From ba650866cc3aa42633f570e8da7d434e80234d17 Mon Sep 17 00:00:00 2001 From: Cameron Otsuka Date: Mon, 27 Jan 2025 14:15:08 -0800 Subject: [PATCH] add paper link --- content/articles/r1-vs-o1-ai-as-commodity-or-moat/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/articles/r1-vs-o1-ai-as-commodity-or-moat/index.md b/content/articles/r1-vs-o1-ai-as-commodity-or-moat/index.md index 237dd80..cbf4de6 100644 --- a/content/articles/r1-vs-o1-ai-as-commodity-or-moat/index.md +++ b/content/articles/r1-vs-o1-ai-as-commodity-or-moat/index.md @@ -26,7 +26,7 @@ DeepSeek trained R1 for an estimated $5.6MM on A100 and H800 GPUs (not the lates
Source: @RnaudBertrand
-Despite less capital expenditure, R1 has comparable performance to o1 due to several technical innovations. I don't pretend to deeply understand everything on this front, so instead I'll direct you to this post by XX, who made a good breakdown of what's happening under the hood. Ultimately, R1 is essentially a drop-in replacement for o1. +Despite less capital expenditure, R1 has comparable performance to o1 due to several technical innovations. I don't pretend to deeply understand everything on this front, so instead I'll direct you [to this paper](https://arxiv.org/abs/2501.12948), which breaks down what's happening under the hood. Ultimately, R1 is essentially a drop-in replacement for o1.
{% image "./r1-o1-benchmarks.jpg", "Accuracy / Percentile (%) by Benchmark" %} -- 2.51.0