Bifrost vs LiteLLM (2026): Which LLM Gateway to Choose

How Bifrost and LiteLLM differ

Bifrost and LiteLLM are both open-source LLM gateways that put many model providers behind one OpenAI-compatible API, and both are free to self-host. Where they split is the language each one is written in, and what that means once the gateway sits on your request path.

LiteLLM is a Python SDK and proxy server from BerriAI that covers 100+ providers. The open-source proxy already includes virtual keys for users and teams, budgets, rate limits, spend tracking, and fallbacks, which makes it a common first gateway for Python teams. Because the proxy runs in Python, though, you may need more instances at high request volumes to keep latency steady than you would with a compiled gateway.

Supply-chain risk is also worth weighing with LiteLLM. On March 24, 2026, two compromised releases (1.82.7 and 1.82.8) were published to PyPI with a credential stealer, and since a gateway holds a key for every provider it routes to, anyone who installed either version had to rotate all of them. The official Docker image wasn't affected and v1.83.0 is the patched release, but if the incident has you comparing LiteLLM alternatives, how a gateway builds and publishes its releases belongs on the checklist.

Bifrost is Maxim AI's gateway, written in Go, with 1,000+ models behind one API. Its free tier includes virtual-key budgets and rate limits, fallbacks, semantic caching, an MCP gateway, and built-in observability with OpenTelemetry export. Bifrost is built around performance, and Maxim's published benchmark reports 0.99ms of gateway overhead at 500 requests per second on a 2-vCPU instance.

Bifrost vs LiteLLM pricing

Both gateways are free at any volume when you run them yourself, so the real cost is the infrastructure and the engineering time it takes to operate them. Paid plans come in when you need enterprise controls, and neither vendor publishes a price.

Bifrost Enterprise is custom-priced and adds guardrails, clustering, adaptive load balancing, SSO through SAML or OIDC, role-based access control, and audit logs. It supports VPC, on-prem, and air-gapped deployment with SLA-backed support, and Maxim offers a 14-day Enterprise trial on request.

LiteLLM Enterprise is an annual contract sized by gateway request capacity, deployment architecture, and support needs rather than by tokens. It adds SSO with SCIM, OIDC and JWT authentication, audit logs, secret manager integration with key rotation, and a multi-region control plane, and you can try it with a 30-day trial key without a sales call.

Since SSO and audit logs sit behind Enterprise on both, the free versions can work well for a single team but may run into limits once a security review asks for them.

Respan: an AI gateway you don't have to run

Whichever one you choose, Bifrost and LiteLLM both put a gateway on your request path that your team deploys, scales, patches, and monitors. Respan is the AI router with built-in observability and automated evals, so you get one OpenAI-compatible endpoint for 1,000+ models without operating the infrastructure behind it.

Because routing and tracing live on the same platform, every request through the gateway is traced with its cost, latency, and token usage, and that same production traffic feeds the evals that catch quality regressions before users do. Fallback chains and spend controls are configured in the same place, so a provider outage or a budget spike shows up next to the traces that explain it. For security reviews, Respan is SOC 2 and GDPR compliant, offers HIPAA with a BAA, and supports PII masking.

If your goal is shipping the LLM app rather than running the gateway, Respan lets you route, observe, and evaluate every LLM call from one platform, starting on the free tier. Bifrost suits teams that already operate their own gateway and need minimal overhead, while LiteLLM suits Python teams that want budgets and virtual keys in a free proxy.