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Auriko vs Switchyard: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Auriko and Switchyard — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Auriko logo

Auriko

Auriko

Freemium

Cache-aware LLM router and inference platform with one API across major providers and zero provider price markup.

Key features

  • Unified API: One OpenAI-compatible endpoint fronts OpenAI, Anthropic, Google, xAI, Fireworks, Together, DeepSeek, Moonshot and more.
  • Cache-Aware Routing: Routes each request using cost estimates that account for each provider's cache hit behavior and workload patterns.
  • Multiple Focus Modes: Optimize routing for cost, time-to-first-token, throughput or balanced modes, with optional custom weights.
  • Deterministic Routing (Pro): Always picks the highest-scoring eligible route so production behavior is reproducible.
  • Bring Your Own Key: BYOK support lets teams keep existing provider contracts and quotas while still benefiting from the router.
  • Fallback & Load Balancing: Automatic fallback and load-balanced routing keep apps up when a single provider degrades.

Best for

  • Production LLM Cost Reduction: Engineering teams cut inference bills by routing chat and RAG traffic to the cheapest cache-friendly provider.
  • Reliability Fallback: Ops teams shield user-facing agents from provider outages via automatic fallback routes.
  • Latency-Sensitive Apps: Real-time products optimize for time-to-first-token when the user is watching a stream.
  • BYOK Enterprise Deployments: Enterprises route through Auriko while keeping token spend on their own provider contracts.
  • Multi-Model A/B Testing: Product teams experiment with different backend models without rewriting client code.
View Auriko details
Switchyard logo

Switchyard

NVIDIA

Free

An open-source Rust proxy and library that routes LLM traffic across models and providers while preserving native OpenAI and Anthropic API compatibility.

Key features

  • Protocol Translation: Converts between OpenAI Chat Completions, OpenAI Responses and Anthropic Messages formats so clients keep their native API while any backend serves the request.
  • Multi-Backend Routing: Spreads traffic across vLLM, NVIDIA NIM, Ollama and any OpenAI-compatible endpoint, letting you point an existing coding agent at an open-source model without changing the agent.
  • LLM Classifier Router: Uses request content to decide whether a given turn needs the weak or the strong model tier, cutting spend on turns that do not need frontier capability.
  • Stage Router: Routes most turns from signals already in the conversation — tool results, errors, conversation stage — so no extra model call is needed to make the decision.
  • Escalation Router: Runs every turn on the weak tier first, then has a judge read that answer and decide whether the same request should be re-sent to the strong tier.
  • Random Routing for A/B Tests: Applies a fixed traffic split across targets for benchmarking, baselines and cost experiments.
  • Operational Metrics: Exposes Prometheus metrics for requests, errors, latency, token counts and the overhead added by routing itself.
  • Server or Library Deployment: Run it as a standalone Rust proxy configured by routes.toml, or embed switchyard-libsy in your own application so it decides the target and hands the model call back to you.

Best for

  • Pointing Coding Agents at Open Models: Serve Claude Code or Codex from vLLM, NIM or Ollama without the agent knowing the API changed.
  • Cost/Performance Optimization: Send routine turns to a cheap weak-tier model and reserve the strong tier for turns a classifier or judge says need it.
  • Model A/B Benchmarking: Split traffic on a fixed ratio across two models to compare quality, latency and cost on real production requests.
  • Provider Migration and Failover: Keep application code on one API shape while swapping or mixing the providers behind it.
  • Embedding Routing in an Agent Runtime: Drop the routing algorithms into an existing gateway or agent framework via the library path without adopting a new HTTP stack.
  • Operational Visibility: Track per-route latency, error rates and token spend through Prometheus to find which routes are actually costing money.
View Switchyard details