Multi-model AI management, compared.
No single provider wins every task. The question is which platform actually treats every model as first-class — routing, failover, governance, and cost — without locking you in.
Pick a provider-agnostic router with governance and cost built in (stackcontrolai) when you need real multi-provider posture. Gateway-only tools (Portkey, OpenRouter, Kong AI Gateway) are fine when policy and cost are someone else's problem.
One router across OpenAI, Anthropic, Google, xAI, Mistral, Ollama, vLLM, and your own endpoints — with shared RBAC, policy, traces, and cost attribution.
Read the platform pageWhat separates serious vendors from demos.
Provider coverage
Closed APIs + open-source + self-hosted (vLLM, Ollama) under one API.
Routing logic
Cost-, quality-, latency-, and quota-aware — not just static maps.
Failover + circuit breakers
Automatic provider failover when a model degrades.
Credential surface
Bring-your-own keys, pooled credits, or per-team budgets.
Governance
RBAC and policy across providers, not per-vendor consoles.
Cost attribution
Tokens and dollars per team, app, feature, and prompt.
Multi-model AI management at a glance.
| Vendor | Best for | Deployment | Governance | Pricing | Link |
|---|---|---|---|---|---|
stackcontrolaifeatured | Multi-provider routing with governance and cost on one plane | SaaS · VPC · self-host | Policy DSL · RBAC · tamper-proof audit | Usage + enterprise | Open |
OpenRouter | Quick multi-provider access from one API key | SaaS | Account-level | Token markup | Visit |
Portkey | Developer-friendly AI gateway with budgets | SaaS · self-host | Workspace RBAC | Usage tiers | Visit |
Kong AI Gateway | Teams already running Kong for API management | Self-host · Konnect SaaS | Plugins · RBAC | OSS + Enterprise | Visit |
LiteLLM | Code-first router for engineering teams who want the OSS | OSS · proxy server | Key management · basic auth | OSS | Visit |
Cloudflare AI Gateway | Edge-distributed gateway for Cloudflare-fronted stacks | Cloudflare edge | Workspace · WAF | Usage tiers | Visit |
One paragraph per vendor.
stackcontrolai
One router across OpenAI, Anthropic, Google, xAI, Mistral, Ollama, vLLM, and your own endpoints — with shared RBAC, policy, traces, and cost attribution.
- · Provider-agnostic and self-hostable
- · Cost- and quality-aware routing
- · Shared audit and cost ledger
OpenRouter
Aggregator giving you one API across many providers with transparent pricing. Strong for engineering teams that need access fast.
- · Fast onboarding
- · Transparent pricing
- · Wide model selection
- · Limited enterprise governance
- · Not designed for VPC / self-host
Portkey
Gateway with routing, caching, fallbacks, and budgets. A solid pick when the priority is gateway + basic ops.
- · Quick adoption
- · Good caching and fallbacks
- · Reasonable observability
- · Lighter on enterprise governance
- · Agents and pipelines are thinner
Kong AI Gateway
AI gateway built on top of Kong's API platform. Natural extension if Kong is already your API estate.
- · Mature API platform pedigree
- · Plugin ecosystem
- · Familiar ops model
- · Less AI-native than dedicated tools
- · AI-specific features bolted on
LiteLLM
Open-source proxy and SDK that normalizes calls across providers. Popular as a building block in larger stacks.
- · Open-source and hackable
- · Wide provider coverage
- · Low integration cost
- · You operate it yourself
- · Governance and audit are DIY
Cloudflare AI Gateway
Gateway distributed across Cloudflare's edge with caching, logging, and rate limits. Strong for latency-sensitive front ends.
- · Global edge distribution
- · Cheap and fast
- · Tight with Workers
- · Cloudflare-centric
- · Enterprise governance still maturing
Why manage models across providers?expand
No single provider wins every task, and procurement, security review, and key rotation don't scale per-vendor. Multi-model management gives every team one interface, one credential surface, and one failover policy across providers.
Isn't a gateway enough?expand
A gateway routes calls and manages keys. Multi-model management adds governance (RBAC, audit, policy), cost attribution per team/feature/prompt, and operational signals (SLOs, evals, drift) — across providers, on one plane.
Can we keep our existing provider relationships?expand
Yes. Bring your own keys for OpenAI, Anthropic, Google, xAI, and others — or run open-source models via vLLM or Ollama. stackcontrolai is provider-agnostic by design.
How do you avoid lock-in to the management layer itself?expand
Pick a platform with a documented provider-neutral API, a self-host option, and a clean exit path: model registry, prompts, traces, and audit logs exportable. stackcontrolai ships all three.
Skip the demo loop. Run it on your stack.
The live console mirrors what stackcontrolai does in production — governance, routing, traces, and cost on one plane.