Best LLM Gateways in 2025: Features, Benchmarks, and Builder's Guide

Описание: As large language models (LLMs) move into production at scale, AI builders are realizing that raw model performance isn’t enough — the real challenge lies in managing traffic, latency, and multi-provider complexity. That’s where LLM Gateways come in.

In this video, we explore the best LLM gateways of 2025, comparing their features, performance benchmarks, and trade-offs for developers building scalable AI systems.

You’ll learn:

What an LLM Gateway is and why it’s essential for multi-model routing, caching, load balancing, and failover.

Key performance benchmarks: throughput, latency, mean overhead, and scalability under load.

The difference between self-hosted and managed gateways; and when to use each.

How open-source tools like Bifrost (https://www.getmaxim.ai/bifrost) are pushing boundaries with ultra-low latency (up to 50x faster than alternatives like LiteLLM), full provider support, built-in Prometheus monitoring, and adaptive load balancing.

What to consider before integrating a gateway into your stack: API unification, performance metrics, observability hooks, and governance.

Additional reading:
AI Gateway Overview (AIMultiple): https://research.aimultiple.com/ai-ga...
OpenAI API Docs: https://platform.openai.com/docs
Anthropic API: https://docs.anthropic.com/
Hugging Face Inference API: https://huggingface.co/inference

Whether you’re building agentic systems, integrating multi-provider pipelines, or scaling production workloads, understanding the LLM gateway layer; and tools like Bifrost; is crucial for performance and reliability.
#LLMGateway #Bifrost #LLMOps #AIInfrastructure #AItools #MaximAI #GenerativeAI #OpenSourceAI #ModelRouting #AIengineering #ArtificialIntelligence

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