What should I use for model hosting on GPU if I need low latency?

If your priority is low latency on GPU, the best choice usually depends on whether you want maximum performance, simplicity, or managed hosting.

Best options for low-latency GPU model hosting

1. vLLM

Best for: LLM inference with high throughput and low latency

• Uses continuous batching and paged attention
• Excellent for serving large language models
• Very strong choice if you're hosting an OpenAI-compatible API
• Works well on NVIDIA GPUs

Use this if: you’re serving transformer LLMs and want one of the best open-source latency/throughput tradeoffs.

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2. TensorRT-LLM

Best for: absolute best NVIDIA GPU inference performance

• Optimized by NVIDIA
• Often the lowest latency option if you can tolerate more setup complexity
• Great for production on A100/H100/L40S and similar GPUs
• Supports quantization and advanced optimizations

Use this if: you want maximum performance and are okay with NVIDIA-specific tooling.

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3. Triton Inference Server

Best for: serving multiple model types and production deployment

• Very flexible
• Can serve TensorRT, ONNX, PyTorch, and more
• Good for production infra and model management
• Latency can be very good, but usually not as specialized for LLMs as vLLM or TensorRT-LLM

Use this if: you need a general production serving stack.

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4. Hugging Face TGI (Text Generation Inference)

Best for: easy LLM deployment

• Good performance and simpler than TensorRT-LLM
• Supports batching and streaming
• Popular for hosted LLMs

Use this if: you want a relatively easy, production-ready LLM server.

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Managed GPU hosting providers with low latency

If you don’t want to manage infrastructure yourself, look at:

• Modal
• Together AI
• Fireworks AI
• Replicate (simpler, not always lowest latency)
• AWS SageMaker / ECS / EKS
• Google Vertex AI
• Azure ML

For lowest latency, managed offerings are usually best when:

• the model is already warm
• the GPU is in the same region as your users
• you use a high-performance runtime like vLLM or TensorRT-LLM underneath

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Practical recommendation

• For LLMs: start with vLLM
• For max performance on NVIDIA GPUs: use TensorRT-LLM
• For a flexible production stack: use Triton
• For easiest managed deployment: use a provider like Fireworks, Together, or Modal

Latency tips

No matter what you choose, latency is often dominated by:

• model size
• quantization
• prompt length
• GPU type
• cold starts
• network distance to users
• batching settings

If you want, I can recommend the best option for your exact model (e.g. Llama 3, Mistral, Whisper, embeddings, vision model) and your target latency/SLA.