Compare leading AI gateway platforms for multi-provider routing, cost management, access control, governance, observability, and enterprise-grade reliability.
[ UNDERSTANDING LLM GATEWAYS ]
An LLM gateway is a centralized platform that sits between applications and AI model providers like OpenAI, Anthropic, AWS Bedrock, and Google Vertex AI.
It standardizes access through a single unified API while layering on production-grade routing, failover, cost management, observability, guardrails, governance, and MCP support.
[ THE CHALLENGE ]
Moving generative AI from prototype to production exposes gaps that traditional infrastructure cannot fill.
Different APIs, credentials, and usage patterns across providers make scaling brittle.
Without centralized logs and metrics, teams cannot trace errors or attribute token spend.
Provider outages and quota limits disrupt workflows. Individual providers rarely exceed 99.7% uptime.
API keys shared across environments create compliance vulnerabilities difficult to audit.
[ CORE FUNCTIONS ]
Modern LLM gateways provide these essential capabilities for production AI deployments.
Route requests across LLM providers using governance rules and intelligent load distribution.
Connect to multiple LLM providers with a single OpenAI-compatible API interface.
Monitor requests in real-time. Track token usage and enforce limits at multiple levels.
Health monitoring, circuit breakers, automatic retries, and failover to alternative providers.
Virtual keys to manage permissions, rate limiting, budgets, and team-based access.
Semantic caching, budget limits, and intelligent routing to reduce costs and latency.
Policy controls on requests and responses with real-time content moderation.
Compatible with OpenAI, Anthropic SDKs, LangChain, and popular frameworks.
[ PLATFORM COMPARISON ]
A quick comparison of leading platforms across deployment, pricing, and key differentiators.
The Fastest Enterprise LLM Gateway
Built with Go for sub-microsecond latency. Native MCP support, adaptive load balancing, and integrated with Maxim AI evaluation platform.
Open Source Multi-Provider Proxy
Python-based open-source gateway supporting multiple providers. Highly customizable with extensive integration options.
Unified AI traffic management
Unified AI traffic management for Cloudflare users. Multiple models supported.
Performance-First Observability
Gateway optimized for performance and observability with zero markup pricing.
API Management Extended
Extends Kong's proven API gateway platform to support LLM routing with plugin-based architecture.
Simplest Multi-Model Access
Simplified access to multiple AI models through a single endpoint. Best for rapid prototyping.
[ DETAILED COMPARISON ]
A direct capability comparison across all evaluated platforms.
| Feature | Bifrost | LiteLLM | Cloudflare AI | Helicone | Kong AI | OpenRouter |
|---|---|---|---|---|---|---|
| Performance & Architecture | ||||||
| Language / Runtime | Go | Python | N/A | Typescript | Lua | Typescript |
| Latency Overhead | <~11µs | ~40ms | 10-50ms | N/A | N/A | 25–40ms |
| Peak Throughput | 5,000 RPS | Not published | Not published | Not published | Not published | High |
| Open Source | Yes | Yes | No | Partial | Partial | No |
| Zero Markup | Yes | Yes | Yes | Yes | Custom | 5% |
| Routing & Reliability | ||||||
| Auto Failover | Yes | Yes | Yes | Yes | Yes | Yes |
| Adaptive Load Balancing | Yes | No | No | Health-aware | Basic | No |
| P2P Clustering | Yes | No | No | No | No | No |
| Semantic Caching | Yes | No | Yes | Yes | No | No |
| MCP Support | Yes | No | No | No | Yes | No |
| Observability & Governance | ||||||
| Built-in Observability | Native | Via integrations | Basic | Native | Basic | No |
| Real-time Alerts | Yes | No | No | No | Via plugins | No |
| Guardrails | Yes | No | No | No | No | No |
| RBAC & Governance | Yes | No | No | No | Yes | No |
| SSO (SAML / OIDC) | Yes | No | No | No | Yes | No |
| Budget Management | Yes | Yes | No | No | No | No |
| Evaluation Integration | Native (Maxim AI) | No | No | No | No | No |
| Enterprise Deployment | ||||||
| VPC Deployment | Yes | Yes | No | Yes | Yes | No |
| Multi-Cloud Support | AWS, GCP, Azure, Cloudflare, Vercel | Self-managed | CF only | Self-managed | Multi-cloud | No |
[ PERFORMANCE ]
The technology stack underneath determines how a gateway handles concurrent requests and sustains low latency under load. Bifrost's Go-based architecture delivers predictable performance without interpreter overhead.
Latency Overhead Comparison (P95)
Based on published benchmarks from each platform's documentation.
[ BIFROST FEATURES ]
Everything you need to run AI in production, from free open source to enterprise-grade features.
01 Model Catalog
Access 8+ providers and 1000+ AI models from multiple providers through a unified interface. Also support custom deployed models!
02 Budgeting
Set spending limits and track costs across teams, projects, and models.
03 Provider Fallback
Automatic failover between providers ensures 99.99% uptime for your applications.
04 MCP Gateway
Centralize all MCP tool connections, governance, security, and auth. Your AI can safely use MCP tools with centralized policy enforcement. Bye bye chaos!
05 Virtual Key Management
Create different virtual keys for different use-cases with independent budgets and access control.
06 Unified Interface
One consistent API for all providers. Switch models without changing code.
07 Drop-in Replacement
Replace your existing SDK with just one line change. Compatible with OpenAI, Anthropic, LiteLLM, Google Genai, Langchain and more.
08 Built-in Observability
Out-of-the-box OpenTelemetry support for observability. Built-in dashboard for quick glances without any complex setup.
09 Community Support
Active Discord community with responsive support and regular updates.
[ ECOSYSTEM ]
Comprehensive integration capabilities across the AI development stack.
Change just one line of code. Works with OpenAI, Anthropic, Vercel AI SDK, LangChain, and more.
