Comparison
LiteLLM vs Keybrake
LiteLLM and Keybrake both call themselves "proxies for AI workloads". They govern different halves of what an autonomous agent does. Here's the head-to-head.
Quick verdict
- Choose LiteLLM if: you need a virtual-key proxy in front of OpenAI, Anthropic, Google or another LLM endpoint — budget caps, fallback routing, a unified OpenAI-compatible API.
- Choose Keybrake if: you need per-day USD caps, endpoint allowlists, customer-scope, and mid-run revoke on Stripe, Twilio, or Resend — the non-LLM SaaS APIs the same agent also calls.
- Choose both if: your agent does inference AND moves money / sends messages. That's most production agents in 2026. They run side-by-side, joined on an
x-agent-run-idheader.
Side by side
| LiteLLM | Keybrake | |
|---|---|---|
| Category | LLM gateway / proxy | SaaS-API governance proxy |
| Vendors governed | OpenAI, Anthropic, Google, 100+ LLMs | Stripe, Twilio, Resend (+ roadmap) |
| Virtual / vault keys | Virtual keys, per-key budgets | Vault keys, per-vendor policy bundles |
| Spend cap unit | USD/day/key (inferred from tokens) | USD/day/vendor/key (parsed from vendor response) |
| Endpoint allowlist | Model allowlist | Endpoint + parameter-level allowlist (e.g. /v1/charges allowed, /v1/payouts blocked) |
| Scope beyond endpoint | Model, organisation | Stripe customer-ID allowlist, Connect account allowlist, merchant-of-record scope |
| Mid-run revoke | Yes — flip key to blocked; next request 401s | Yes — flip vault_key to revoked; median next-request 401 < 5s |
| Audit log shape | Prompt / completion / tokens in / tokens out / cost / latency | Vendor / endpoint / request-params / vendor-parsed-cost / policy-result / latency |
| Pricing model | OSS self-host free; cloud starts ~$50/mo | Free (1k req/mo, 1 vendor); Team $99/mo (100k req, all vendors); Scale custom |
| Best for | AI-ops engineers managing LLM spend across teams | Ops-risk engineers worried about a runaway agent burning real dollars |
Where the comparison falls apart (in a good way)
LiteLLM cannot read a Stripe response
LiteLLM's cost accounting is a table of model-name → cost-per-token. Stripe doesn't expose tokens; it returns a charge object with amount and fee fields. To cap Stripe spend correctly you need a proxy that parses vendor responses — which is a categorically different piece of code. Keybrake ships vendor-specific parsers (Stripe's amount, Twilio's price, Resend's flat $0.0004/email). LiteLLM does not, and adding them would be a different product.
Keybrake cannot speak OpenAI's chat-completions schema
Conversely, Keybrake does not (and won't) broker /v1/chat/completions. The schema work, the token counting, the provider fallback routing — that's LiteLLM's actual product, refined across 100+ model integrations and thousands of deployments. If you point Keybrake at OpenAI, it won't know how to cost a streamed completion or route a timeout to Anthropic. That's correct; we don't want to fragment the LLM-gateway category where LiteLLM is the right answer.
Detailed differences
Different "unit of money" to cap on
A LiteLLM daily cap is fundamentally tokens × price-table-row. A Keybrake daily cap is fundamentally parse-this-specific-vendor-response-and-sum. Those are different engineering problems. LiteLLM's solution is elegant for LLMs because the cost function is uniform; Keybrake's is necessary for SaaS tools because there is no uniform cost function — each vendor returns cost in its own shape and header.
Different revoke implications
When you revoke a LiteLLM virtual key, the consequence is a stopped chat completion. When you revoke a Keybrake vault_key, the consequence is a stopped charge. The stop-latency targets are the same (sub-10-second), but the incident severity isn't — which is why Keybrake exposes kill-switch controls (per-vendor pause, global kill, auto-pause on anomaly) more prominently than LiteLLM does.
Different audit-trail consumer
LiteLLM's audit log is consumed by the AI-ops engineer reconciling token spend. Keybrake's audit log is consumed by the ops-risk engineer (or, increasingly, the finance or compliance reviewer) asking "which customer was charged, by which agent run, under which policy?" The rows are shaped for that second question.
When to ship both
Most production agent stacks running against any money-moving SaaS API ship both proxies. See the longer piece on positioning for the diagram and the x-agent-run-id join pattern.
Try Keybrake
If you've already got LiteLLM, adding Keybrake is a base-URL change plus a vault_key_…. Five minutes.