The LLM gateway market has matured rapidly. Teams choosing infrastructure for production AI applications now have several options, each with distinct tradeoffs in performance, features, and deployment models.
Bifrost, an open-source LLM gateway from Maxim AI, enters this space with a performance-first approach. Written in Go, it delivers 11 microseconds of overhead at 5,000 requests per second while maintaining enterprise governance features.
maximhq
/
bifrost
Fastest LLM gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.
Bifrost
The fastest way to build AI applications that never go down
Bifrost is a high-performance AI gateway that unifies access to 15+ providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, and more) through a single OpenAI-compatible API. Deploy in seconds with zero configuration and get automatic failover, load balancing, semantic caching, and enterprise-grade features.
Quick Start
Go from zero to production-ready AI gateway in under a minute.
Step 1: Start Bifrost Gateway
# Install and run locally
npx -y @maximhq/bifrost
# Or use Docker
docker run -p 8080:8080 maximhq/bifrost
Step 2: Configure via Web UI
# Open the built-in web interface
open http://localhost:8080
Step 3: Make your first API call
curl -X POST http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-4o-mini",
"messages": [{"role": "user", "content": "Hello, Bifrost!"}]
}'
That's it! Your AI gateway is running with a web interface for visual configuration, real-time monitoring…
This analysis examines how Bifrost compares to established alternatives and where it fits in the gateway ecosystem.
The Performance Benchmark
Performance claims require data. Bifrost provides comprehensive benchmarks on identical hardware (t3.medium instances) comparing against LiteLLM, the most popular open-source alternative.
At 500 RPS sustained load:
| Metric | Bifrost | LiteLLM | Improvement |
|---|---|---|---|
| p99 Latency | 1.68s | 90.72s | 54x faster |
| Throughput | 424 req/sec | 44.84 req/sec | 9.4x higher |
| Memory Usage | 120MB | 372MB | 3x lighter |
| Mean Overhead | 11µs | 500µs | 45x lower |
At 5,000 RPS, Bifrost maintains 11µs overhead with 100% success rate. LiteLLM cannot sustain this request rate.
These aren't theoretical microbenchmarks. Full request/response cycles including routing, logging, and observability show consistent performance under sustained load.
Architecture: Why Go Matters
The performance advantage stems from architectural choices. Bifrost is written in Go, a compiled language designed for concurrent systems. LiteLLM uses Python with FastAPI, optimized for developer experience over raw performance.
Go's advantages for gateway workloads:
- Compiled to native code (no interpreter overhead)
- Efficient goroutines (handle thousands of connections)
- Predictable garbage collection (low-latency applications)
- Native concurrency (no Global Interpreter Lock)
Python's advantages lie elsewhere: rapid development, extensive ecosystem, familiar syntax. For gateway infrastructure serving thousands of requests per second, Go's performance characteristics matter.
Feature Comparison: Beyond Speed
Performance alone doesn't define production readiness. Here's how Bifrost compares across key features:
Multi-Provider Support
Bifrost: 15+ providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Cohere, Mistral, Ollama, Groq, Cerebras)
LiteLLM: 100+ providers (widest ecosystem support)
Portkey: 1600+ models across major providers
Kong AI Gateway: Major providers plus custom model integration
LiteLLM leads in breadth of provider support. Bifrost focuses on production-critical providers with verified integrations.
Governance and Budget Management
Bifrost: Hierarchical budgets (customer/team/virtual key/provider), real-time enforcement, token-aware rate limiting
Portkey: Advanced governance, prompt management, compliance (SOC 2, HIPAA, GDPR)
Kong AI Gateway: Enterprise-grade governance, MCP support, PII sanitization across 12 languages
LiteLLM: Basic budget tracking, virtual keys, rate limiting
Helicone: Cost tracking focus, usage analytics
Portkey and Kong emphasize enterprise governance. Bifrost provides hierarchical budget controls without requiring managed services.
Model Context Protocol (MCP)
Bifrost: Native MCP support (STDIO, HTTP, SSE), agent mode, code mode, tool filtering
Kong AI Gateway: MCP governance, security, observability
Others: Limited or no MCP support
MCP enables AI agents to use external tools (filesystems, databases, APIs). Bifrost and Kong provide production-ready MCP implementations. Most alternatives don't support MCP yet.
