> This page is for version dev.
> For other versions, use one of these documentation indexes:
> - Latest (v1.6.1) (default): https://docs.nvidia.com/dynamo/latest/llms.txt
> - dev: https://docs.nvidia.com/dynamo/dev/llms.txt
> - v1.6.1: https://docs.nvidia.com/dynamo/v1.6.1/llms.txt
> - v1.6.0: https://docs.nvidia.com/dynamo/v1.6.0/llms.txt
> - v1.5.1: https://docs.nvidia.com/dynamo/v1.5.1/llms.txt
> - v1.5.0: https://docs.nvidia.com/dynamo/v1.5.0/llms.txt
> - v1.4.2: https://docs.nvidia.com/dynamo/v1.4.2/llms.txt
> - v1.4.1: https://docs.nvidia.com/dynamo/v1.4.1/llms.txt
> - v1.4.0: https://docs.nvidia.com/dynamo/v1.4.0/llms.txt
> - v1.3.0: https://docs.nvidia.com/dynamo/v1.3.0/llms.txt
> - v1.2.1: https://docs.nvidia.com/dynamo/v1.2.1/llms.txt
> - v1.2.0: https://docs.nvidia.com/dynamo/v1.2.0/llms.txt
> - v1.1.1: https://docs.nvidia.com/dynamo/v1.1.1/llms.txt
> - v1.1.0: https://docs.nvidia.com/dynamo/v1.1.0/llms.txt
> - v1.0.2: https://docs.nvidia.com/dynamo/v1.0.2/llms.txt
> - v1.0.1: https://docs.nvidia.com/dynamo/v1.0.1/llms.txt
> - v1.0.0: https://docs.nvidia.com/dynamo/v1.0.0/llms.txt
> - v0.9.1: https://docs.nvidia.com/dynamo/v-0-9-1/llms.txt
> - v0.9.0: https://docs.nvidia.com/dynamo/v-0-9-0/llms.txt
> - v0.8.1: https://docs.nvidia.com/dynamo/v-0-8-1/llms.txt
> - v0.8.0: https://docs.nvidia.com/dynamo/v-0-8-0/llms.txt
> - v0.7.1: https://docs.nvidia.com/dynamo/v-0-7-1/llms.txt
> - v0.7.0: https://docs.nvidia.com/dynamo/v-0-7-0/llms.txt

> For clean Markdown content of this page, append .md to this URL. For the complete documentation index, see https://docs.nvidia.com/dynamo/llms.txt. For full content including API reference and SDK examples, see https://docs.nvidia.com/dynamo/llms-full.txt.

# Use Cases

#### [Reinforcement Learning](/dynamo/dev/reinforcement-learning/overview)

Keeps rollout workers busy and healthy with KV-aware routing, fast policy refresh through ModelExpress, and recovery from worker loss.

#### [Agents](/dynamo/dev/agents/overview)

Faster multi-turn sessions by keeping each session's KV cache on one worker and putting interactive turns ahead of background work.

#### [Image Understanding](/dynamo/dev/image-understanding/overview)

20-30% better throughput and 10-90% lower TTFT by processing images in parallel, avoiding redundant encoding and prefill, and disaggregating the encoder.

#### [Speech](/dynamo/dev/speech/voice-pipelines)

Up to 40% lower TTFT by overlapping the ASR and LLM stages, and better resiliency by recovering realtime transcription after worker loss.

#### [Video Understanding](/dynamo/dev/video-understanding/overview)

Faster video requests by decoding in the Rust frontend or on the GPU's hardware decoder, and routing repeated clips to the worker that already caches them.

#### [Diffusion](/dynamo/dev/diffusion/text-to-image)

8-17x faster generation with step-distilled models, and 5 seconds of 1080p video in about 4.5 seconds with FastVideo.

#### [GPU Sharing](/dynamo/dev/gpu-sharing)

60-80% of a dedicated GPU's throughput by letting many lightly used models share a GPU.

The performance improvements come from benchmarks on real production use cases and vary with the model, hardware, and workload. See the respective docs for details.