diff --git a/README.md b/README.md
index c775c9776..c7e22d706 100644
--- a/README.md
+++ b/README.md
@@ -15,6 +15,8 @@ Features
   - Sparse feature format allows easy handling of missing values, and improve computation efficiency.
 * Push the limit on single machine:
   - Efficient implementation that optimizes memory and computation.
+* Speed: XGBoost is very fast
+  - IN [demo/higgs/speedtest.py](../blob/master/demo/kaggle-higgs/speedtest.py), kaggle higgs data it is faster(on our machine 20 times faster using 4 threads) than sklearn.ensemble.GradientBoostingClassifier
 * Layout of gradient boosting algorithm to support user defined objective
 * Python interface, works with numpy and scipy.sparse matrix
 
diff --git a/demo/kaggle-higgs/README.md b/demo/kaggle-higgs/README.md
index b3db23266..28472a848 100644
--- a/demo/kaggle-higgs/README.md
+++ b/demo/kaggle-higgs/README.md
@@ -14,8 +14,6 @@ make
 
 3. Run ./run.sh
 
-
-
 Speed
 =====
 speedtest.py compares xgboost's speed on this dataset with sklearn.GBM