LLM Gateway

List of Top 5 LLM Gateways in 2025

List of Top 5 LLM Gateways in 2025

TL;DR

LLM gateways have become essential infrastructure for production AI applications in 2025. This guide examines the five leading LLM gateway solutions: Bifrost, Portkey, LiteLLM, Helicone, and Kong AI Gateway. Each platform addresses the critical challenge of unified LLM access while offering distinct capabilities:

  • Bifrost: The fastest open-source LLM gateway (50x faster than LiteLLM) with <11 µs overhead, built for production-grade AI systems
  • Portkey: Enterprise AI gateway with 1600+ LLM support, advanced guardrails, and comprehensive governance
  • LiteLLM: Open-source unified API supporting 100+ LLMs with extensive provider compatibility
  • Helicone: Rust-based gateway emphasizing observability, caching, and developer-friendly integration
  • Kong AI Gateway: Enterprise API management extended to AI traffic with advanced governance and MCP support

Organizations deploying AI face a fragmented provider landscape where every provider implements authentication differently, API formats vary significantly, and model performance changes constantly. LLM gateways solve these challenges by providing unified interfaces, intelligent routing, and enterprise-grade reliability features essential for production deployments.

Table of Contents

  1. Introduction: The LLM Gateway Infrastructure Challenge
  2. What is an LLM Gateway?
  3. Why LLM Gateways are Essential in 2025
  4. Top 5 LLM Gateways
  5. Gateway Comparison Table
  6. Choosing the Right LLM Gateway
  7. Further Reading
  8. External Resources

Introduction: The LLM Gateway Infrastructure Challenge

Large language models now power mission-critical workflows across customer support, code assistants, knowledge management, and autonomous agents. As AI adoption accelerates, engineering teams confront significant operational complexity: every provider offers unique APIs, implements different authentication schemes, enforces distinct rate limits, and maintains evolving model catalogs.

According to Gartner's Hype Cycle for Generative AI 2025, AI gateways have emerged as critical infrastructure components, no longer optional but essential for scaling AI responsibly. Organizations face several fundamental challenges:

  • Vendor Lock-in Risk: Hard-coding applications to single APIs makes migration costly and slow
  • Governance Gaps: Without centralized control, cost management, budget enforcement, and rate limiting remain inconsistent
  • Operational Blind Spots: Teams lack unified observability across models and providers
  • Resilience Challenges: Provider outages or rate limits can halt production applications

LLM gateways address these challenges by centralizing access control, standardizing interfaces, and providing the reliability infrastructure necessary for production AI deployments.

What is an LLM Gateway?

An LLM gateway functions as an intelligent routing and control layer between applications and model providers. It serves as the unified entry point for all LLM traffic, handling API format differences, managing failovers during provider outages, optimizing costs through intelligent routing, and providing comprehensive monitoring capabilities.

Core Functions

LLM gateways deliver several essential capabilities:

  • Unified API Interface: Normalize request and response formats across providers through standardized APIs
  • Intelligent Routing: Distribute traffic across models and providers based on cost, performance, or availability
  • Reliability Features: Implement automatic failover, load balancing, and retry logic for production resilience
  • Governance Controls: Enforce authentication, role-based access control (RBAC), budgets, and audit trails
  • Observability: Provide tracing, logs, metrics, and cost analytics for comprehensive visibility

By 2025, expectations from gateways have expanded beyond basic routing to include agent orchestration, Model Context Protocol (MCP) compatibility, and advanced cost governance capabilities that transform gateways from routing layers into long-term platforms.

Why LLM Gateways are Essential in 2025

Multi-Provider Reliability

Model quality, pricing, and latency vary significantly by provider and change over time. Relying on a single vendor increases risk and limits iteration speed. Production AI demands 99.99% uptime, but individual providers rarely exceed 99.7%. LLM gateways maintain service availability during regional outages or rate-limit spikes through automatic failover and intelligent load balancing.

Cost Optimization

LLM costs typically scale based on token usage, making cost control critical for production deployments. Gateways enable cost optimization through:

  • Semantic Caching: Eliminate redundant API calls by caching responses based on semantic similarity
  • Intelligent Routing: Route requests to most cost-effective providers while maintaining quality requirements
  • Budget Enforcement: Set spending caps per team, application, or use case with automated limits
  • Usage Analytics: Track token consumption and costs across providers for informed optimization decisions

Security and Governance

As AI usage expands across organizations, centralized governance becomes essential. Gateways provide:

  • Access Control: Define which teams can access which models under specified conditions
  • Guardrails: Enforce content policies, block inappropriate outputs, and prevent PII leakage
  • Compliance: Maintain audit trails, implement data handling policies, and ensure regulatory compliance
  • Secret Management: Centralize API key storage and rotation without application code changes

Developer Productivity

Organizations standardizing on gateways reduce integration overhead by abstracting provider differences. Developers integrate once with the gateway's unified API rather than managing separate SDKs for each provider, enabling faster model switching and reducing maintenance burden.

