diff --git a/gen.regression.go b/gen.regression.go
index 483d713..7d74ae6 100644
--- a/gen.regression.go
+++ b/gen.regression.go
@@ -13,6 +13,8 @@ import (
 	"go/format"
 
 	"gonum.org/v1/gonum/mat"
+	"golang.org/x/exp/maps"
+	"sort"
 )
 
 type LinearRegression struct {
@@ -407,10 +409,11 @@ func {{ .Name }}(width, height uint32, flashAttention bool) uint64 {
 			Degree: 2,
 		}
 
-		xs, ys := make([]float64, 0, len(t.x2y)), make([]float64, 0, len(t.x2y))
-		for x, y := range t.x2y {
-			xs = append(xs, x)
-			ys = append(ys, y*1024*1024) // MB to B
+		xs := maps.Keys(t.x2y)
+		sort.Float64s(xs)
+		ys := make([]float64, len(xs))
+		for j, x := range xs {
+			ys[j] = t.x2y[x] * 1024 * 1024 // MB to B
 		}
 		pr.Fit(xs, ys)
 
@@ -440,10 +443,11 @@ func {{ .Name }}(width, height uint32, flashAttention bool) uint64 {
 
 		lr := LinearRegression{}
 
-		xs, ys := make([]float64, 0, len(t.fax2y)), make([]float64, 0, len(t.fax2y))
-		for x, y := range t.fax2y {
-			xs = append(xs, x)
-			ys = append(ys, y*1024*1024) // MB to B
+		xs := maps.Keys(t.fax2y)
+		sort.Float64s(xs)
+		ys := make([]float64, len(xs))
+		for j, x := range xs {
+			ys[j] = t.fax2y[x] * 1024 * 1024 // MB to B
 		}
 		lr.Fit(xs, ys)
 
diff --git a/zz_generated.diffusion_model_memory_usage.regression.go b/zz_generated.diffusion_model_memory_usage.regression.go
index 5f870f1..4ed421e 100644
--- a/zz_generated.diffusion_model_memory_usage.regression.go
+++ b/zz_generated.diffusion_model_memory_usage.regression.go
@@ -5,7 +5,7 @@ import "math"
 // GuessSD1DiffusionModelMemoryUsage returns the memory usage in bytes for the given width and height,
 // which is calculated by linear regression or polynomial regression.
 func GuessSD1DiffusionModelMemoryUsage(width, height uint32, flashAttention bool) uint64 {
-	coefficients := []float64{7.8763685671743e+06, 161.42301986333496, 0.007812489338703485}
+	coefficients := []float64{7.876368567179878e+06, 161.4230198633402, 0.007812489338703482}
 	degree := 2
 	x := float64(width * height)
 
@@ -24,7 +24,7 @@ func GuessSD2DiffusionModelMemoryUsage(width, height uint32, flashAttention bool
 	x := float64(width * height)
 
 	if flashAttention {
-		coefficients = []float64{3.78068128077788e+06, 513.2102510934714}
+		coefficients = []float64{3.7806812807775633e+06, 513.2102510934715}
 		degree = 1
 	}
 
@@ -38,12 +38,12 @@ func GuessSD2DiffusionModelMemoryUsage(width, height uint32, flashAttention bool
 // GuessSDXLDiffusionModelMemoryUsage returns the memory usage in bytes for the given width and height,
 // which is calculated by linear regression or polynomial regression.
 func GuessSDXLDiffusionModelMemoryUsage(width, height uint32, flashAttention bool) uint64 {
-	coefficients := []float64{5.554129038929968e+07, 138.31961166554433, 0.0006109454572342757}
+	coefficients := []float64{5.55412903892993e+07, 138.3196116655456, 0.0006109454572342753}
 	degree := 2
 	x := float64(width * height)
 
 	if flashAttention {
-		coefficients = []float64{-5.95880278052181e+06, 500.0687898914631}
+		coefficients = []float64{-5.958802780521662e+06, 500.06878989146264}
 		degree = 1
 	}
 
@@ -57,7 +57,7 @@ func GuessSDXLDiffusionModelMemoryUsage(width, height uint32, flashAttention boo
 // GuessSDXLRefinerDiffusionModelMemoryUsage returns the memory usage in bytes for the given width and height,
 // which is calculated by linear regression or polynomial regression.
 func GuessSDXLRefinerDiffusionModelMemoryUsage(width, height uint32, flashAttention bool) uint64 {
-	coefficients := []float64{4.939599234485548e+07, 155.2477810191175, 0.0007351735797614931}
+	coefficients := []float64{4.939599234485548e+07, 155.24778101911753, 0.0007351735797614931}
 	degree := 2
 	x := float64(width * height)
 
@@ -76,7 +76,7 @@ func GuessSDXLRefinerDiffusionModelMemoryUsage(width, height uint32, flashAttent
 // GuessSD3MediumDiffusionModelMemoryUsage returns the memory usage in bytes for the given width and height,
 // which is calculated by linear regression or polynomial regression.
 func GuessSD3MediumDiffusionModelMemoryUsage(width, height uint32, flashAttention bool) uint64 {
-	coefficients := []float64{1.6529921370035086e+07, 234.66562477184195, 0.0014648995324747492}
+	coefficients := []float64{1.6529921370034331e+07, 234.6656247718448, 0.0014648995324747485}
 	degree := 2
 	x := float64(width * height)
 
@@ -104,7 +104,7 @@ func GuessSD35MediumDiffusionModelMemoryUsage(width, height uint32, flashAttenti
 // GuessSD35LargeDiffusionModelMemoryUsage returns the memory usage in bytes for the given width and height,
 // which is calculated by linear regression or polynomial regression.
 func GuessSD35LargeDiffusionModelMemoryUsage(width, height uint32, flashAttention bool) uint64 {
-	coefficients := []float64{2.320436920291992e+07, 410.3731196298318, 0.002319594715894278}
+	coefficients := []float64{2.3204369202917013e+07, 410.37311962983387, 0.0023195947158942774}
 	degree := 2
 	x := float64(width * height)
 
@@ -118,7 +118,7 @@ func GuessSD35LargeDiffusionModelMemoryUsage(width, height uint32, flashAttentio
 // GuessFLUXDiffusionModelMemoryUsage returns the memory usage in bytes for the given width and height,
 // which is calculated by linear regression or polynomial regression.
 func GuessFLUXDiffusionModelMemoryUsage(width, height uint32, flashAttention bool) uint64 {
-	coefficients := []float64{4.651166867423782e+07, 997.7758807792155, 0.001457339256095295}
+	coefficients := []float64{4.651166867423724e+07, 997.7758807792177, 0.001457339256095294}
 	degree := 2
 	x := float64(width * height)