Real data. No sponsored rankings. No "it depends" non-answers.
Leaper is a technical blog covering the decisions that actually cost developers time and money: which cloud platform to use, which LLM API delivers the best value, how to structure a RAG pipeline that doesn't fall apart in production, when to self-host vs. pay for managed services.
Every article is built around real data—actual bills, benchmark results, production metrics—not synthetic tests or vendor-provided numbers.
The goal: give you the information you need to make an informed decision in 15 minutes, not 15 hours of reading docs and blog posts with undisclosed affiliate relationships.
Most technology comparisons online have a problem: they're either written by vendors who have an obvious incentive, written by people who haven't used the thing in production, or written in 2022 and never updated as pricing changed.
The questions developers are actually asking—"how much will this cost at 500k requests/month?", "will Gemini Flash be good enough for my classification task?", "what breaks when you move from Vercel to Cloudflare?"—rarely get straight answers.
Leaper is an attempt to fix that with specifics: real numbers from real usage, honest trade-off analysis, and conclusions that aren't hedged into meaninglessness.
API cost comparisons across OpenAI, Anthropic, and Google. RAG architecture patterns and when fine-tuning actually makes sense. AI agent frameworks benchmarked against each other. Security considerations for AI in production pipelines.
Vercel vs. Cloudflare vs. AWS vs. self-hosting, with actual billing data. Serverless compute trade-offs. When the managed service is worth the premium and when it isn't. Real CDN and edge performance benchmarks.
Vector database comparisons with benchmark results. BaaS pricing at different traffic tiers. When to reach for a managed database and when Postgres on a $6 VPS is the right answer.
CI/CD integration patterns. IaC approaches. Observability trade-offs. The deployment mistakes that cost hours, and how to not make them.
Take the numbers as a starting point, not a verdict. Real-world costs vary based on traffic pattern, request size, caching behavior, and a dozen other factors. Use the data to calibrate your own estimates, not to copy them directly.
When something here is wrong or outdated, let us know. Pricing changes fast and infrastructure articles go stale. We'd rather fix a mistake than leave bad data online.
Have a comparison you'd like to see? Running a different stack and have cost data to share? Found a number that doesn't add up? Reach out.