diff --git a/lib/LinearSolveAutotune/Project.toml b/lib/LinearSolveAutotune/Project.toml
index f01a99bd7..9d06c49cb 100644
--- a/lib/LinearSolveAutotune/Project.toml
+++ b/lib/LinearSolveAutotune/Project.toml
@@ -10,6 +10,7 @@ CPUSummary = "2a0fbf3d-bb9c-48f3-b0a9-814d99fd7ab9"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
+FastLapackInterface = "29a986be-02c6-4525-aec4-84b980013641"
 GitHub = "bc5e4493-9b4d-5f90-b8aa-2b2bcaad7a26"
 LAPACK_jll = "51474c39-65e3-53ba-86ba-03b1b862ec14"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -36,6 +37,7 @@ CPUSummary = "0.2"
 CUDA = "5"
 DataFrames = "1"
 Dates = "1"
+FastLapackInterface = "2"
 GitHub = "5"
 LAPACK_jll = "3"
 LinearAlgebra = "1"
diff --git a/lib/LinearSolveAutotune/src/LinearSolveAutotune.jl b/lib/LinearSolveAutotune/src/LinearSolveAutotune.jl
index 0cbfd6d7c..f698de377 100644
--- a/lib/LinearSolveAutotune/src/LinearSolveAutotune.jl
+++ b/lib/LinearSolveAutotune/src/LinearSolveAutotune.jl
@@ -36,6 +36,7 @@ using blis_jll
 using LAPACK_jll
 using CUDA
 using Metal
+using FastLapackInterface
 
 
 # Optional dependencies for telemetry and plotting
@@ -156,7 +157,8 @@ end
         samples::Int = 5,
         seconds::Float64 = 0.5,
         eltypes = (Float32, Float64, ComplexF32, ComplexF64),
-        skip_missing_algs::Bool = false)
+        skip_missing_algs::Bool = false,
+        include_fastlapack::Bool = false)
 
 Run a comprehensive benchmark of all available LU factorization methods and optionally:
 
@@ -179,6 +181,7 @@ Run a comprehensive benchmark of all available LU factorization methods and opti
   - `seconds::Float64 = 0.5`: Maximum time per benchmark
   - `eltypes = (Float32, Float64, ComplexF32, ComplexF64)`: Element types to benchmark
   - `skip_missing_algs::Bool = false`: If false, error when expected algorithms are missing; if true, warn instead
+  - `include_fastlapack::Bool = false`: If true, includes FastLUFactorization in benchmarks
 
 # Returns
 
@@ -199,6 +202,9 @@ results = autotune_setup(sizes = [:small, :medium, :large, :big])
 # Large matrices only
 results = autotune_setup(sizes = [:large, :big], samples = 10, seconds = 1.0)
 
+# Include FastLapackInterface.jl algorithms
+results = autotune_setup(include_fastlapack = true)
+
 # After running autotune, share results (requires gh CLI or GitHub token)
 share_results(results)
 ```
@@ -209,7 +215,8 @@ function autotune_setup(;
         samples::Int = 5,
         seconds::Float64 = 0.5,
         eltypes = (Float64,),
-        skip_missing_algs::Bool = false)
+        skip_missing_algs::Bool = false,
+        include_fastlapack::Bool = false)
     @info "Starting LinearSolve.jl autotune setup..."
     @info "Configuration: sizes=$sizes, set_preferences=$set_preferences"
     @info "Element types to benchmark: $(join(eltypes, ", "))"
@@ -219,7 +226,7 @@ function autotune_setup(;
     @info "System detected: $(system_info["os"]) $(system_info["arch"]) with $(system_info["num_cores"]) cores"
 
     # Get available algorithms
-    cpu_algs, cpu_names = get_available_algorithms(; skip_missing_algs = skip_missing_algs)
+    cpu_algs, cpu_names = get_available_algorithms(; skip_missing_algs = skip_missing_algs, include_fastlapack = include_fastlapack)
     @info "Found $(length(cpu_algs)) CPU algorithms: $(join(cpu_names, ", "))"
 
     # Add GPU algorithms if available
diff --git a/lib/LinearSolveAutotune/src/algorithms.jl b/lib/LinearSolveAutotune/src/algorithms.jl
index 360f4bd40..d71c2b768 100644
--- a/lib/LinearSolveAutotune/src/algorithms.jl
+++ b/lib/LinearSolveAutotune/src/algorithms.jl
@@ -1,12 +1,13 @@
 # Algorithm detection and creation functions
 
 """
-    get_available_algorithms(; skip_missing_algs::Bool = false)
+    get_available_algorithms(; skip_missing_algs::Bool = false, include_fastlapack::Bool = false)
 
 Returns a list of available LU factorization algorithms based on the system and loaded packages.
 If skip_missing_algs=false, errors when expected algorithms are missing; if true, warns instead.
+If include_fastlapack=true, includes FastLUFactorization in benchmarks.
 """
-function get_available_algorithms(; skip_missing_algs::Bool = false)
+function get_available_algorithms(; skip_missing_algs::Bool = false, include_fastlapack::Bool = false)
     algs = []
     alg_names = String[]
 
@@ -68,6 +69,12 @@ function get_available_algorithms(; skip_missing_algs::Bool = false)
     push!(algs, SimpleLUFactorization())
     push!(alg_names, "SimpleLUFactorization")
 
+    # FastLapackInterface LU if requested (always available as dependency)
+    if include_fastlapack
+        push!(algs, FastLUFactorization())
+        push!(alg_names, "FastLUFactorization")
+    end
+
     return algs, alg_names
 end