diff --git a/.github/workflows/benchmark.yml b/.github/workflows/benchmark.yml
new file mode 100644
index 0000000..5c56b17
--- /dev/null
+++ b/.github/workflows/benchmark.yml
@@ -0,0 +1,29 @@
+name: Benchmark this PR
+
+on:
+  pull_request:
+    branches: [main]
+    paths-ignore: ['docs/**']
+
+permissions:
+  pull-requests: write
+  contents: read
+
+jobs:
+  benchmark:
+    runs-on: ubuntu-latest
+    timeout-minutes: 30
+    strategy:
+      fail-fast: false
+      matrix:
+        version: ["1", "lts"]
+    env:
+      # Force consistent Julia depot path for self-hosted runners
+      JULIA_DEPOT_PATH: ~/.julia
+    steps:
+      - uses: MilesCranmer/AirspeedVelocity.jl@action-v1
+        with:
+          julia-version: ${{ matrix.version }}
+          script: "benchmark/benchmarks.jl"
+          extra-pkgs: "Lux,StableRNGs"
+          job-summary: true
diff --git a/benchmark/benchmarks.jl b/benchmark/benchmarks.jl
new file mode 100644
index 0000000..5a52f79
--- /dev/null
+++ b/benchmark/benchmarks.jl
@@ -0,0 +1,43 @@
+using NeuralOperators, BenchmarkTools
+using Lux, Random, StableRNGs
+
+const SUITE = BenchmarkGroup()
+const rng = StableRNG(123)
+
+# =============================================================================
+# FourierNeuralOperator
+# =============================================================================
+
+fno1 = FourierNeuralOperator(; chs = (2, 8, 8, 8, 4), modes = (8,), shift = false)
+fno2 = FourierNeuralOperator(; chs = (2, 8, 8, 8, 4), modes = (4, 4), shift = true)
+
+ps1, st1 = Lux.setup(rng, fno1)
+ps2, st2 = Lux.setup(rng, fno2)
+
+x1 = rand(rng, Float32, 32, 2, 4)
+x2 = rand(rng, Float32, 16, 16, 2, 4)
+
+SUITE["fno"] = BenchmarkGroup()
+
+SUITE["fno"]["construct_1d"] = @benchmarkable FourierNeuralOperator(
+    ; chs = (2, 8, 8, 8, 4), modes = (8,)
+)
+SUITE["fno"]["setup_1d"] = @benchmarkable Lux.setup($rng, $fno1)
+SUITE["fno"]["forward_1d"] = @benchmarkable $fno1($x1, $ps1, $st1)
+SUITE["fno"]["forward_2d"] = @benchmarkable $fno2($x2, $ps2, $st2)
+
+# =============================================================================
+# DeepONet
+# =============================================================================
+
+don = DeepONet(; branch = (64, 32, 32, 16), trunk = (1, 8, 8, 16))
+psd, std = Lux.setup(rng, don)
+
+xin = (rand(rng, Float32, 64, 5), rand(rng, Float32, 1, 10))
+
+SUITE["deeponet"] = BenchmarkGroup()
+
+SUITE["deeponet"]["construct"] = @benchmarkable DeepONet(
+    ; branch = (64, 32, 32, 16), trunk = (1, 8, 8, 16)
+)
+SUITE["deeponet"]["forward"] = @benchmarkable $don($xin, $psd, $std)