LLM Gateway vs Orq.ai

LLM Gateway provides one OpenAI-compatible API for routing requests among more than 250 models from over 40 providers. If a provider errors, times out, or rate-limits a request, it can retry up to twice with another provider for the same model. Its dashboard tracks request, token, spend, latency, error, and cache metrics, with model and provider breakdowns. Teams can use their own provider API keys without a platform fee and pay providers directly. The open-source core is licensed under AGPLv3 and can be self-hosted for free; enterprise features require a license. The Free plan is free, billed free forever, and has a 5% fee on credit usage. It includes 200+ models across 40+ providers, activity logs and export, and 20 requests per minute on free models; paid models are not rate limited. Enterprise pricing is custom and not listed. It includes custom routing, unlimited data retention, a 99.9% uptime SLA, and 24/7 priority support. Published integration guides cover tools including Claude Code, Cursor, Codex CLI, Cline, n8n, and VS Code.

Orq.ai is an AI gateway and platform for routing, governing and observing requests to models and tools. Through an OpenAI-compatible API, it lists more than 500 models from over 30 providers. Smart Router can select models by cost or quality strategy, with fallbacks, retries and load balancing. Controls include budgets, spend limits, guardrails and PII redaction. Observability covers request traces, cost and token tracking, dashboards and OpenTelemetry ingestion. Integrations include OpenAI and Anthropic APIs, Python and Node SDKs, remote MCP servers, Azure AI Foundry, Vertex AI and compatible endpoints. It supports Claude Code, Cursor, Codex and more than 25 agent frameworks. Deployment options are EU SaaS, VPC and on-premises. Orq.ai says prompts, outputs and traces are not used to train models, and lists EU residency and retention controls. Pay-as-you-go is free, usage-based, with provider-rate model charges and stated allowances.