Monthly LLM stack audit — compare your current models against latest benchmarks and pricing from OpenRouter. Identifies potential savings, upgrades, and better alternatives by category (reasoning, code, fast, cheap, vision). Use for optimizing AI costs and staying on the frontier.
Monthly LLM stack audit — compare your current models against latest benchmarks and pricing from OpenRouter. Identifies potential savings, upgrades, and better alternatives by category (reasoning, code, fast, cheap, vision). Use for optimizing AI costs and staying on the frontier.
Monthly LLM stack audit — compare your current models against latest benchmarks and pricing from OpenRouter. Identifies potential savings, upgrades, and better alternatives by category (reasoning, code, fast, cheap, vision). Use for optimizing AI costs and staying on the frontier.
Compares against top alternatives in each category
Calculates potential monthly savings
Recommends upgrades or cost optimizations
Output Example
═══ LLM Stack Audit ═══
Your Models:
anthropic/claude-opus-4-6 $5.00/$25.00 per 1M tokens (in/out)
openai/gpt-4o $2.50/$10.00 per 1M tokens
google/gemini-2.0-flash $0.10/$0.40 per 1M tokens
Recommendations:
💡 For fast tasks: gemini-2.0-flash is 50x cheaper than opus
💡 Consider: deepseek/deepseek-r1 for reasoning at $0.55/$2.19
💡 Your stack covers: reasoning ✓, code ✓, fast ✓, vision ✓
