The hidden cost of vendor lock-in with a single AI provider

Picking one AI provider feels efficient. One SDK, one bill, one mental model. But the convenience hides a set of costs that only show up later — usually at the worst possible moment, like during an outage or a price change you didn't approve. This piece breaks down where those costs actually live and what you can do about them without rewriting your stack.

The cost you notice: downtime

When your product depends on a single API, that vendor's bad day becomes your bad day. And 2024–2025 had several.

According to OpenAI's own status page, a January 23, 2025 incident took chatgpt.com and "a small number of APIs" to elevated error rates for roughly three and a half hours, traced to a Cosmos DB failure and crash-looping web pods. Earlier, on December 11, 2024, OpenAI reported a major degradation across services after a new telemetry deployment overwhelmed its Kubernetes control plane. A separate December 26, 2024 disruption, attributed to an upstream provider, drew over 50,000 reports on Downdetector per coverage of the event.

None of this means OpenAI is uniquely fragile — every provider has incidents. The point is structural: if your only code path runs through one vendor, your uptime is capped by theirs. There is no failover, only a status page to refresh.

The cost you don't notice: optionality

The quieter cost is everything you can't do because switching is expensive.

• Pricing has no exit. LLM prices move with compute costs and competition. If your single provider raises rates or deprecates the model you tuned your prompts around, your only options are pay more or undertake a migration.
• You can't shop per task. A cheap, fast model is fine for classification; a frontier model earns its keep on hard reasoning. Locked to one vendor, you overpay on easy work or underperform on hard work.
• New models age you out. New foundation models ship almost monthly. A single-vendor stack means you watch better or cheaper options launch elsewhere and can't reach them without integration work.

Industry analysts have been blunt about how common this trap is, and Gartner has projected that AI gateway adoption for multi-model applications will grow sharply through 2028 — a signal that "one provider forever" is being treated as an architectural risk, not a default.

Why lock-in is sticky

Lock-in isn't just the API call. It's the surrounding gravity: provider-specific SDKs, auth, response formats, and the prompt tuning baked into one model's quirks. Rip-and-replace migrations are why teams stall. The fix isn't picking the "right" vendor up front — it's choosing an architecture where the vendor is a variable, not a foundation.

Multi-provider access as the mitigation

The practical hedge is an OpenAI-compatible gateway in front of many models. AnyModel gives you one endpoint (https://anymodel.org/v1) and one API key that reaches GPT, Claude, Gemini, DeepSeek, GLM, Kimi, Qwen, and Grok. Switching providers means changing the model id in your request — nothing else in your code moves.

curl https://anymodel.org/v1/chat/completions \
  -H "Authorization: Bearer $YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"claude-sonnet","messages":[{"role":"user","content":"Hello"}]}'

Want a different provider for that call? Change "claude-sonnet" to "gpt-5" or "gemini-2.5-pro". Same key, same endpoint, same SDK. That turns "we're migrating providers" into a one-line change, and it lets you route per task or fail over when one upstream has an incident. You can compare models side by side before committing traffic to any of them.

For supported CLIs, setup is a single line:

bash <(curl -fsSL "https://anymodel.org/i?tool=codex") <YOUR_API_KEY>

Use tool=claude for Claude Code. For Cursor, Windsurf, Zed, Cline, Aider, Continue, or the Gemini CLI, point the client's OpenAI-compatible setting at https://anymodel.org/v1 with your key.

What it costs to find out

Avoiding lock-in shouldn't require a procurement cycle. AnyModel is free to start with 1,000,000 tokens on signup (6,000,000 total if you link Telegram), no credit card. After that it's pay-per-token — no subscription, no minimums. Privacy-sensitive work can use Ghost Mode, an opt-in zero-retention setting where we don't store prompts or responses, only a token counter (the model provider still receives the prompt, so it isn't absolute privacy — but our side keeps nothing).

The cheapest insurance against a vendor's next bad day is not being tied to a single one. Create a free account and make your provider a variable you control. More breakdowns like this live on the blog.