop and Magnitude — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
CleanSlop
CleanSlop
Scans vibe-coded apps for launch-blocking issues like leaked keys and data exposure, and reports what to fix first, right from your coding agent.
Key features
- Agent-Native Scanning: Tell Claude Code, Codex, Cursor or other agents to scan with CleanSlop and fix findings where you build.
- System-Level Code Mapping: Maps routes, background jobs, data and external services so each finding follows a real call path.
- Prioritized Reports: Findings grouped as needs attention, worth a look and minor, worst first.
- Evidence for Every Finding: Shows where each issue lives in your code and why it was flagged.
- Plain-English Fixes: Explains what is wrong, why it matters and what to do about it.
- Copy for LLM: Hands any report to your AI tool so it can apply the fixes.
- GitHub App Integration: Scan only the repositories you select, read-only access.
- Expert Triage Calls: Book a 15-minute call with a CleanSlop engineer to walk through findings.
Best for
- A solo founder checks a Next.js and Supabase app built with an AI coding assistant before launching.
- A developer discovers an exposed AI API key bundled into browser code and moves it to a server route.
- A side-project builder verifies that one user's data cannot be read by another through database policies.
- A Claude Code user runs a scan from the terminal and has the agent fix the top findings.
- A team lead gets a short prioritized list instead of hundreds of linter warnings.
- An indie hacker books an expert triage call to confirm an ambiguous finding.
Magnitude
Magnitude
Open-source inference server that profiles your hardware, picks and tunes the best local models for it, and plugs them into the coding agent you already use.
Key features
- Hardware Profiling: Inspects your CPU, GPU, and memory and recommends only the local models that will actually run well on that machine.
- Automatic Model Setup: Downloads, tunes, and serves the models you select so you never hand-configure quantization, context length, or serving flags.
- Agent-First Installation: Send one prompt to your existing coding agent and it profiles the hardware, walks you through model choice, and switches itself over to the local endpoint.
- Broad Harness Compatibility: Works as a drop-in backend for Pi, OpenCode, Hermes, OpenClaw, Codex, Claude Code, Oh My Pi, and Cline.
- Built-In Harness: Ships its own agent harness for users who want local coding assistance without adopting a separate client.
- Fully Offline Operation: Models, prompts, and files stay on the machine, so there are no API keys, no token costs, and no rate limits.
- Cross-Platform Support: Runs natively on macOS and Linux, with Windows supported through WSL.
- CLI Distribution: Installed and managed through the @magnitudedev/cli npm package with an interactive setup flow.
Best for
- Private Codebase Work: Run an agent against proprietary source without sending any of it to a hosted model provider.
- Zero-Cost Development: Replace metered API calls with local inference for high-volume experimentation and long agent runs.
- Offline and Air-Gapped Environments: Keep a coding agent working on a plane, in a secure facility, or anywhere with no reliable network.
- Hardware Evaluation: Discover which local models a given laptop or workstation can realistically serve before committing to a setup.
- Existing Agent Migration: Point a harness you already use at a local backend without changing your workflow or tooling.
- Compliance-Constrained Teams: Satisfy data-residency requirements by keeping prompts and outputs on company-controlled machines.