Want to cut your LLM API costs? Start with visibility
“Why is this month's OpenAI bill so high?” — run an LLM-powered app or agent long enough and this moment always arrives. This page lays out a practical approach to actually reducing LLM costs, and where Argosvix fits in.
Before cutting costs: most of the time, you can't see the breakdown
An invoice only tells you per-provider totals. What you actually need for reduction decisions:
- Which feature and which model is spending how much
- Whether each call earns its cost (would a cheaper model do?)
- Whether anomalies are mixed in (runaway loops, retry storms, needlessly long prompts)
Switching to a cheaper model without seeing the breakdown can cost you more in quality regressions. The order is: visibility, then anomaly elimination, then model/prompt optimization.
Four commonly missed cost accounting gaps
Typical reasons your bill and your intuition diverge — you find these the moment you build measurement yourself.
1. Streaming under-counting
OpenAI returns no token counts on streaming unless you set stream_options. Chat UIs are almost all streaming, so naive homegrown measurement shows most calls as “free.”
2. Interrupted calls
When a user closes the page, you are still billed for tokens up to the disconnect. Counting only completed calls under-reports.
3. Cache misreading
Ignore prompt-cache discounts and you over-report; forget cache-write costs and you under-report.
4. Multi-step agent calls
One task can fire dozens of API calls behind the scenes. Each call is cheap, but the per-task cost is high — and invisible.
The Argosvix SDK handles all four on the measurement side (setup is one line in your existing code).
Don't stop at visibility — watching and budgets
Even with a dashboard, if you don't have time to check it daily, cost anomalies wait for the invoice. Argosvix delegates the watching to an AI:
- An automatic scan every 15 minutes detects cost spikes against your past trends and delivers findings to an inbox
- Set a budget gate and calls stop client-side when the cap is reached — insurance against a runaway agent burning money overnight
- Ask from Claude / Cursor — “which model costs the most this month?”, “why did cost rise since yesterday?” — and get answers from your real data (MCP)
Pricing at a glance
- Free: $0 — records up to 50,000 calls/month, 30-day retention. For many projects, cost visibility alone fits here.
- Pro: $13/month flat — 1,000,000 calls/month, 90-day retention, no metering. Automatic cost-anomaly detection, optimization suggestions, and end-of-month forecasts live here.
If the observability tool itself is usage-billed, you can't predict the cost of watching your costs — so ours is flat.
See where you stand in 5 minutes
Run npx @argosvix/cli init and everything from key issuance to SDK setup and a test event is automated. After a few days you'll have the per-feature breakdown. That's where the real reduction conversation starts.