Model performance

Generally Available: The fastest, most accurate and cost-efficient Whisper transcription

At Baseten, we've built the most performant (1000x real-time factor), accurate, and cost-efficient speech-to-text pipeline for production AI audio transcription

3 others

How to build function calling and JSON mode for open-source and fine-tuned LLMs

Use a state machine to generate token masks for logit biasing to enable function calling and structured output at the model server level.

How to double tokens per second for Llama 3 with Medusa

We observe up to a 122% increase in tokens per second for Llama 3 after training custom Medusa heads and running the updated model with TensorRT-LLM

1 other

How to serve 10,000 fine-tuned LLMs from a single GPU

LoRA swapping with TRT-LLM supports in-flight batching and loads LoRA weights in 1-2 ms, enabling each request to hit a different fine-tune.

Benchmarking fast Mistral 7B inference

Running Mistral 7B in FP8 on H100 GPUs with TensorRT-LLM, we achieve best in class time to first token and tokens per second on independent benchmarks.

3 others

33% faster LLM inference with FP8 quantization

Quantizing open-source LLMs to FP8 resulted in near-zero perplexity gains and yielded material performance improvements across latency, throughput, and cost.

High performance ML inference with NVIDIA TensorRT

Use TensorRT to achieve 40% lower latency for SDXL and sub-200ms time to first token for Mixtral 8x7B on A100 and H100 GPUs.

1 other

40% faster Stable Diffusion XL inference with NVIDIA TensorRT

Using NVIDIA TensorRT to optimize each component of the SDXL pipeline, we improved SDXL inference latency by 40% and throughput by 70% on NVIDIA H100 GPUs.

2 others

Unlocking the full power of NVIDIA H100 GPUs for ML inference with TensorRT

Double or triple throughput at same-or-better latencies by switching to H100 GPUs from A100s for model inference with TensorRT/TensorRT-LLM.