---
# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
title: Router
---

The Dynamo KV Router intelligently routes requests by evaluating their computational costs across different workers. It considers both decoding costs (from active blocks) and prefill costs (from newly computed blocks), using KV cache overlap to minimize redundant computation. Optimizing the KV Router is critical for achieving maximum throughput and minimum latency in distributed inference setups.

## Quick Start

To launch the Dynamo frontend with the KV Router:

```bash
python -m dynamo.frontend --router-mode kv --http-port 8000
```

For Kubernetes, set `DYN_ROUTER_MODE=kv` on the Frontend service. Workers automatically report KV cache events — no worker-side configuration changes needed.

| Argument | Default | Description |
|----------|---------|-------------|
| `--router-mode kv` | `round_robin` | Enable KV cache-aware routing |
| `--router-kv-overlap-score-weight` | `1.0` | Balance prefill vs decode optimization (higher = better TTFT) |
| `--no-router-kv-events` | enabled | Fall back to approximate routing (no event consumption from workers) |
| `--router-queue-threshold` | `4.0` | Backpressure queue threshold; enables priority scheduling via `nvext.agent_hints.priority` |
| `--router-queue-policy` | `fcfs` | Queue scheduling policy: `fcfs` (tail TTFT), `wspt` (avg TTFT), or `lcfs` (comparison-only reverse ordering) |

### Standalone Router

You can also run the KV router as a standalone service (without the Dynamo frontend). See the [Standalone Router component](https://github.com/ai-dynamo/dynamo/tree/main/components/src/dynamo/router/) for more details.

For all CLI arguments, environment variables, K8s deployment examples, and tuning guidelines, see the [Router Guide](router-guide.md). For A/B benchmarking, see the [KV Router A/B Benchmarking Guide](../../benchmarks/kv-router-ab-testing.md).

## Prerequisites and Limitations

**Requirements:**
- **Dynamic endpoints only**: KV router requires `register_model()` with `model_input=ModelInput.Tokens`. Your backend handler receives pre-tokenized requests with `token_ids` instead of raw text.
- Backend workers must call `register_model()` with `model_input=ModelInput.Tokens` (see [Backend Guide](../../development/backend-guide.md))
- You cannot use `--static-endpoint` mode with KV routing (use dynamic discovery instead)

**Multimodal Support:**
- **TRT-LLM and vLLM**: Multimodal routing supported for images via multimodal hashes
- **SGLang**: Image routing not yet supported
- **Other modalities** (audio, video, etc.): Not yet supported

**Limitations:**
- Static endpoints not supported—KV router requires dynamic model discovery via etcd to track worker instances and their KV cache states

For basic model registration without KV routing, use `--router-mode round-robin` or `--router-mode random` with both static and dynamic endpoints.

## Next Steps

- **[Router Guide](router-guide.md)**: Deep dive into KV cache routing, configuration, disaggregated serving, and tuning
- **[Router Examples](router-examples.md)**: Python API usage, K8s examples, and custom routing patterns
- **[Standalone Indexer](standalone-indexer.md)**: Run the KV indexer as a separate service for independent scaling
- **[Router Design](../../design-docs/router-design.md)**: Architecture details, algorithms, and event transport modes
