Enterprise gateway comparison

Tygress vs LiteLLM: one enterprise gateway, not another proxy

LiteLLM gives teams a mature abstraction across many model providers. Tygress goes further: one self-hosted Rust data plane for enterprise APIs, LLMs, MCP tools, and AI agents, with identity, governance, cost control, and observability applied before every upstream.

Join the Tygress waitlistExplore the AI gateway

Tygress is pre-launch. LiteLLM claims were checked against first-party documentation on 21 August 2026.

Every workload

REST/api/v1/orders
gRPCpayments.Charge
LLM/v1/chat/completions
MCPtools/call

One Rust data plane

Tygress

One route model and one policy chain for API, model, tool, and agent traffic.

IdentityRate limitsAI guardrailsCost budgetsAuditOpenTelemetry

Every upstream

APIs & microservices
OpenAI & Anthropic
Bedrock & Gemini
MCP & A2A agents
Tygress applies the same enterprise controls before traffic reaches APIs, model providers, tools, or agents.

Why Tygress

The gateway becomes the control point

The case for Tygress is not that LiteLLM lacks useful model features. It is that enterprise AI traffic eventually needs the same identity, resilience, protocol support, and audit discipline as every other API. Tygress brings those concerns into one data plane instead of synchronizing policy across an API gateway and a separate LLM proxy.

01

One policy surface

Apply identity, traffic policy, audit, and observability to REST, gRPC, LLM, MCP, and A2A routes from one gateway configuration.

02

Enterprise identity on traffic

Chain OIDC, LDAP, mTLS, OAuth2 introspection, JWE, HMAC, and API keys per route, then map credentials to consumers and tenants.

03

AI governance in the data plane

Redact PII and secrets, block prompt injection, enforce model and tool access, and hold sensitive calls for approval before forwarding.

04

Cost-aware model operations

Combine virtual keys, token-aware limits, USD budgets, semantic caching, quota-aware key pools, and provider failover.

05

Rust from edge to upstream

Tygress runs its proxy and policy path in Rust on Pingora, without a Python request path or garbage-collected data plane.

06

Self-hosted by design

Run all-in-one or split control and data planes in your VPC, on-premises, Kubernetes, or an air-gapped environment.

Side by side

Tygress and LiteLLM compared

This is a category comparison, not a claim that one product wins every workload. Tygress is designed for consolidation; LiteLLM is optimized for dedicated model access.

Tygress and LiteLLM enterprise gateway comparison
CapabilityTygressLiteLLM
Primary jobEnterprise API + AI gatewayLLM gateway and Python SDK
Traffic governedREST, gRPC, WebSocket, LLM, MCP, A2ALLM, model, MCP, and agent traffic; HTTP pass-through available
RuntimeRust and Pingora end to endPython by default; opt-in Rust paths are beta
Gateway authenticationOIDC, LDAP, mTLS, OAuth2, JWT/JWKS, JWE, HMAC, API keysVirtual keys; OIDC/JWT gateway auth is listed as Enterprise
Operational footprintOne binary; NATS, Postgres, and Redis are optional by topology or featureProxy service; Postgres required for virtual keys, Redis used for distributed features
AI controlsDLP, prompt guard, semantic cache, token limits, USD budgets, failoverBroad guardrail ecosystem, caching, budgets, routing, and fallbacks
Agent governanceMCP + A2A routing, per-consumer tool policy, gateway-held approvalsMCP and agent gateway with key, team, and organization access controls
Best fitTeams consolidating API and AI infrastructureTeams that need a mature, dedicated LLM abstraction today
AvailabilityPre-launch; waitlist openAvailable and production-deployed

Decision guide

Choose Tygress when consolidation is the goal

  • You are running an API gateway beside an LLM proxy and do not want two policy systems.
  • REST, gRPC, model, MCP, and agent traffic must share identity, rate limits, and audit.
  • PII redaction, tool approvals, cost budgets, and provider failover need to run inside your network.
  • A Rust data plane, air-gapped deployment, and feature-scoped dependencies fit your platform standards.

Choose LiteLLM when

A dedicated LLM layer is exactly what you need

  • You need a production-deployed LLM proxy immediately; Tygress is still pre-launch.
  • Provider breadth and the long tail of model integrations matter more than API consolidation.
  • Your team depends on LiteLLM's Python SDK or Python callback ecosystem.
  • Your existing enterprise API gateway is staying, and adding one more data plane is acceptable.

Migration path

Move the gateway, not every application

Tygress targets LiteLLM Proxy deployments, not the in-process Python SDK. OpenAI-compatible clients keep the same request shape while infrastructure policy moves to Tygress in deliberate stages.

# LiteLLM
base_url = "http://litellm:4000"

# Tygress
base_url = "https://gateway.internal/v1"
  1. 01

    Keep the client contract

    Point OpenAI-compatible clients at Tygress and preserve the application-facing chat and embeddings contract.

  2. 02

    Move identity to the edge

    Replace shared proxy credentials with consumer identity, per-route authentication, and tenant-aware policy.

  3. 03

    Map model operations

    Translate model aliases, fallbacks, rate limits, budgets, caches, and guardrails into Tygress routes and plugins.

  4. 04

    Consolidate API routes

    Bring REST, gRPC, and agent traffic onto the same data plane, then retire duplicate gateway policy gradually.

FAQ

Tygress vs LiteLLM questions

Is Tygress a LiteLLM alternative?

Yes, for teams evaluating a deployed LLM gateway or proxy. Tygress exposes an OpenAI-compatible API and provides model routing, virtual keys, failover, budgets, guardrails, and observability. It also handles REST, gRPC, WebSocket, MCP, and A2A traffic, so it can replace the separate API gateway that commonly sits beside LiteLLM. Tygress is currently pre-launch.

What is the main difference between Tygress and LiteLLM?

LiteLLM is centered on model access through its Python SDK and LLM proxy. Tygress is an enterprise API gateway and AI gateway in one Rust data plane. The practical difference is scope: Tygress applies one identity, policy, and observability model to application APIs, model calls, MCP tools, and agent traffic.

Does LiteLLM have a Rust gateway?

LiteLLM has an opt-in Rust core in beta. Its current documentation says Python still owns authentication, configuration, routing, logging, callbacks, and spend tracking, while supported provider paths can use Rust and unsupported paths fall back to Python. Tygress uses Rust for its data plane and policy path end to end.

Can Tygress use the same OpenAI clients as LiteLLM?

Yes. Tygress presents an OpenAI-compatible endpoint for chat completions and embeddings. In most applications the client integration begins with a base URL and credential change, followed by deliberate migration of keys, model aliases, budgets, and guardrail policy.

When is LiteLLM the better choice?

LiteLLM is the stronger choice when you need its broad provider catalog, Python SDK, mature deployment history, or an LLM-only proxy immediately. Tygress is the stronger architectural fit when the goal is to consolidate API and AI governance, but it is still pre-launch.

LiteLLM sources and verification

Competitor capabilities change quickly. These claims use LiteLLM's own documentation and pricing page, checked 21 August 2026.

One gateway for the whole stack

Bring API and AI governance together

Join the waitlist for Tygress early access, migration guidance, and launch updates.