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LLM caching and model routing cut token costs by replaying repeated responses and sending simple prompts to cheaper models. This guide compares Bifrost, LiteLLM, Cloudflare AI Gateway, Kong AI Gateway, and OpenRouter on caching depth, routing, budgets, and deployment.

TL;DR: As enterprise LLM spending surges past $8.4 billion in 2025, teams building production AI applications need LLM gateways that scale without becoming bottlenecks. While LiteLLM has been a popular choice for multi-provider routing, production teams increasingly face performance degradation, memory leaks, and latency overhead issues at

TL;DR Enterprise AI teams need LLM gateways that go beyond basic proxy functionality. Bifrost, built in Go by Maxim AI, delivers 50x faster performance than LiteLLM with just 11 µs overhead at 5,000 RPS. While LiteLLM works well for prototyping with its 100+ provider support, it struggles under

TL;DR: Claude Code is a powerful terminal-based AI coding agent, but it locks you into a single provider by default. Bifrost, an open-source AI gateway, lets you route Claude Code traffic through 23+ providers, switch models mid-session, set up automatic failovers, and apply expression-based routing

TL;DR Claude Code is locked to Anthropic's models by default. Enterprise AI gateways solve this by sitting between Claude Code and any LLM provider, translating API formats transparently so you can route requests to OpenAI, Google Gemini, Mistral, AWS Bedrock, or any other provider without modifying the

The best LLM gateway for fallback design retries failed requests, rotates API keys, and fails over across providers without code changes. This guide shows how Bifrost chains retries, fallback lists, routing rules, and adaptive load balancing, plus criteria for choosing a gateway.