Skip to content
ReviewRamble

LiteLLM vs Bifrost

LiteLLM is the safer default for breadth and ecosystem; Bifrost is the better fit when gateway overhead at thousands of requests a second is a real cost and you will lock down its admin API.

By Sheela · Checked Oct 26, 2026 · How we review

LiteLLM

4.3/5

Choose LiteLLM if you need the widest provider coverage, a Python SDK, or the integrations many tools already ship, and can pin and verify releases.

Read our LiteLLM review

Bifrost

3.9/5

Choose Bifrost if you run high request volumes or write Go, want Apache 2.0 across the whole codebase, and will enable management authentication from day one.

Read our Bifrost review
LiteLLM vs Bifrost, side by side
FeatureLiteLLMBifrost
Our rating4.3/53.9/5
PriceFree and open source under MIT, except the enterprise/ folder, which is under a separate commercial licence. Enterprise is custom-priced with a free 30-day trial key.Free and open source under Apache 2.0. Enterprise is custom-priced, with a 14-day free trial; the price is not published.
Best forPlatform teams that must give many developers governed access to many model providers from their own infrastructure.Teams running high request volumes, or Go shops, that want an Apache-licensed gateway with budgets and are prepared to lock down its admin API.
Language and formPython proxy plus Python SDK; Rust gateway in betaGo binary with web UI, plus a Go SDK
Provider coverage100+ providers32 providers in the docs' support matrix
Claimed overhead8 ms at P95 at 1,000 requests a second (own benchmark)11 µs at 5,000 requests a second on a t3.xlarge (own benchmark)
LicenceMIT, except an enterprise/ folder under a commercial licenceApache 2.0 for the whole repository; Enterprise is a separate build
Paid tierEnterprise on request: SSO, SCIM, audit logs, Sev 0 one-hour targetEnterprise on request: clustering, adaptive load balancing, SSO, audit logs; 14-day trial
Security record in 2026Poisoned PyPI releases in March; 17 advisories, four criticalAdmin API open by default; CVSS 9.8 command execution fixed in v2.1.0
MaturityAbout 62,000 stars; releases every few daysAbout 9,100 stars; created March 2025

Both are self-hosted gateways that put many model providers behind one OpenAI-style API, with virtual keys, budgets and fallbacks in the free build. LiteLLM, in Python, covers 100+ providers and doubles as a Python library. Bifrost, in Go, covers 32 providers in its docs and claims microseconds of overhead where LiteLLM cites milliseconds, but those speed figures are the vendors' own.

The two gateways do the same job and make different bets. LiteLLM bets on breadth: more than 100 providers, a Python library that works without the proxy, and enough adoption, about 62,000 GitHub stars, that many tools ship a LiteLLM integration. Bifrost bets on speed. It is a single Go binary from Maxim AI, and its README reports 11 µs of added latency at 5,000 requests a second, where LiteLLM's README cites 8 ms at P95 at 1,000. Maxim's own comparison at 500 requests a second on a 2 vCPU machine shows LiteLLM failing about 11% of requests; neither project's numbers have been independently reproduced in anything we found.

That speed matters less than it sounds for most teams. In Bifrost's own table, the average request took 1.61 seconds including the provider, so a few milliseconds of gateway time is noise for a chat feature. It starts to count when one gateway serves thousands of requests a second and the Python proxy needs a fleet of nodes; LiteLLM's docs size each worker at 1 vCPU and 4 GiB, while Bifrost reports handling 5,000 requests a second on a 2 vCPU, 4 GB instance.

Feature for feature, the free builds are close. Both offer virtual keys with budgets and rate limits, fallbacks, load balancing and an MCP gateway. Bifrost's licence is simpler, Apache 2.0 throughout, though its enterprise page lists governance and guardrails as paid while its open-source description claims both; LiteLLM has a similar muddle between its docs and enterprise page. Bifrost keeps clustering and adaptive load balancing for Enterprise, which matters for high availability.

Neither has a clean security year, and both hold every provider key you own. LiteLLM suffered a supply-chain attack through PyPI in March 2026 and has published 17 advisories this year. Bifrost shipped with management authentication off and its Docker image listening on all interfaces, which led to a 9.8-rated flaw letting one unauthenticated request run commands; it was fixed in v2.1.0 in September. The practical rule is the same for both: pin a version, keep the admin interface off untrusted networks, and turn authentication on before anything else.

Which should you choose?

The jobs each one is best at, from our reviews.

Pick LiteLLM if you are…

  • A platform team giving 300 engineers access to OpenAI, Anthropic and Bedrock

    Issue per-team keys with budgets and report spend by team

    Run the proxy on Kubernetes with Postgres and Redis, hand each team a virtual key with a budget, and give finance spend by key, user and team. Free in the open-source build; SSO for the admin UI needs an enterprise licence.

  • An SRE responsible for an LLM-backed product's uptime

    Fail over from Azure OpenAI to OpenAI when one deployment degrades

    Put both deployments in one model group with fallbacks and retries in the router. The cost is an extra network hop and a component that holds every provider key, so pin a -stable image and verify its cosign signature.

  • A head of engineering at a regulated fintech

    Decide between self-hosted open-source LiteLLM and the enterprise licence

    Enterprise is custom-priced with a 30-day self-hosted trial key and adds SSO, SCIM, audit logs and a one-hour Sev 0 response target. Either way, budget time for patching: four critical advisories landed in 2026.

Pick Bifrost if you are…

  • A platform engineer whose Python gateway needs a fleet of nodes at peak

    Serve several thousand requests a second through fewer gateway instances

    Maxim reports 5,000 requests a second with 100% success on a 2 vCPU, 4 GB t3.medium, peaking at about 1.3 GB of memory. Run your own load test with the published benchmark guide before resizing, and back multiple instances with PostgreSQL 16 or later.