Deployment and Setup
Bifrost: Zero-config deployment (npx -y @maximhq/bifrost), self-hosted, Docker, under 30 seconds
LiteLLM: Self-hosted, requires database setup, 10-30 minutes
Portkey: Managed SaaS, quick setup, also offers self-hosted
Kong AI Gateway: Complex setup (30-60 minutes), container orchestration
Helicone: Cloud or self-hosted, flexible deployment
Bifrost optimizes for deployment speed. Production-ready in seconds with no database requirements.
Caching Strategies
Bifrost: Semantic caching (embedding-based similarity), 40-60% cost reduction
Portkey: Semantic caching with advanced prompt management
Kong AI Gateway: Semantic caching integrated with gateway layer
Helicone: Response caching with analytics
LiteLLM: Basic caching support
Semantic caching (based on meaning, not exact string matching) is becoming standard. Bifrost, Portkey, and Kong all implement this effectively.
Security and Compliance
Bifrost: SSO (Google, GitHub), HashiCorp Vault integration, audit logging (SOC 2, GDPR, HIPAA, ISO 27001)
Portkey: Comprehensive compliance certifications, enterprise security features
Kong AI Gateway: PII detection (20+ categories), advanced security controls
LiteLLM: Basic authentication, limited compliance features
Helicone: Security focus with flexible deployment options
Portkey and Kong lead in enterprise security certifications. Bifrost provides core security features in open-source form.
Pricing and Licensing
Bifrost: Apache 2.0 (fully open-source), enterprise support available
LiteLLM: Open-source, managed service available
Portkey: Freemium SaaS, enterprise pricing
Kong AI Gateway: Open-source core, enterprise licensing for advanced features
Helicone: Free tier (10k requests/month), usage-based pricing
Bifrost's Apache 2.0 license means no enterprise-only performance features. Core functionality is fully open. Kong follows a similar model with paid enterprise features.
Use Case Fit
Choose Bifrost When:
- Performance is critical (real-time chat, voice assistants)
- High throughput required (5K+ RPS)
- Quick deployment needed (zero-config setup)
- Enterprise governance without managed services
- MCP support for AI agents
Choose LiteLLM When:
- Provider breadth matters (100+ providers)
- Python ecosystem preferred
- Moderate traffic (under 500 RPS)
- Rapid prototyping priority
Choose Portkey When:
- Enterprise compliance critical (SOC 2, HIPAA, GDPR)
- Prompt management and versioning needed
- Managing 25+ AI use cases
- Prefer managed service
Choose Kong AI Gateway When:
- Existing Kong infrastructure present
- Advanced PII protection required
- Unified API and AI management needed
- Enterprise support critical
Choose Helicone When:
- Observability and analytics primary focus
- Cost tracking and monitoring priority
- Flexible deployment (cloud or self-hosted)
- Primarily OpenAI-compatible models
Integration Ecosystem
Bifrost integrates with Maxim's AI quality platform for:
- Agent simulation and testing
- Unified evaluation frameworks
- Production observability
- Data curation from logs
This positions Bifrost uniquely for teams wanting end-to-end AI development workflows. However, Bifrost works standalone as a pure gateway.
LiteLLM integrates with LangChain, LangGraph, and major AI frameworks. Portkey provides deep integrations with CrewAI, AutoGen, and enterprise tools.
Migration Path
Switching between gateways should be straightforward. Most implement OpenAI-compatible APIs, allowing applications to change base URLs without code changes.
Example migrating from LiteLLM to Bifrost:
from litellm import completion
response = completion(
model="gpt-4o-mini",
messages=[{"role": "user", "content": "Hello!"}],
base_url="http://localhost:8080/litellm" # Point to Bifrost
)
Bifrost maintains LiteLLM API compatibility for seamless migration.
The Bottom Line
Bifrost brings performance-first architecture to the LLM gateway space. The 50x performance advantage over Python alternatives matters for latency-sensitive applications and high-throughput workloads.
The tradeoff: LiteLLM supports more providers (100+ vs 15+). Portkey offers deeper enterprise features and managed services. Kong provides comprehensive API management integration.
For teams prioritizing performance, quick deployment, and open-source flexibility, Bifrost presents a compelling option. For teams needing maximum provider breadth or managed services, alternatives remain strong choices.
The gateway you choose depends on your specific requirements: traffic volume, latency sensitivity, provider needs, governance requirements, and deployment preferences.
Links:
Evaluating LLM gateways for your team? What factors matter most to you?
Top comments (0)