Vercel's AI Gateway now supports fallback models for when models fail or are unavailable. In addition to safeguarding against provider-level failures, model fallbacks can help with errors and capability mismatches between models (e.g., multimodal, tool-calling, etc.). Fallback models will be tried in the specified order until a request succeeds or no options remain. Any error, such as context limits, unsupported inputs, or provider outages, can trigger a fallback. Requests are billed based on the model that completes successfully. This example shows an instance where the primary model does not support multimodal capabilities, falling back to models that do.…