We Eliminated 100% of Repeat AI Query Costs. Here's the Data.

Businesses running AI at scale pay full LLM cost on every query. Repeat questions — same API patterns, same framework questions, same validation checks — cost exactly as much the hundredth time as the first.

There’s no reason for that.

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How It Works

The logic is simple:

Query comes in → cache checked first → if matched, returns instantly at $0.00 → LLM never called.

The first time a query runs, the LLM handles it and the result is cached. Every subsequent identical or near-identical query is served from cache. No tokens burned. No cost. The answer already exists — the system just returns it.

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The Benchmark

We ran the same validation query three ways:

• Run 3A (cold cache): First time this query has been seen. Cache empty. LLM called.
• Run 3B (warm cache): Same query, second time. Cache has the result. LLM not called.
• Run 3C (10 queries): Same query, ten times total. All served from cache after the first.

	First Query	Repeat Query	10 Queries
Cost	$0.005227	$0.00	$0.00
Tokens used	8,745	0	0
Source	LLM	Cache	Cache
Savings	—	100%	100%

First query warms the cache. Every query after: free.

Run 3A cost $0.005227 and consumed 8,745 tokens — a normal LLM call. Run 3B: $0.00, zero tokens. Run 3C: ten queries, $0.00 total, 100% cache hit rate. The LLM was called exactly once across all ten runs.

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What This Means at Scale

In a development team asking dozens of coding questions daily, cache hit rate compounds over time.

Common patterns — framework syntax, API methods, validation rules — get cached once and served free forever. The second developer asking about SQLAlchemy 2.0 syntax gets the same verified answer as the first, instantly, at zero cost. The tenth developer asking the same question costs nothing.

At scale, you’re paying full LLM price for a shrinking fraction of your traffic. The rest is cached. As usage grows, cost per query drops — not because you’re cutting corners, but because the system gets smarter about what it already knows.

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The Honest Part

Net-new queries still cost tokens. The cache doesn’t replace the LLM for novel work — it eliminates cost for repeat and near-repeat queries.

In most production systems, those repeat queries make up the majority of traffic. The same frameworks, the same validation patterns, the same API conventions get asked about constantly. Cache those once, and the economics shift significantly.

Novel questions get the full LLM treatment. Known answers get served instantly. That’s the right division of labor.

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Benchmark conducted April 15, 2026. Model: claude-opus-4-6 via OpenRouter. All costs estimated based on published token pricing. Results reflect a controlled test environment and may vary in production.