From 801b13266757cdad30bdae9e41004299db7ec6c7 Mon Sep 17 00:00:00 2001 From: filipstrand Date: Mon, 19 Aug 2024 19:19:12 +0200 Subject: [PATCH] Update readme with latest performance numbers --- README.md | 26 +++++++++++++++++++++----- 1 file changed, 21 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index dca8aef..d227d18 100644 --- a/README.md +++ b/README.md @@ -87,12 +87,28 @@ ImageUtil.save_image(image, "image.png") If the model is not already downloaded on your machine, it will start the download process and fetch the model weights (~34GB in size for the Schnell model). -Generating a single image (with 2 inference steps, Schnell model) takes between 2 and 3 minutes. This implementation has been tested on two Macbook Pro machines: -- 2021 M1 Pro (32 GB) -- 2023 M2 Max (32 GB) -Update: -On faster machines, [@karpathy](https://gist.github.com/awni/a67d16d50f0f492d94a10418e0592bde?permalink_comment_id=5153531#gistcomment-5153531) and [@awni](https://x.com/awnihannun/status/1823515121827897385) have reported times ~20s and below! +### Image generation speed (updated) + +These numbers are based on the Schnell model, with the configuration provided in the code snippet below. +To time your machine, run the following: +``` +time python main.py \ +--prompt "Luxury food photograph" \ +--steps 2 \ +--seed 2 \ +--height 1024 \ +--width 1024 +``` + +| Device | User | Reported Time | +|--------------------|----------------------------------------------------------------------------------------------------------------------------|---------------| +| M3 Max | [@karpathy](https://gist.github.com/awni/a67d16d50f0f492d94a10418e0592bde?permalink_comment_id=5153531#gistcomment-5153531) | ~20s | +| M2 Ultra | [@awni](https://x.com/awnihannun/status/1823515121827897385) | <15s | +| 2023 M2 Max (96GB) | [@explorigin](https://github.com/filipstrand/mflux/issues/6) | ~25s | +| 2021 M1 Pro (16GB) | [@qw-in](https://github.com/filipstrand/mflux/issues/7) | ~175s | +| 2021 M1 Pro (32GB) | @filipstrand | ~160s | +| 2023 M2 Max (32GB) | @filipstrand | ~70s | ### Equivalent to Diffusers implementation