ClawPaneModel Routing: How to Automatically Pick the Best LLM for Every Request
Model routing is the infrastructure layer that decides which language model handles each request. Instead of a static assignment, the router evaluates each request's needs and picks the best available model based on your priorities.
The Model Routing Problem
Your AI application doesn't have one type of request — it has dozens. A support agent might handle:
- Simple greetings (any model works)
- FAQ lookups (fast model preferred)
- Complex troubleshooting (quality model needed)
- Multilingual conversations (specialized model required)
Hardcoding one model means you're overpaying on easy requests and potentially underperforming on hard ones. Model routing fixes both problems simultaneously.
How Model Routing Scores Requests
A model router maintains a scoring function across multiple dimensions:
Cost Score
Each model has a known price per token (input and output). The router calculates expected cost based on the prompt length and estimated response length. Cheaper models score higher when cost weight is prioritized.
Latency Score
Models differ dramatically in response time. Flash/Lite variants return in 100–200ms. Frontier models may take 2–5 seconds. The router tracks real-time latency data and scores accordingly.
Quality Score
Quality scoring uses benchmark data, task-specific evaluations, and historical performance. A model that scores 95% on coding benchmarks gets a higher quality score for code requests.
The Final Selection
Each dimension is weighted according to your router configuration. A cost-first router might weight cost at 60%, quality at 25%, and latency at 15%. The model with the highest weighted score wins.
Router Configurations for Common Workloads
| Workload | Cost | Quality | Latency | Recommended Preset |
|---|---|---|---|---|
| Customer support | 0.55 | 0.25 | 0.20 | Economy |
| Code generation | 0.10 | 0.70 | 0.20 | Quality |
| Real-time chat | 0.15 | 0.20 | 0.65 | Fast |
| Data processing | 0.70 | 0.20 | 0.10 | Economy |
| Content creation | 0.20 | 0.60 | 0.20 | Quality |
Model Routing vs. Load Balancing
Model routing is not load balancing. Load balancers distribute requests across identical servers. Model routers select between different models with different capabilities and prices.
A load balancer sends request #1 to Server A and request #2 to Server B — same model, different server. A model router sends request #1 to GPT-5 (complex) and request #2 to Gemini 2.5 Flash (simple) — different models, optimized per request.
Implementing Model Routing
You can build model routing from scratch, but it requires maintaining model catalogs, pricing data, latency monitoring, and fallback logic. Most teams use a routing service instead.
ClawPane provides model routing as a drop-in OpenClaw provider. Configure your weights, get an API key, and every request is routed automatically. No changes to your agent configs.