Quick answer: what is the best LiteLLM alternative?
The best LiteLLM alternative for most teams is GoModel, an MIT-licensed, open-source AI gateway written in Go. GoModel ships as a single binary, exposes an OpenAI-compatible API, and includes caching, guardrails, budgets, and observability. Other strong options are Bifrost for raw performance, TensorZero for LLM optimization, and Portkey for a managed enterprise platform.
| Rank | LiteLLM alternative | Best for |
|---|---|---|
| 1 | GoModel | Secure, self-hosted, auditable gateway |
| 2 | Bifrost | Maximum throughput |
| 3 | TensorZero | Prompt and model optimization |
| 4 | Portkey | Managed enterprise platform |
What is a LiteLLM alternative?
A LiteLLM alternative is any AI gateway or LLM proxy that replaces LiteLLM's core job: giving applications one unified API across multiple LLM providers, with routing, fallbacks, cost controls, and logging. Most teams search for a LiteLLM alternative when they need better security, higher performance, or easier deployment in regulated environments.
Why teams are looking for a LiteLLM alternative in 2026
LiteLLM is a widely used Python library that acts as a unified proxy for over 100 LLM providers. Its popularity also made it a target.
On March 24, 2026, LiteLLM versions 1.82.7 and 1.82.8 on PyPI were published with credential-stealing malware, attributed to the threat actor TeamPCP. The payload hid in a .pth file that Python executes automatically at startup, so the code ran without anyone importing LiteLLM. It harvested SSH keys, cloud credentials, Kubernetes tokens, and environment variables, including API keys.
The maintainers responded quickly, and users running the official Docker proxy image were not affected, since that image pins package versions. Still, the incident made a structural risk visible: an AI gateway holds API keys for your whole AI stack, and a Python package with a deep dependency tree is a large attack surface for that job.
The other common reasons teams look for a LiteLLM alternative are:
- Performance. A Python proxy usually needs more replicas and tuning under heavy load than a compiled Go or Rust gateway.
- Deployment constraints. Air-gapped and on-premises environments favor self-contained binaries over runtime package installs.
- Upgrade predictability. LiteLLM's fast release pace can make upgrades harder to manage.
How to choose a LiteLLM alternative
A good LiteLLM alternative should offer:
- An OpenAI-compatible API, so migration is a base-URL change.
- A minimal supply-chain footprint, ideally a compiled binary with pinned dependencies.
- Governance features: virtual keys, budgets, rate limits, and fallbacks.
- Caching, both exact and semantic.
- Open-standard observability through OpenTelemetry and Prometheus.
- Self-hosting, including on-prem and air-gapped support.
- Transparent licensing, with enterprise features clearly separated from the open core.
1. GoModel: the best overall LiteLLM alternative
GoModel is an open-source LiteLLM alternative written in Go, designed for secure, self-hosted AI gateway deployments.
- Language: Go
- License: MIT (open core)
- Deployment: single binary, Docker image of about 17 MB
- API: OpenAI-compatible
- Website: gomodel.enterpilot.io
Why GoModel is the top LiteLLM alternative
GoModel was built specifically to address the limitations of Python-based gateways. It compiles to one static binary with no interpreter, no pip install at deploy time, and no .pth-style auto-execution path. Security teams can checksum it, scan it, and move it into a locked-down network as a single artifact.
GoModel covers the features LiteLLM proxy users rely on:
- Exact and semantic caching
- Budget controls and usage tracking
- A guardrails pipeline for prompts and responses
- Prometheus metrics and OpenTelemetry, both free in the MIT core
- An admin dashboard
- Per-provider-family translators that respect each provider's API differences
- A passthrough endpoint (
/p/{provider}/...) for native provider features
GoModel enterprise and cloud
GoModel's enterprise module adds SSO, RBAC, audit logs, and multi-tenancy. Unlike many open-core gateways, that code lives in a visible /ee folder in the public repository, so buyers can review it. GoModel Cloud offers a hosted bring-your-own-key tier for teams that don't want to run infrastructure.
Who should choose GoModel
Choose GoModel as your LiteLLM alternative if you left LiteLLM over security concerns, work in a regulated industry, need on-prem or air-gapped deployment, or want an AI gateway you can fully audit.
Trade-off: GoModel is younger than LiteLLM, so confirm your specific providers are supported before migrating.
2. Bifrost: the fastest LiteLLM alternative
Bifrost is a Go-based LiteLLM alternative from Maxim AI focused on high throughput.
