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◈ Agents & Manager/2026-04-23Advanced

Antigravity × Multi-Provider LLM Failover — A Production Guide for Gemini, Claude, and Local Gemma

When Gemini returns 503, does your agent stop responding? This guide walks through a production-ready router, circuit breaker, and graded fallback design, with code you can paste in today.

antigravity461multi-providerfailoverresilience9gemini20claude3gemma

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Last month, the AI agent I run returned 503 errors from the Gemini API between 9 and 11 AM. Google Cloud's status page showed no incident; it took a search on X (Twitter) to confirm that a regional rollout was flaking intermittently.

The service didn't go down outright. But responses were peppered with errors, and more than a dozen users reached out asking if something was broken. A single morning erased trust I had spent six months building.

This article shares the full implementation I rebuilt after that morning — a "LLM stack that doesn't stop." Inside an Antigravity agent environment, we'll combine Gemini, Claude, and a local Gemma 4 model, with a router, circuit breaker, and graded fallback that hides partial outages from users. Every code sample is runnable as-is.

The reason I rebuilt this in earnest is that, as an indie developer, I run a mobile app business and several websites in parallel. Ad delivery in the apps and the routine jobs behind the sites both lean on the same kind of external APIs underneath. When any one of them stalls, revenue and user trust erode at the same speed — and after feeling that a few times, I stopped treating resilience as an afterthought and started baking "it must not stop" into the first draft of every design. From here on, I'll turn that habit into concrete code and numbers.

When Multi-Provider Becomes Non-Negotiable

When people hear "LLM outages," they often picture something rare — the once-a-month global incident that shows up on status pages. Those do exist, but they're not what causes most user-visible failures.

Partial outages happen nearly every week in real operations:

  • 503 errors spike in a single region while global metrics stay green
  • A rate-limit cap takes 3–5 minutes to clear even after traffic normalizes
  • A model becomes briefly pathological — p99 latency goes over 30 seconds
  • INTERNAL errors appear for specific token lengths only

A single-provider setup surfaces all of these directly to the user. The real value of multi-provider isn't avoiding total failure; it's absorbing partial failures so the user never notices. That framing matters because it changes what you optimize for — you're not building a second line of defense, you're building a shock absorber that fires dozens of times per day, invisibly.

Three Axes That Drive the Routing Decision

Before writing code, I want to lay out the decision framework I actually run in production. Three axes, evaluated in this order:

The capability axis comes first. Does this provider meet the minimum requirements of this request? If you need a 1M-token context, Gemini is your only choice. If you need complex tool-calling with nested JSON schemas, Claude wins. If you're offline, Gemma. Capability is a hard filter — a provider either qualifies or it doesn't.

The latency axis comes second. Among providers that qualify, prefer the one with lower p95 latency. One subtle but important rule: use a rolling median over the last 5 minutes, not the instantaneous response time. Spike-based routing causes oscillation, and your router ends up switching providers every other request.

The cost axis comes last. When capability and latency are comparable, pick the cheaper one. It has to be last because if you lead with cost, fallback breaks down — imagine a cheap provider that fails; you flip to the premium provider, but then the router keeps trying to return to cheap-and-broken. The order "capability → latency → cost" prevents this cycle.

Invert the order even slightly, and in six months you'll be staring at graphs trying to explain why your error rate hasn't improved. I've seen this firsthand.

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WHAT YOU'LL LEARN
✦Full router code that switches between Gemini, Claude, and local Gemma by capability, then latency, then cost
✦Circuit breaker and graded fallback implemented with production-tested configuration values
✦Three months of real metrics — fallback rate, p95, cost split — plus a reusable incident retro template
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