Bifrost: 50x Faster Open-Source AI Gateway
Bifrost unifies 20+ LLM providers via OpenAI-compatible API, adding routing, failover, caching, and governance—50x faster than LiteLLM in 500 RPS benchmarks with 100% success rate and P50 latency of 804ms vs 38s.
Centralize Routing, Failover, and Governance for Multi-Provider AI
Deploy Bifrost as a gateway layer between your app and 20+ providers like OpenAI and Anthropic to avoid scattering retry logic, key management, and monitoring across services. It exposes a single OpenAI-compatible API, compatible with SDKs including LangChain and LiteLLM, letting you route traffic, apply weighted load balancing, set fallbacks for outages, and enforce virtual keys for team budgets without app changes. Semantic caching reduces redundant calls, while observability via Prometheus metrics and OpenTelemetry provides request logs and analytics. For agents, MCP support acts as client/server for tool filtering, OAuth, and execution controls, centralizing access for Claude Desktop or similar. This setup cuts provider-specific code in your app, enabling dynamic shifts like favoring cheaper models for tasks without redeploys.
Launch Locally in Seconds for Testing
Run npx -y @maximhq/bifrost to start the HTTP gateway on port 8080 with a web UI at http://localhost:8080 for configuring providers, viewing live metrics, and managing keys. Test immediately: 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!"}]}'. Use Docker for containers or flags like --port and --log-level for tweaks; scale to enterprise clustering for private networks. Post-setup, update routing or controls via UI without restarts, keeping your app pointed at one stable endpoint.
Outperform LiteLLM with Low-Overhead Design
In AWS t3.medium benchmarks at 500 RPS, Bifrost hits 100% success (vs LiteLLM's 88.78%), P50 latency 804ms (vs 38.65s), P99 1.68s (vs 90.72s), max 6.13s (vs 92.67s), throughput 424 req/s (vs 44.84), and peak memory 120MB (vs 372MB). At 5,000 RPS sustained, it adds just 11 microseconds overhead per request. Prioritize it over proxies like LiteLLM or Vercel AI Gateway (author switched post-security breach) when performance and controls matter, as it consolidates traffic management, budgets, observability, and availability into one low-overhead layer.
Target Internal Platforms, SaaS, and Agent Systems
Use Bifrost for teams outgrowing single-provider setups: internal AI platforms needing shared governance, SaaS with model features requiring logs/visibility, enterprises demanding private deploys, or agent workflows combining model routing and tool security. It shines when loose ends like outages, cost limits, or audits pile up, grouping features into traffic management (routing/failover), governance (keys/budgets), observability (metrics/logs), and deployment (local-to-cluster). Avoid for narrow single-model use; it's infrastructure for expanding AI systems across teams.