diff --git a/ops.h b/ops.h
index db2ae4f..7619b44 100644
--- a/ops.h
+++ b/ops.h
@@ -214,7 +214,8 @@ static HWY_NOINLINE HWY_MAYBE_UNUSED void Gelu(float* HWY_RESTRICT x,
                                                size_t size) {
   namespace hn = hwy::HWY_NAMESPACE;
   using D = hn::ScalableTag<float>;
-  hn::Transform(D(), x, size, [](D d, hn::Vec<D> v) { return Gelu(d, v); });
+  hn::Transform(D(), x, size,
+                [](D d, hn::Vec<D> v) HWY_ATTR { return Gelu(d, v); });
 }
 
 // out[i] = BF(mul[i] * Gelu(gelu_in[i]))
@@ -567,22 +568,41 @@ static HWY_NOINLINE void Softmax(float* HWY_RESTRICT x, size_t size,
   namespace hn = hwy::HWY_NAMESPACE;
   using D = hn::ScalableTag<float>;
   const D d;
-  using V = hn::Vec<D>;
+  const size_t N = hn::Lanes(d);
 
-  // Find max so we can subtract it below.
-  const V vmin = hn::Set(d, hwy::LowestValue<float>());
-  V max = vmin;
-  hn::Foreach(d, x, mask_pos, vmin,
-              [&max](D d, V v) { max = hn::Max(max, v); });
-  max = hn::MaxOfLanes(d, max);  // broadcast
+  // Find max so we can subtract it below. Avoid hn::Foreach because SVE vectors
+  // cannot be lambda-captured.
+  // TODO(janwas): could be replaced with an hn::Accumulate algo.
+  const hn::Vec<D> vmin = hn::Set(d, hwy::LowestValue<float>());
+  hn::Vec<D> vmax = vmin;
+  size_t idx = 0;
+  if (mask_pos >= N) {
+    for (; idx <= mask_pos - N; idx += N) {
+      vmax = hn::Max(vmax, LoadU(d, x + idx));
+    }
+  }
+  vmax = hn::Max(vmax, LoadNOr(vmin, d, x + idx, mask_pos - idx));
+  vmax = hn::MaxOfLanes(d, vmax);  // broadcast
 
   // Subtract max (avoid precision loss for large exponents) and exponentiate.
-  V sum = hn::Zero(d);
-  hn::Transform(d, x, mask_pos, [&sum, max](D d, V v) {
-    const V out = hn::Exp(d, hn::Sub(v, max));
+  // Also avoid hn::Transform because the additional `sum` output vector cannot
+  // be captured by a lambda.
+  hn::Vec<D> sum = hn::Zero(d);
+  idx = 0;
+  if (mask_pos >= N) {
+    for (; idx <= mask_pos - N; idx += N) {
+      const hn::Vec<D> out = hn::Exp(d, hn::Sub(hn::LoadU(d, x + idx), vmax));
+      sum = hn::Add(sum, out);
+      hn::StoreU(out, d, x + idx);
+    }
+  }
+  if (mask_pos > idx) {
+    const size_t remaining = mask_pos - idx;
+    const hn::Vec<D> out =
+        hn::Exp(d, hn::Sub(hn::LoadN(d, x + idx, remaining), vmax));
     sum = hn::Add(sum, out);
-    return out;
-  });
+    hn::StoreN(out, d, x + idx, remaining);
+  }
 
   // Normalize to probability distribution
   const float mul = 1.0f / hn::ReduceSum(d, sum);
@@ -601,13 +621,12 @@ static HWY_NOINLINE void LogitsSoftCap(const float cap, float* HWY_RESTRICT x,
   namespace hn = hwy::HWY_NAMESPACE;
   using D = hn::ScalableTag<float>;
   const D d;
-  using V = hn::Vec<D>;
 
-  const V inv_cap = hn::Set(d, 1.0f / cap);
-  const V vcap = hn::Set(d, cap);
+  const float inv_cap = 1.0f / cap;
 
-  hn::Transform(d, x, size, [vcap, inv_cap](D d, hn::Vec<D> v) {
-    return hn::Mul(vcap, hn::Tanh(d, hn::Mul(inv_cap, v)));
+  hn::Transform(d, x, size, [cap, inv_cap](D d, hn::Vec<D> v) HWY_ATTR {
+    return hn::Mul(hn::Set(d, cap),
+                   hn::Tanh(d, hn::Mul(v, hn::Set(d, inv_cap))));
   });
 }