Inference Gateway review
A self-hosted OpenAI-compatible gateway with broad provider support but no fallback routing.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Inference Gateway is an open-source, self-hostable proxy for developers and teams running LLM applications across hosted and local providers. It presents a unified OpenAI-compatible API and is documented for Windows, macOS, Linux, API use, and self-hosted environments. The project covers Docker, Kubernetes, on-premises, cloud, and air-gapped deployments, with a command-line interface and desktop application also documented. Its provider list includes OpenAI, DeepSeek, Anthropic, Cohere, Groq, Cloudflare, Ollama, Google, Mistral, NVIDIA, and other documented integrations.
Its strongest fit is an environment that needs one interface across different inference backends. Logical model aliases can route requests across providers and models using round-robin selection, while server-sent events provide token-level deltas and usage metrics. Native MCP integration supports tool discovery and execution, and Kubernetes resources provide declarative gateway and agent configuration. These capabilities make the product relevant for teams coordinating hosted APIs, local runtimes, and operational tooling without changing the application-facing API.
Operational visibility and access control are substantial parts of the offering. Prometheus metrics, OTLP tracing, structured logs, and Grafana dashboards support observability, while OIDC authentication and JWT validation against issuer JWKS address gateway access. The CLI adds token usage and per-model pricing for cost tracking. The main limitation is routing resilience: retries and fallback routing are deferred, so teams requiring automatic recovery between providers should choose a gateway with explicit fallback behavior instead. Inference Gateway suits developers who value open-source control, self-hosting, local-provider support, and standards-based integrations; it is less suitable when managed hosting or built-in failover is a primary requirement.
Inference Gateway pros and cons
- Where it wins
- Unifies 15 documented hosted and local LLM providers
- Adds observability with Prometheus, OTLP, logs, and Grafana
- Supports OIDC, JWT, MCP, Kubernetes, and cost tracking
- Where it doesn't
- Retries and fallback routing are deferred
- Requires self-hosting for deployment
- Routing uses round-robin rather than fallback recovery
Inference Gateway fact sheet, pricing and score →
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