---
title: "Accelerate BERT inference with DeepSpeed-Inference on GPUs"
url: https://daily.dev/posts/accelerate-bert-inference-with-deepspeed-inference-on-gpus-4ayvo1djq
source_url: https://www.philschmid.de/bert-deepspeed-inference
type: article
source: "Philipp Schmid"
published: 2026-05-31T07:41:04.263Z
updated: 2026-05-31T07:59:42.171Z
tags: ["python", "bert"]
reading_time: 5
upvotes: 0
comments: 0
language: en
---

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# Accelerate BERT inference with DeepSpeed-Inference on GPUs

**[Philipp Schmid](https://daily.dev/sources/philschmid)** · 5 min read · 0 upvotes · 0 comments

## Summary

A hands-on tutorial demonstrating how to optimize BERT-large for GPU inference using DeepSpeed-Inference with minimal code changes. Using a fine-tuned NER model on CoNLL-2003, the guide walks through setting up the environment, establishing a baseline, applying DeepSpeed's InferenceEngine via a single `deepspeed.init_inference` call, and benchmarking results. The optimization reduces latency from 30.4ms to 10.4ms (2.92x speedup) while retaining 99.88% of the original model accuracy on an NVIDIA T4 GPU.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.philschmid.de/bert-deepspeed-inference>

---

Tags: [#python](https://daily.dev/tags/python), [#bert](https://daily.dev/tags/bert)

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