docs: add Graviton-vs-GPU LLM inference benchmark sample (vLLM & llama.cpp) - #21
Open
Jyothirmaikottu wants to merge 1 commit into
Open
Jyothirmaikottu wants to merge 1 commit into
Jyothirmaikottu wants to merge 1 commit into
Conversation
…a.cpp) Reproducible benchmark for serving Qwen3-8B across three compute targets (AWS Graviton arm64 CPU, x86 CPU, and x86 GPU) using prebuilt public AWS Deep Learning Container images. Includes serving scripts for the vLLM and llama.cpp engines, a benchmark driver with multiple load profiles (baseline, saturation, production, sweep, sharegpt), and a teardown helper.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Adds a reproducible sample that benchmarks Qwen3-8B across AWS Graviton (arm64) CPU, x86 CPU, and x86 GPU using prebuilt public AWS Deep Learning Container images for the vLLM and llama.cpp engines. Includes serving scripts for each engine, a benchmark driver (inference-perf) with multiple load profiles, a teardown helper, and nav/index entries under Inference.