REPORTS

The 2026 Developer
AI Spending Benchmark

An analysis of 1.2B+ tokens reveals why 40% of teams are over-spending on LLM API costs - and how to fix it.

Join 800+ developers to get the full PDF report.

40%
Avg. Waste on Over-Provisioning
$1,240
Monthly Savings per Engineer
1.2B
Tokens Analyzed

Key Findings

In our comprehensive study of modern AI agent workflows, we found that developers using tools like Cursor and Claude Code often fall into the "Model Trap"-using high-cost models (like Claude 3 Opus) for tasks that could be handled by faster, cheaper alternatives (like Sonnet 3.5).

  • Context Bloat: 25% of costs come from unnecessary file inclusions.
  • Model Mismatch: 15% of requests could be 10x cheaper with no quality loss.
  • Latency Spikes: Infrastructure overhead accounts for 12% of perceived latency.