Top 5 LLM Gateways

1. Bifrost

Platform Overview

Bifrost is a high-performance, open-source LLM gateway built by Maxim AI, engineered specifically for production-grade AI systems requiring maximum speed and reliability. Written in Go, Bifrost delivers exceptional performance with <11 µs overhead at 5,000 RPS, making it 50x faster than LiteLLM according to sustained benchmarking.

The gateway provides unified access to 15+ providers including OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Cerebras, Cohere, Mistral, Ollama, and Groq through a single OpenAI-compatible API. Bifrost emphasizes zero-configuration deployment, enabling teams to go from installation to production-ready gateway in under a minute.

Key Features

Unmatched Performance

Bifrost's Go-based architecture delivers industry-leading speed:

Unified Multi-Provider Access

Bifrost's unified interface provides seamless access across providers:

  • OpenAI-Compatible API: Single consistent interface following OpenAI request/response format
  • 12+ Provider Support: OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Cohere, Mistral, Ollama, Groq, Cerebras
  • Custom Model Support: Easy integration of custom-deployed models and fine-tuned endpoints
  • Dynamic Provider Resolution: Automatic routing based on model specification (e.g., openai/gpt-4o-mini)

Automatic Failover and Load Balancing

Bifrost's reliability features ensure 99.99% uptime:

  • Weighted Key Selection: Distribute traffic across multiple API keys with configurable weights
  • Adaptive Load Balancing: Intelligent request distribution based on provider health and performance
  • Automatic Provider Failback: Seamless fallover to backup providers during throttling or outages
  • Zero-Downtime Switching: Model and provider changes without service interruption

Enterprise Governance

Comprehensive governance capabilities for production deployments:

  • Virtual Keys: Create separate keys for different use cases with independent budgets and access control
  • Hierarchical Budgets: Set spending limits at team, customer, or application levels
  • Usage Tracking: Detailed cost attribution and consumption analytics across all dimensions
  • Rate Limiting: Fine-grained request throttling per team, key, or endpoint

Model Context Protocol (MCP) Support

Bifrost's MCP integration enables AI models to use external tools:

  • Tool Integration: Connect AI agents to filesystems, web search, databases, and custom APIs
  • Centralized Governance: Unified policy enforcement for all MCP tool connections
  • Security Controls: Granular permissions and authentication for tool access
  • Observable Tool Usage: Complete visibility into agent tool interactions

Advanced Optimization Features

Additional capabilities for production AI systems:

  • Semantic Caching: Intelligent response caching based on semantic similarity reduces costs and latency
  • Multimodal Support: Unified handling of text, images, audio, and streaming
  • Custom Plugins: Extensible middleware architecture for analytics, monitoring, and custom logic
  • Observability: Native Prometheus metrics, distributed tracing, and comprehensive logging

Developer Experience

Bifrost prioritizes ease of integration and deployment:

  • Zero-Config Startup: Start immediately with NPX or Docker, no configuration files required
  • Drop-in Replacement: Replace existing OpenAI/Anthropic SDKs with one line of code change
  • SDK Integrations: Native support for OpenAI, Anthropic, Google GenAI, LangChain, and more
  • Web UI: Visual configuration interface for provider setup, monitoring, and governance
  • Configuration Flexibility: Support for UI-driven, API-based, or file-based configuration

Enterprise Security

Production-grade security features:

  • SSO Integration: Google and GitHub authentication support
  • Vault Support: HashiCorp Vault integration for secure API key management
  • Self-Hosted Deployment: Complete control over data and infrastructure with VPC deployment options
  • Audit Trails: Comprehensive logging of all gateway operations for compliance

Integration with Maxim Platform

Bifrost uniquely integrates with Maxim AI's full-stack platform:

This end-to-end integration enables teams to ship AI agents reliably and 5x faster by unifying pre-release testing with production monitoring.

Best For

Bifrost is ideal for:

  • Performance-Critical Applications: Teams requiring ultra-low latency and high throughput for production AI workloads
  • Open-Source Advocates: Organizations prioritizing transparency, extensibility, and community-driven development
  • Enterprise Deployments: Companies needing self-hosted solutions with complete infrastructure control
  • Production-Scale AI: Teams running high-volume LLM traffic requiring robust governance and observability
  • Full-Stack AI Quality: Organizations seeking integrated simulation, evaluation, and observability alongside gateway capabilities

Bifrost's combination of exceptional performance, enterprise features, and integration with Maxim's comprehensive AI quality platform makes it the optimal choice for teams building production-grade AI systems.

Get started with Bifrost in under a minute with NPX or Docker, or explore Maxim AI's complete platform for end-to-end AI quality management.

