BurnRate
Local-first AI coding cost analytics. Tracks Claude Code, Cursor, Codex, Copilot, Windsurf, Cline, and Aider. Cost breakdowns, 23 optimization rules, rate limit monitoring, provider comparison, and PDF reports.
What is BurnRate?
BurnRate is a local-first AI coding cost analytics platform designed to help developers monitor and optimise spending across multiple AI coding assistants. It tracks usage and costs from Claude Code, Cursor, Codex, Copilot, Windsurf, Cline, and Aider in real-time, providing detailed cost breakdowns by provider, model, and individual agent. The tool runs locally on your machine with zero configuration required, meaning your data stays private and no cloud uploads are necessary. BurnRate is built for developers and teams who use multiple AI coding tools and want visibility into their AI infrastructure spending. It includes 23 built-in optimization rules to help reduce costs, rate limit monitoring to prevent unexpected overage charges, and generates exportable PDF reports for cost analysis and team budgeting. The freemium model makes it accessible for individual developers while offering advanced features for teams managing larger AI tool fleets.
Key Features
Multi-provider cost tracking
Monitors spending across Claude Code, Cursor, Codex, Copilot, Windsurf, Cline, and Aider in unified dashboard
Local-first architecture
All data processing happens locally with zero configuration and no cloud dependency
Cost optimization rules
23 pre-built optimization rules to identify and reduce unnecessary spending patterns
Rate limit monitoring
Real-time alerts and tracking to prevent hitting provider rate limits and unexpected charges
Provider comparison
Side-by-side cost analysis across different AI providers to identify most cost-efficient options
PDF report generation
Exportable reports for cost analysis, team sharing, and budget planning
Pros & Cons
Advantages
- Privacy-focused local-first design keeps sensitive usage data on your machine
- Supports the widest range of popular AI coding tools in one dashboard
- Zero configuration setup makes it immediately useful without complex onboarding
- Freemium model with no paywall for basic cost tracking functionality
- Built-in optimization rules provide practical advice without manual analysis
Limitations
- Requires manual installation and setup on local machine, limiting accessibility for non-technical users
- Limited to tracking coding assistants only; doesn't monitor other AI tool spending categories
- Effectiveness of optimization rules depends on developer adoption and workflow changes
Use Cases
Individual developers tracking spending across multiple AI coding assistants to identify cost-saving opportunities
Engineering teams monitoring collective AI tool spending and optimising provider selection
Startups managing burn rate on AI infrastructure as part of overall cost control
Freelancers and agencies billing clients for AI-assisted development and needing cost transparency
DevOps teams implementing cost governance policies for AI tool usage across the organization