Bifrost is an open-source LLM gateway built in Go that delivers production-grade reliability with <11µs overhead at 5,000 RPS. If you're evaluating LiteLLM or experiencing performance bottlenecks at scale, Bifrost is a drop-in alternative designed for serious GenAI workloads.
[ PERFORMANCE AT A GLANCE ]
[ WHY BIFROST ]
| Your Challenge | Why Bifrost |
|---|---|
| High latency at scale | Built in Go with native concurrency for high-throughput workloads |
| Infrastructure bottlenecks | Connection pooling and zero runtime allocation, no Python GIL limitations |
| Memory consumption | Efficient memory management with Go's lightweight goroutines |
| Complex self-hosting | Zero-configuration deployment via npx or Docker, no Redis/Postgres required |
| Limited observability | Native Prometheus metrics and OpenTelemetry built-in, not bolted on |
| Production reliability | 100% success rate at 5,000 RPS with <11µs overhead |
[ PERFORMANCE BENCHMARKS ]
Benchmarked on production infrastructure under sustained load. Perfect reliability with sub-11µs overhead.
4 vCPU, 16GB RAM
2 vCPU, 4GB RAM
[ ARCHITECTURE ]
The Python Challenge
Python's GIL prevents true parallelism, forcing the interpreter to execute one thread at a time. Under high concurrency, this creates a bottleneck.
Python's asyncio adds overhead in context switching and event loop management, especially with thousands of concurrent requests.
Python's dynamic typing and garbage collection consume more memory and can introduce latency spikes.
Production Python deployments often require Redis for caching and rate limiting, adding operational complexity.
Bifrost's Go Advantage
Go's goroutines enable handling thousands of concurrent requests with minimal memory overhead. No GIL, no bottlenecks.
As a compiled language, Go eliminates interpretation overhead and provides predictable, low-latency execution.
Connection pooling with efficient memory reuse and lightweight goroutines reduce RAM consumption.
Bifrost handles configuration, logging, and state management internally without requiring external databases.
[ FEATURE COMPARISON ]
| Feature | Bifrost | LiteLLM |
|---|---|---|
| Provider Support | 20+ providers, 1000+ models | 100+ LLM APIs |
| OpenAI-Compatible API | Yes | Yes |
| Automatic Failover | Adaptive load balancing | Retry logic |
| Semantic Caching | Built-in | ⚠️Via external integration |
| Zero Configuration | Works out of box | ⚠️Requires config file |
| Web UI | Built-in dashboard | Not included |
| Deployment Time | <30 seconds | 2-10 minutes |
| Feature | Bifrost | LiteLLM |
|---|---|---|
| Language | Go (compiled) | Python (interpreted) |
| Gateway Overhead | 11µs | 40ms |
| Concurrency Model | Native goroutines | Async/await with GIL |
| Connection Pooling | Native | ⚠️Via configuration |
| External Dependencies | Zero | Redis recommended |
| Feature | Bifrost | LiteLLM |
|---|---|---|
| Prometheus Metrics | Native, no setup | Available |
| OpenTelemetry | Built-in | Via integration |
| Distributed Tracing | Native | Via integration |
| Request Logging | Built-in SQLite | ⚠️Via configuration |
| Real-time Analytics | Web UI dashboard | External tools required |
| Feature | Bifrost | LiteLLM |
|---|---|---|
| Budget Management | Virtual keys with limits | Team/user budgets |
| Rate Limiting | Per-key, per-model | Global and per-user |
| Access Control | Model-specific keys | RBAC available |
| Cost Tracking | Real-time per request | Available |
| SSO Integration | Google, GitHub | Available |
| Audit Logs | Built-in | Available |
| Feature | Bifrost | LiteLLM |
|---|---|---|
| Setup Complexity | Single command | Install + config |
| Configuration | Web UI, API, or files | Files or env variables |
| Hot Reload | No restart needed | ⚠️Requires restart |
| Plugin System | Go-based plugins | Python callbacks |
| Deployment Asset | Single binary | python package + webserver |
| Docker Size | 80 MB | |
| License | Apache 2.0 | MIT |
[ ENTERPRISE READY ]
Everything you need for production AI infrastructure, without bolting on external tools.
Create API keys with spending limits, model restrictions, and rate limits per team or use case.
Cost controlMetrics automatically available at /metrics - requests, latency, provider health, memory usage.
No sidecarsDistributed tracing built-in. Point to your Jaeger or OTEL collector and traces flow automatically.
Built-inMonitor spend per key, per model, per team via the built-in web UI. No external tools required.
Web UIAutomatically distributes load based on current success rates, latency patterns, and available capacity.
Intelligent routingIf a provider fails, Bifrost transparently routes to configured backups. Zero downtime, zero manual intervention.
High availability[ QUICK START ]
No configuration files, no Redis, no external databases. Just install and go.
One command. No configuration files, no Redis, no databases required.
Add provider keys, configure models, set up fallback chains, all from the browser.
Change the base URL in your code. Everything else stays the same.
[ DECISION GUIDE ]
[ COMPARISON SUMMARY ]
| Factor | Bifrost | LiteLLM |
|---|---|---|
| Best For | High-throughput production systems | Multi-provider abstraction, Python teams |
| Performance | 11µs | 40ms |
| Setup Time | <30 seconds | 2-10 minutes |
| Dependencies | Zero | Redis recommended |
| Deployment Asset | Single binary, Docker, npx | Python package, Docker |
| Configuration | Web UI, API, files | Files, env variables |
| Observability | Native Prometheus, built-in UI | Via integrations |
| Cost | Free (Apache 2.0) | Free (MIT) |
| Providers | 20+ providers, 1000+ models | 100+ LLM APIs |
100% open source under Apache 2.0. Free forever. No vendor lock-in. Get started in under 30 seconds.
[ 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.
Change just one line of code. Works with OpenAI, Anthropic, Vercel AI SDK, LangChain, and more.