2. Cloudflare

Platform Overview

Cloudflare AI Gateway provides a unified interface to connect with major AI providers including Anthropic, Google, Groq, OpenAI, and xAI, offering access to over 350 models across 6 different providers

Features:

  • Multi-provider support: Works with Workers AI, OpenAI, Azure OpenAI, HuggingFace, Replicate, Anthropic, and more
  • Performance optimization: Advanced caching mechanisms to reduce redundant model calls and lower operational costs
  • Rate limiting and controls: Manage application scaling by limiting the number of requests
  • Request retries and model fallback: Automatic failover to maintain reliability
  • Real-time analytics: View metrics including number of requests, tokens, and costs to run your application with insights on requests and errors
  • Comprehensive logging: Stores up to 100 million logs in total (10 million logs per gateway, across 10 gateways) with logs available within 15 seconds
  • Dynamic routing: Intelligent routing between different models and providers

3. LiteLLM

Platform Overview

LiteLLM is an open-source gateway providing unified access to 100+ LLMs through OpenAI-compatible APIs. Available as both Python SDK and proxy server, LiteLLM emphasizes flexibility and extensive provider compatibility for development and production environments.

Features

  • Multi-Provider Support: OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Cohere, and 100+ additional providers
  • Unified Output Format: Standardizes responses to OpenAI-style format across all providers
  • Retry and Fallback Logic: Ensures reliability across multiple model deployments
  • Cost Tracking: Budget management and spending monitoring per project or team
  • Observability Integration: Integrates with Langfuse, MLflow, Helicone, and other monitoring platforms
  • Built-in Guardrails: Blocking keywords, pattern detection, and custom regex patterns
  • MCP Gateway Support: Control tool access by team and key with granular permissions

4. Vercel

Platform Overview

Vercel AI Gateway, now generally available, provides a single endpoint to access hundreds of AI models across providers with production-grade reliability. The platform emphasizes developer experience, with deep integration into Vercel's hosting ecosystem and framework support.

Key Features:

  • Multi-provider support: Access to hundreds of models from OpenAI, xAI, Anthropic, Google, and more through a unified API
  • Low-latency routing: Consistent request routing with latency under 20 milliseconds designed to keep inference times stable regardless of provider
  • Automatic failover: If a model provider experiences downtime, the gateway automatically redirects requests to an available alternative
  • OpenAI API compatibility: Compatible with OpenAI API format, allowing easy migration of existing applications
  • Observability: Per-model usage, latency, and error metrics with detailed analytics

5. Kong AI Gateway

Platform Overview

Kong AI Gateway extends Kong's mature API management platform to AI traffic, providing enterprise-grade governance, security, and observability for LLM applications. The platform integrates AI capabilities into existing Kong infrastructure for unified API and AI management.

Key Features

Gateway Comparison Table

Feature Bifrost Cloudflare LiteLLM Vercel Kong AI
Performance <11 µs overhead @ 5k RPS Varies Higher latency @ scale <20ms Standard
Speed Comparison 50x faster than LiteLLM Standard Baseline Standard Standard
Primary Language Go N/A Python N/A Lua/Go
Deployment Options Self-hosted, VPC, Docker, NPX SaaS Self-hosted, proxy server SaaS Cloud, on-premises, hybrid
Semantic Caching ✅ ✅ ❌ ❌ ✅
Automatic Failover ✅ Adaptive ✅ ✅ ✅ Circuit breaking ✅
Adaptive Load Balancing ✅ Weighted + adaptive ❌ ✅ ❌ ✅
MCP Support ✅ Full governance ❌ ✅ Team-level control ❌ ✅ Enterprise
Guardrails ✅ Custom plugins ❌ ✅ Built-in + integrations ❌ ✅ Comprehensive
Built-in Observability Prometheus, distributed tracing Basic Integration-based Basic Enterprise dashboards
Budget Management ✅ Hierarchical ❌ ✅ Per project/team ❌ ✅ Enterprise
SSO Integration ✅ Google, GitHub ❌ ❌ (Enterprise only) ❌ ✅
Vault Support ✅ HashiCorp ❌ ❌ ❌ ❌
Multimodal ✅ ✅ ✅ ✅ ✅ Advanced
Free Tier ✅ Open source ✅ Platform plans ✅ Open source ✅ Zero markup ✅ Limited
Platform Integration Maxim AI (simulation, evals, observability) Standalone Standalone Standalone Kong Konnect

Further Reading

Bifrost Resources

Maxim AI Platform

External Resources

Industry Analysis

Get Started with Bifrost

Building production-grade AI applications requires infrastructure that delivers exceptional performance, reliability, and enterprise features. Bifrost provides the fastest open-source LLM gateway with <11 µs overhead, complete with automatic failover, intelligent load balancing, and comprehensive governance.

Ready to deploy a production-ready LLM gateway?

For organizations seeking comprehensive AI quality management beyond gateway capabilities, Maxim AI delivers end-to-end simulation, unified evaluations, and production observability in a single platform.

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