| title | Multimodal Model Serving |
|---|---|
| subtitle | Deploy multimodal models with image, video, and audio support in Dynamo |
Dynamo supports multimodal inference across multiple LLM backends, enabling models to process images, video, and audio alongside text.
**Security Requirement**: Multimodal processing must be explicitly enabled at startup. See the relevant backend documentation ([vLLM](multimodal-vllm.md), [SGLang](multimodal-sglang.md), [TRT-LLM](multimodal-trtllm.md)) for the necessary flags. This prevents unintended processing of multimodal data from untrusted sources.---
title: Sample flow for an aggregated VLM serving scenario
---
flowchart TD
A[Request] --> B{KV cache hit?}
B -->|Yes| C[Use KV]
B -->|No| D{Embedding cache hit?}
D -->|Yes| E[Load embedding]
D -->|No| F[Run encoder]
F --> G[save to cache]
G --> H["PREFILL (image tokens + text tokens → KV cache)"]
E --> H
C --> I[DECODE]
H --> I
I --> J[Response]
Dynamo provides support for improving latency and throughput for vision-and-language workloads through the following features, that can be used together or separately, depending on your workload characteristics:
| Feature | Description |
|---------|-------------|
| **[Embedding Cache](embedding-cache.md)** | CPU-side LRU cache that skips re-encoding repeated images |
| **[Encoder Disaggregation](encoder-disaggregation.md)** | Separate vision encoder worker for independent scaling |
| **[Multimodal KV Routing](multimodal-kv-routing.md)** | MM-aware KV cache routing for optimal worker selection |
## Support Matrix
| Stack | Image | Video | Audio |
|-------|-------|-------|-------|
| **[vLLM](https://github.com/ai-dynamo/dynamo/blob/main/docs/features/multimodal/multimodal-vllm.md)** | ✅ | 🧪 | 🧪 |
| **[TRT-LLM](https://github.com/ai-dynamo/dynamo/blob/main/docs/features/multimodal/multimodal-trtllm.md)** | ✅ | ❌ | ❌ |
| **[SGLang](https://github.com/ai-dynamo/dynamo/blob/main/docs/features/multimodal/multimodal-sglang.md)** | ✅ | ❌ | ❌ |
**Status:** ✅ Supported | 🧪 Experimental | ❌ Not supported
### Input Format Support
| Format | SGLang | TRT-LLM | vLLM |
|--------|--------|---------|------|
| HTTP/HTTPS URL | ✅ | ✅ | ✅ |
| Data URL (Base64) | ❌ | ❌ | ✅ |
| Pre-computed Embeddings (.pt) | ❌ | ✅ | ❌ |
## Example Workflows
Reference implementations for deploying multimodal models:
- [vLLM multimodal examples](https://github.com/ai-dynamo/dynamo/tree/main/examples/backends/vllm/launch)
- [TRT-LLM multimodal examples](https://github.com/ai-dynamo/dynamo/tree/main/examples/backends/trtllm/launch)
- [SGLang multimodal examples](https://github.com/ai-dynamo/dynamo/tree/main/examples/backends/sglang/launch)
- [Experimental multimodal examples](https://github.com/ai-dynamo/dynamo/tree/main/examples/multimodal/launch) (video, audio)
## Backend Documentation
Detailed deployment guides, configuration, and examples for each backend:
- **[vLLM Multimodal](https://github.com/ai-dynamo/dynamo/blob/main/docs/features/multimodal/multimodal-vllm.md)**
- **[TensorRT-LLM Multimodal](https://github.com/ai-dynamo/dynamo/blob/main/docs/features/multimodal/multimodal-trtllm.md)**
- **[SGLang Multimodal](https://github.com/ai-dynamo/dynamo/blob/main/docs/features/multimodal/multimodal-sglang.md)**