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Table of Contents * TL;DR * Quick Comparison Table * Overview > What is an LLM Gateway * Detailed Feature Matrix * Gateway Profiles * Gateways > Bifrost by Maxim AI * Gateways > Cloudflare AI Gateway * Gateways > LiteLLM * Gateways > Vercel AI Gateway * Gateways > Kong AI Gateway * Selection Guide > How to Choose

TL;DR Token tracking is essential for controlling costs, optimizing performance, and maintaining transparency in AI applications. Without visibility into token consumption, organizations face unpredictable bills, inefficient resource allocation, and difficulty attributing costs across teams. This guide covers the fundamentals of token tracking, common challenges in multi-provider environments, and practical

TL;DR LLM routing is the process of intelligently directing queries to the most appropriate model based on factors like complexity, cost, latency, and domain expertise. This guide covers the top 5 routing techniques that production teams use to optimize their AI infrastructure: 1. Semantic Routing - Uses embedding-based similarity

Access OpenAI, Anthropic, Google, AWS Bedrock, and more through a single, familiar interface The OpenAI SDK has become the de facto standard for LLM application development. Developers have invested countless hours building applications around its API format, creating a significant migration barrier when exploring alternative providers. Bifrost eliminates this barrier