# Open Model Routing Stack

> A practical stack for selecting, evaluating, and operating open or hosted models according to task quality, latency, cost, and fallback rules.

- Canonical: https://gptnavi.com/stacks/open-model-routing-stack
- Estimated monthly cost: $0-$500/month plus model usage
- Last materially updated: 2026-08-19
- Best for: AI product teams, Developers, Technical founders

## Problems this stack solves

- Model hype cycles
- Unmeasured quality
- Latency surprises
- Cost drift
- No provider fallback

## Recommended tools

### Model discovery

Recommended: Hugging Face, OpenRouter

Why: Find viable model families and test options through a clear, comparable interface.

### Production inference

Recommended: Replicate, Together AI, Cerebras

Why: Run appropriate model routes for batch, media, or high-performance use cases.

### Interactive latency

Recommended: GroqCloud, ngrok AI Gateway

Why: Test and operate fast, resilient routes for user-facing interactions.

### Evaluation

Recommended: LangSmith, Langfuse

Why: Version task sets, compare results, trace failures, and monitor production behavior.

## Beginner setup plan

1. Choose one customer task instead of a generic model bake-off.
2. Collect representative and failure-prone examples before testing.
3. Define a fallback and human escalation route before launch.
4. Re-run evaluations when models, prompts, or tools change.

## Included workflows

- https://gptnavi.com/workflows/open-model-routing-and-evaluation
- https://gptnavi.com/workflows/llm-evaluation-before-production
- https://gptnavi.com/workflows/ai-product-release-control-plane
- https://gptnavi.com/workflows/api-to-ai-operations-workflow