⚠️ Pending Update · 2026-08-29 Verification · Content may be outdated, please refer to official docs Updated: 2026-08-29 · Status: Pending Verification
Background
"Save money" is a vague goal; the gateway needs to decompose it into executable routing rules. The core idea: free providers are the first choice, paid providers are the fallback, and the cache is the amplifier. Each layer has explicit budgets and triggers; only when composed do they squeeze cost to the minimum.
Routing Rule Set
Execute in priority order, top to bottom; stop on the first hit:
- L0 cache hit: exact or semantic cache returns directly at zero cost. Typically catches 20-40% of traffic.
- L1 free-tier first: among providers whose daily free quota remaining crosses a threshold, sort by latency + remaining quota.
- L2 free degradation: if the first choice fails or quota runs out, switch to the next free provider.
- L3 paid fallback: when no free provider is available, use a paid one, but cap the daily total.
- L4 model downgrade: as the paid budget approaches exhaustion, downgrade the request from
gpt-4otogpt-4o-miniorllama-3.1-8b. - L5 reject: when every budget is exhausted, return a friendly notice instead of a bare 503.
Cost Dashboard
- Daily cost curve: watch the paid-tier ratio; target <10%.
- Cache hit rate: target 25%+; below that, redesign the key.
- Downgrade trigger count: frequent triggers mean the free pool is too small — expand it.
Code Example
class FreeFirstRouter:
def __init__(self, cache, providers, daily_budget_cents=100):
self.cache = cache
self.providers = providers # sorted by free quota remaining
self.paid_used_cents = 0
self.daily_budget = daily_budget_cents
async def route(self, req):
# L0 cache
if cached := self.cache.get(req):
return cached, "L0-cache"
# L1/L2 free-first
for p in self.providers:
if p.free_remaining > 0:
try:
return await p.call(req), f"L1-{p.name}"
except (RateLimit, InternalError):
continue
# L3 paid fallback within budget
if self.paid_used_cents < self.daily_budget:
resp = await paid_provider.call(req)
self.paid_used_cents += resp.cost_cents
return resp, "L3-paid"
# L4 degrade
req["model"] = "llama-3.1-8b"
return await self.providers[0].call(req), "L4-degraded"
Provider Pool Capacity Planning
The free-first strategy's success depends on the provider pool size. Too small (1-2 providers) and any rate limit cascades to paid — savings vanish; too large (10 providers) and operational cost explodes, every provider needs monitoring. Recommended: 3-5 free providers + 1-2 paid fallbacks. Each provider's quota should cover 30% of daily peak, so any one going down leaves the other 2-3 with enough headroom. Weekly review of "which provider is always down, which is always over quota" tunes pool membership dynamically.
Best Practices
- Budget guardrails: a soft cap (downgrade) + a hard cap (reject); soft sits below hard.
- Diversify the free pool: register at least three free providers so a single rate limit does not cascade.
- Cache warming: for known high-frequency questions, batch-generate the cache in a nightly job.
- Weekly review: audit downgrade-chain hit rates weekly and tune provider ordering and budget allocation.
- Cross-region design: pick free providers across multiple regions so a regional outage still leaves backups.
Make "free first" into code, not an OKR slogan.
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