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 <100 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 <100 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. Portkey

Platform Overview

Portkey is a comprehensive enterprise AI gateway providing unified access to 1600+ LLMs across multiple providers. Built with observability at its core, Portkey offers advanced tools for control, visibility, and security in AI applications. The platform serves both cloud-hosted and self-hosted deployment models.

Key Features

  • Extensive Model Support: Access to 1600+ AI models including vision, audio, and image generation providers
  • Advanced Guardrails: Enforce content policies and output controls with real-time safety filters
  • Virtual Key Management: Secure API key handling with centralized rotation and access control
  • Configurable Routing: Automatic retries, fallbacks with exponential backoff strategies
  • Prompt Management: Built-in tools for prompt versioning and testing
  • Enterprise Features: Compliance controls, audit trails, SSO support, and HIPAA/GDPR compliance
  • Observability: Detailed analytics, custom metadata, and alerting with export capabilities

Best For

  • Enterprise teams requiring extensive model coverage across multiple modalities
  • Organizations needing advanced compliance features (HIPAA, GDPR, SOC 2)
  • Teams prioritizing comprehensive observability and prompt management
  • Companies seeking managed gateway services with enterprise SLAs

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.

Key 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

Best For

  • Developers seeking maximum provider flexibility with open-source infrastructure
  • Teams requiring quick integration with extensive LLM provider catalog
  • Organizations building custom LLMOps pipelines with self-hosting requirements
  • Startups prioritizing cost-effective solutions without vendor lock-in

4. Helicone

Platform Overview

Helicone is an open-source AI gateway built in Rust for exceptional performance, delivering <1ms P99 latency overhead under heavy load. The platform emphasizes observability, intelligent caching, and developer-friendly integration with minimal setup requirements.

Key Features

Best For

  • Developers prioritizing performance and low-latency requirements
  • Teams wanting strong observability without complex instrumentation
  • Organizations requiring self-hosted solutions with data sovereignty
  • Startups seeking lightweight integration with generous free tier (10k requests/month)

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

Best For

  • Enterprises with existing Kong API infrastructure seeking unified AI/API management
  • Organizations requiring advanced governance and compliance features
  • Teams needing automated RAG pipelines and hallucination mitigation
  • Companies prioritizing enterprise-grade security and MCP support

Gateway Comparison Table

Feature Bifrost Portkey LiteLLM Helicone Kong AI
Performance <100 µs overhead @ 5k RPS Standard Higher latency @ scale <1ms P99 overhead Standard
Speed Comparison 50x faster than LiteLLM Standard Baseline 25-100x faster than LiteLLM Standard
Primary Language Go TypeScript/Node.js Python Rust Lua/Go
Open Source ✅ Apache 2.0 ✅ (Gateway only) ✅ ✅ ✅ (Enterprise features paid)
Provider Support 15+ providers 1600+ models 100+ providers 100+ models Major providers + custom
Deployment Options Self-hosted, VPC, Docker, NPX Cloud, self-hosted Self-hosted, proxy server Cloud, self-hosted Cloud, on-premises, hybrid
Unified API OpenAI-compatible OpenAI-compatible OpenAI-compatible OpenAI-compatible Universal LLM API
Semantic Caching ✅ ✅ ❌ ✅ ✅
Automatic Failover ✅ Adaptive ✅ ✅ ✅ Circuit breaking ✅
Load Balancing ✅ Weighted + adaptive ✅ ✅ ✅ Regional ✅
MCP Support ✅ Full governance ✅ ✅ Team-level control ❌ ✅ Enterprise
Guardrails ✅ Custom plugins ✅ Advanced ✅ Built-in + integrations ❌ ✅ Comprehensive
Observability Prometheus, distributed tracing Detailed analytics Integration-based Native + OpenTelemetry Enterprise dashboards
Budget Management ✅ Hierarchical ✅ Virtual keys ✅ Per project/team ❌ ✅ Enterprise
Rate Limiting ✅ Fine-grained ✅ ✅ ✅ Multi-level ✅
SSO Integration ✅ Google, GitHub ✅ Enterprise ❌ (Enterprise only) ❌ ✅
Vault Support ✅ HashiCorp ❌ ❌ ❌ ❌
Prompt Management Via Maxim platform ✅ Built-in ❌ ❌ ✅
RAG Pipeline Via Maxim platform ❌ ❌ ❌ ✅ Automated
Multimodal ✅ ✅ ✅ ✅ ✅ Advanced
Setup Time <1 minute (NPX/Docker) <5 minutes 15-30 minutes <5 minutes Varies by deployment
Free Tier ✅ Open source ✅ Limited ✅ Open source ✅ 10k requests/month ✅ Limited
Enterprise Features ✅ ✅ Paid tier only Limited ✅ Comprehensive
Platform Integration Maxim AI (simulation, evals, observability) Standalone Standalone Standalone Kong Konnect
Best For Production-scale, performance-critical, full-stack AI quality Enterprise governance, extensive model coverage Developer flexibility, open-source Performance, observability, self-hosting Existing Kong users, enterprise compliance

