Multi-Model Routing¶
Multi-model routing cuts operational costs by matching task complexity to the appropriate model. Simple tasks run on free local models. Complex tasks escalate to premium APIs. Result: approximately 65% cost savings versus single-model approaches.
Routing Matrix¶
| Task Complexity | Model | Provider | Cost |
|---|---|---|---|
| Routine execution | Qwen 3.6 27B | Ollama (local) | $0 |
| Content generation | Ollama models | Local GPU | $0 |
| Complex reasoning | DeepSeek R1/V4 | API | ~$1 |
| Strategic analysis | Claude Opus | Anthropic | ~$10 |
| Architecture | Claude Opus | Anthropic | ~$15 |
| Code generation | DeepSeek | API | ~$2 |
Classification Logic¶
Tasks classified by context length, reasoning depth, output quality requirements, latency tolerance, and cost budget.
Fallback Chains¶
Claude Opus → DeepSeek R1 → Qwen local → Alert
When a primary model fails or times out, the chain escalates to the next available. No single model failure stops operations.
Cost Comparison¶
| Strategy | Monthly Cost | Latency |
|---|---|---|
| Claude-only | ~$500 | 500ms+ |
| DeepSeek-only | ~$150 | 300ms+ |
| Multi-model | ~$50 | 50-300ms |
Local-first routing saves $200-400/month for a production deployment while improving latency on routine tasks.