diff --git a/mlx/backend/cpu/matmul.cpp b/mlx/backend/cpu/matmul.cpp
index 029e94aab..777b31c02 100644
--- a/mlx/backend/cpu/matmul.cpp
+++ b/mlx/backend/cpu/matmul.cpp
@@ -131,10 +131,6 @@ void Matmul::eval_cpu(const std::vector<array>& inputs, array& out) {
 }
 
 void AddMM::eval_cpu(const std::vector<array>& inputs, array& out) {
-  if (out.dtype() != float32) {
-    throw std::runtime_error(
-        "[AddMM::eval_cpu] Currently only supports float32.");
-  }
   if (out.size() == 0) {
     out.set_data(allocator::malloc(out.nbytes()));
     return;
diff --git a/python/tests/test_blas.py b/python/tests/test_blas.py
index 67289ceef..82c63e3d8 100644
--- a/python/tests/test_blas.py
+++ b/python/tests/test_blas.py
@@ -712,6 +712,15 @@ class TestBlas(mlx_tests.MLXTestCase):
             expected = beta * c + alpha * (a @ b)
             self.assertTrue(mx.allclose(expected, out))
 
+        # Test half precision
+        for t, tol in [(mx.float16, 1e-3), (mx.bfloat16, 1e-2)]:
+            c = mx.ones((32, 32)).astype(t)
+            a = mx.random.uniform(shape=(32, 32)).astype(t)
+            b = mx.random.uniform(shape=(32, 32)).astype(t)
+            out = mx.addmm(c, a, b)
+            expected = a @ b + c
+            self.assertTrue(mx.allclose(out, expected, rtol=tol, atol=tol))
+
     def test_addmm_grad(self):
         def make_ref_addmm(alpha, beta):
             return lambda c, a, b: alpha * (a @ b) + beta * c