Choosing the Right LLM Gateway

Decision Framework

Choose Bifrost if:

  • Performance is critical and you need <100 µs overhead at scale
  • You require open-source infrastructure with complete control
  • You're building production-grade AI systems requiring maximum reliability
  • You want integrated simulation, evaluation, and observability through Maxim AI
  • Zero-configuration deployment and drop-in SDK replacement are priorities
  • Enterprise features like SSO, Vault, and hierarchical budgets are essential

Choose Portkey if:

  • You need access to 1600+ models across multiple modalities
  • Advanced compliance requirements (HIPAA, GDPR, SOC 2) are mandatory
  • Comprehensive prompt management and versioning are priorities
  • You prefer managed services with enterprise SLAs
  • Advanced guardrails and content policies are essential

Choose LiteLLM if:

  • Maximum provider flexibility is the primary requirement
  • You're building custom LLMOps pipelines requiring deep customization
  • Open-source infrastructure with self-hosting is non-negotiable
  • Budget constraints favor cost-effective solutions
  • You need extensive provider catalog (100+) with unified interface

Choose Helicone if:

  • Low-latency performance with minimal overhead is critical
  • Strong observability without complex setup is required
  • Self-hosting with complete data sovereignty is mandatory
  • You want generous free tier for development and small-scale production
  • Rust-based performance characteristics align with requirements

Choose Kong AI Gateway if:

  • Your organization already uses Kong for API management
  • Automated RAG pipelines for hallucination reduction are needed
  • Enterprise-grade MCP governance and security are required
  • Unified AI and API traffic management is preferred
  • Comprehensive prompt engineering and guardrails are essential

Key Considerations

1. Performance Requirements

For high-throughput, latency-sensitive applications, Bifrost and Helicone deliver superior performance through Go and Rust architectures respectively. Standard applications may find adequate performance with other options.

2. Deployment Model

  • Self-hosted/VPC: Bifrost, LiteLLM, Helicone offer robust self-hosting
  • Managed services: Portkey, Kong provide enterprise-managed options
  • Hybrid: Most platforms support both deployment models

3. Integration Complexity

  • Fastest setup: Bifrost (<1 minute with NPX), Helicone (<5 minutes)
  • Moderate setup: Portkey, Kong (<5-10 minutes)
  • Technical setup: LiteLLM (15-30 minutes with configuration)

4. Cost Structure

  • Open-source/Free: Bifrost, LiteLLM (completely open)
  • Free tiers: Helicone (10k requests/month), Portkey, Kong (limited)
  • Enterprise pricing: All platforms offer enterprise tiers with advanced features

5. Feature Completeness

For comprehensive AI quality management beyond gateway capabilities, Bifrost's integration with Maxim AI's platform provides unique advantages through unified simulation, evaluation, and observability.

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 <100 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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