  • A backend team writing services in Go

    Call several providers with fallbacks without running a separate proxy

    go get github.com/maximhq/bifrost/core embeds the router in the service, so there is no extra network hop and no gateway to secure. The trade is that you lose the web UI and shared spend tracking a central gateway gives you.

  • An engineering manager at a 60-person company with three product teams

    Give each team its own key and monthly budget without buying an enterprise licence

    Create a virtual key per team with a dollar budget that resets monthly and request limits, all in the open-source build. SSO for the dashboard, audit logs and clustering need Enterprise, which has a 14-day trial and unpublished pricing.

  • A team building agents that call internal tools

    Register MCP servers once and control which keys can use which tools

    Add MCP clients in the gateway and filter tools per virtual key. Turn on management authentication first and run v2.1.0 or later: stdio MCP registration was the route for the 9.8-rated flaw.

LiteLLM vs Bifrost pricing

LiteLLM

Free and open source under MIT, except the enterprise/ folder, which is under a separate commercial licence. Enterprise is custom-priced with a free 30-day trial key.

Bifrost

Free and open source under Apache 2.0. Enterprise is custom-priced, with a 14-day free trial; the price is not published.

Pros and cons

LiteLLM

Good

  • 100+ providers in OpenAI format
  • Virtual keys, budgets and fallbacks in the free build
  • Cosign-signed -stable images with 12-hour load tests
  • Terraform modules for AWS and GCP

Not so good

  • 17 security advisories in 2026, four critical
  • Poisoned PyPI releases in March 2026
  • Open-core boundary is unclear in the docs
  • Enterprise pricing not published

Bifrost

Good

  • Apache 2.0 across the whole repository
  • Virtual keys, budgets and rate limits in the free build
  • 11 µs overhead at 5,000 requests a second (vendor benchmark)
  • Drop-in endpoints for OpenAI, Anthropic and GenAI SDKs

Not so good

  • Admin API unauthenticated by default before v2.1.0; CVSS 9.8 flaw
  • 32 providers against LiteLLM's 100+
  • Clustering and adaptive load balancing are Enterprise-only
  • Most comparisons online are written by the vendor

Before you commit

LiteLLM vs Bifrost: setup, integrations, data, cost and limits
TopicLiteLLMBifrost
Setupuv tool install 'litellm[proxy]' then litellm --model gpt-4o runs a local proxy on port 4000; production uses the Docker image, the Helm chart or Terraform modules for AWS (ECS Fargate, Aurora, ElastiCache) and GCP (Cloud Run, Cloud SQL).npx -y @maximhq/bifrost or docker run -p 8080:8080 maximhq/bifrost starts the gateway and web UI on port 8080, which the README says takes under a minute; config and logs default to SQLite in the app directory, with PostgreSQL 16+ for production, plus Helm charts and Terraform in the repository.
IntegrationsOpenAI-compatible /chat/completions, /responses, /embeddings, /messages, /batches and more across 100+ providers; logging to Langfuse, MLflow, Helicone and others; MCP and A2A gateways; a Python SDK that works without the proxy.OpenAI-compatible API plus drop-in OpenAI, Anthropic, Bedrock and GenAI SDK endpoints; 32 providers in the docs; MCP gateway; Prometheus and OpenTelemetry; a plugin for Maxim's own observability product; a Go SDK.
Data and privacySelf-hosted, so prompts go only to the providers you configure; the production guide mentions no telemetry to BerriAI. The proxy keeps keys, spend logs and optionally prompts in your Postgres. Seventeen security advisories were published in 2026, four critical.Self-hosted, so prompts go only to the providers you configure; we found no usage reporting to Maxim in the docs, and its telemetry plugin serves Prometheus metrics locally. Content logging can be switched off per key. One critical and two high-severity advisories were published in 2026; management auth must be enabled by hand.
Cost at scaleThe docs size each worker at 1 vCPU and 4 GiB, so an 8-worker node needs 8 vCPU and 32 GiB, plus Postgres and Redis 7 once you run more than one instance. Enterprise is priced on request.The vendor's 5,000 requests-a-second test ran on a t3.medium (2 vCPU, 4 GB) and a t3.xlarge (4 vCPU, 16 GB), the latter peaking at 3.3 GB of memory. Running more than one node with shared state means PostgreSQL; peer-to-peer clustering is Enterprise, priced on request.
Limits5,748 open issues and pull requests; releases every few days mean frequent upgrades; Postgres connection pools must be sized per instance and worker; the Rust gateway is still in beta.550 open issues and 823 open pull requests; frequent releases with database migrations; PostgreSQL migrations can fail behind PgBouncer in transaction mode or RDS Proxy; no Python SDK; fewer providers than LiteLLM.

Common questions

Is LiteLLM better than Bifrost?
LiteLLM is the safer default for breadth and ecosystem; Bifrost is the better fit when gateway overhead at thousands of requests a second is a real cost and you will lock down its admin API. We rate LiteLLM 4.3 and Bifrost 3.9 out of 5.
When should I choose LiteLLM?
If you need the widest provider coverage, a Python SDK, or the integrations many tools already ship, and can pin and verify releases.
When should I choose Bifrost?
If you run high request volumes or write Go, want Apache 2.0 across the whole codebase, and will enable management authentication from day one.
How much do LiteLLM and Bifrost cost?
LiteLLM: Free and open source under MIT, except the enterprise/ folder, which is under a separate commercial licence. Enterprise is custom-priced with a free 30-day trial key. Bifrost: Free and open source under Apache 2.0. Enterprise is custom-priced, with a 14-day free trial; the price is not published.

Sources