LLM Prices Fell 80% Last Year. Your Bill Doubled Anyway. Here's Why.
This is part of our guide to controlling your LLM bill.
The LLMflation Trap Explained
Every major provider has cut per-token pricing repeatedly since 2023. GPT-4-class pricing alone dropped roughly 80% peak to trough once mini and flash tiers launched. On paper, that should make AI features cheaper to run every single quarter.
In practice, cheaper tokens change product behavior. A feature that was too expensive to ship at $6 per 1,000 requests becomes trivial to ship at $0.20. Teams add streaming, add retries, add multi-step agent chains, add a second model call to "double check" the first one. Usage volume grows 3-5x faster than price falls, so total monthly spend keeps climbing even while the per-token line falls.
Interactive: LLMflation Simulator
Price vs. bill, 2023-2027
The 30-40% Waste Number
Falling prices mask a separate problem: waste. Across production LLM deployments, 30-40% of spend is typically recoverable without any feature changes. The waste breaks into three repeatable categories — duplicate requests that never hit a cache, the wrong model tier selected by default for a task, and bloated context windows carrying tokens nobody reads. None of these require a price cut from the provider. They require visibility into what you're actually sending.
Interactive: Waste Audit Estimator
Estimate your recoverable waste
The Governance Solution
Falling prices reward teams that watch usage, not teams that wait for the next price cut. Governance means feature-level attribution, model-tier rules, and alerts before a usage spike becomes a quarter-end surprise. Without that visibility, every price cut just subsidizes more unmonitored growth.
// Track every request with feature + model so growth is visible per surface
fetch('https://llm-track.com/api/ingest', {
method: 'POST',
headers: { 'x-api-key': process.env.LLMTRACK_KEY },
body: JSON.stringify({
provider: 'openai',
model: response.model,
feature_name: 'agent-chain-step-2',
total_tokens: response.usage.total_tokens,
latency_ms: Date.now() - startedAt,
status: 'success'
})
}).catch(() => {})The Forecast Advantage
Teams that track spend daily can see the usage-growth curve weeks before it crosses budget. That advance warning is the real defense against LLMflation — not waiting for the next round of price cuts, but knowing your own growth rate well enough to act before it outpaces them.
Track feature-level usage growth before the next price cut convinces you everything is fine.
FAQ
Most likely yes, in line with the trend since 2023. That does not guarantee your bill falls — usage growth is the variable that actually decides your invoice.
Most production deployments without caching or model-tier rules can recover 30-40% of spend without changing any feature behavior.
Daily spend growth rate by feature. A feature growing faster than 30%/month will outpace any price cut within a year.
See your real usage growth — not just the price trend
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