- Language: Go
- License: Apache 2.0 (open core)
- Deployment: binary, Docker, or npx
Bifrost unifies 20+ providers behind one OpenAI-compatible API, with automatic failover, load balancing, and semantic caching. In its own sustained 5,000 RPS benchmarks, Bifrost added about 11 µs of overhead per request.
Trade-offs: advanced capabilities such as adaptive load balancing, clustering, guardrails, and the MCP gateway are enterprise features, and the enterprise code is developed privately.
Choose Bifrost if throughput is your top priority and you accept a closed enterprise tier.
3. TensorZero: the best LiteLLM alternative for optimization
TensorZero is a Rust-based LiteLLM alternative that combines a gateway with an LLM optimization framework.
- Language: Rust
- License: open source
- Deployment: single Docker container
TensorZero combines an LLM gateway with observability, optimization, evaluation, and experimentation. The project reports under 1 ms of p99 latency overhead at 10k QPS. It uses metrics and human feedback to optimize prompts, models, and inference strategies, and includes A/B testing, routing, fallbacks, and retries.
Trade-off: TensorZero is closer to a framework than a drop-in proxy, so full value requires adopting its workflow.
Choose TensorZero if improving model quality through experiments matters more than centralized governance.
4. Portkey: the managed enterprise LiteLLM alternative
Portkey is a managed AI gateway, now owned by Palo Alto Networks.
Portkey offers routing, observability, guardrails, and cost tracking as a managed platform. Palo Alto Networks completed its acquisition of Portkey and plans to make it the core AI gateway of its Prisma AIRS security platform.
Trade-off: Portkey's roadmap is now tied to a large security vendor, which may affect pricing, packaging, and neutrality. It is also a weaker fit for air-gapped deployments.
Choose Portkey if you want a fully managed gateway and already use Palo Alto Networks tooling.
LiteLLM alternative comparison table
| Feature | GoModel | Bifrost | TensorZero | Portkey | LiteLLM |
|---|---|---|---|---|---|
| Language | Go | Go | Rust | TypeScript | Python |
| License | MIT | Apache 2.0 | Open source | Managed + OSS gateway | MIT |
| Single binary | Yes | Yes | Container | No | No |
| OpenAI-compatible API | Yes | Yes | Yes | Yes | Yes |
| Semantic caching | Yes | Yes | Yes | Yes | Yes |
| Guardrails | Built-in | Enterprise | Limited | Yes | Via integrations |
| Public enterprise code | Yes | No | N/A | No | Yes |
| Air-gapped fit | Excellent | Good | Good | Limited | Possible |
| Supply-chain footprint | Minimal | Minimal | Small | Moderate | Large |
How to migrate to a LiteLLM alternative
If you use the LiteLLM proxy:
- Deploy your LiteLLM alternative alongside LiteLLM.
- Map your
config.yamlmodel list, fallbacks, and virtual keys to the new gateway. - Point one low-risk service at the new base URL.
- Compare latency, errors, and cost.
- Move the remaining services and retire LiteLLM.
If you use the LiteLLM Python library: replace litellm.completion() calls with a standard OpenAI client pointed at your new gateway. This also removes the gateway from your application's dependency tree.
Security note: rotate any provider keys that were present on machines that installed LiteLLM 1.82.7 or 1.82.8.
LiteLLM alternative FAQ
What is the best LiteLLM alternative?
GoModel is the best LiteLLM alternative for most teams. It is MIT-licensed, OpenAI-compatible, ships as a single Go binary, and includes caching, guardrails, budgets, and observability.
What is the best open-source LiteLLM alternative?
GoModel is the best open-source LiteLLM alternative for self-hosted and regulated environments. Bifrost and TensorZero are also open source.
Is there a LiteLLM alternative written in Go?
Yes. GoModel and Bifrost are both LiteLLM alternatives written in Go that compile to a single binary.
Which LiteLLM alternative is most secure?
GoModel is designed for the lowest supply-chain risk: one compiled binary, no runtime package installs, and enterprise code that is publicly reviewable.
Which LiteLLM alternative works in air-gapped environments?
GoModel is built for on-prem and air-gapped deployments because it ships as one self-contained binary.
Is LiteLLM still safe to use?
The compromised versions were removed and versions 1.82.6 and earlier were not affected. The broader risk of running a large Python dependency tree in the component holding all your API keys remains.
Can I switch to a LiteLLM alternative without changing code?
If you use the LiteLLM proxy with an OpenAI client, usually yes: you only change the base URL and keys.
Try the best LiteLLM alternative: get started with GoModel at https://github.com/ENTERPILOT/GoModel/.
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