diff --git a/candle-metal-kernels/src/lib.rs b/candle-metal-kernels/src/lib.rs
index 1bf4d20cbf..0e2614c5c8 100644
--- a/candle-metal-kernels/src/lib.rs
+++ b/candle-metal-kernels/src/lib.rs
@@ -1879,6 +1879,7 @@ pub fn call_sdpa_vector(
     k_stride: &[usize],
     k_buffer: &Buffer,
     v_offset: usize,
+    v_stride: &[usize],
     v_buffer: &Buffer,
     output: &Buffer,
     alpha: f32,
@@ -1890,7 +1891,8 @@ pub fn call_sdpa_vector(
     let gqa_factor = (q_shape[1] / k_shape[1]) as i32;
     let n = k_shape[2] as i32;
     let b = (q_shape[0] * q_shape[1]) as i32;
-    let stride = k_stride[1];
+    let kstride = k_stride[1];
+    let vstride = v_stride[1];
 
     let name = match (bk, itype) {
         (32, SdpaDType::F16) => "sdpa_vector_float16_t_32",
@@ -1949,15 +1951,20 @@ pub fn call_sdpa_vector(
     encoder.set_bytes(
         6,
         std::mem::size_of::<usize>() as u64,
-        &stride as *const usize as *const c_void,
+        &kstride as *const usize as *const c_void,
     );
     encoder.set_bytes(
         7,
+        std::mem::size_of::<usize>() as u64,
+        &vstride as *const usize as *const c_void,
+    );
+    encoder.set_bytes(
+        8,
         std::mem::size_of::<f32>() as u64,
         &alpha as *const f32 as *const c_void,
     );
     encoder.set_bytes(
-        8,
+        9,
         std::mem::size_of::<f32>() as u64,
         &softcapping as *const f32 as *const c_void,
     );
diff --git a/candle-metal-kernels/src/scaled_dot_product_attention.metal b/candle-metal-kernels/src/scaled_dot_product_attention.metal
index d65cc621ac..bfe241d1b0 100644
--- a/candle-metal-kernels/src/scaled_dot_product_attention.metal
+++ b/candle-metal-kernels/src/scaled_dot_product_attention.metal
@@ -56,6 +56,7 @@ template <typename T, int D>
     const constant int& gqa_factor,
     const constant int& N,
     const constant size_t& k_stride,
+    const constant size_t& v_stride,
     const constant float& scale,
     const constant float& softcapping,
     uint3 tid [[threadgroup_position_in_grid]],
@@ -82,7 +83,7 @@ template <typename T, int D>
   const int kv_head_idx = head_idx / gqa_factor;
   queries += head_idx * D + simd_lid * elem_per_thread;
   keys += kv_head_idx * k_stride + simd_gid * D + simd_lid * elem_per_thread;
-  values += kv_head_idx * k_stride + simd_gid * D + simd_lid * elem_per_thread;
+  values += kv_head_idx * v_stride + simd_gid * D + simd_lid * elem_per_thread;
   out += head_idx * D + simd_gid * elem_per_thread;
 
   // Read the query and 0 the output accumulator
@@ -1234,6 +1235,7 @@ instantiate_fast_inference_self_attention_kernel(half, half, 16, 16, 256, 2, 2);
       const constant int& gqa_factor,                                        \
       const constant int& N,                                                 \
       const constant size_t& k_stride,                                       \
+      const constant size_t& v_stride,                                       \
       const constant float& scale,                                           \
       const constant float& softcapping,                                     \
       uint3 tid [[threadgroup_position_in_grid]],                            \
diff --git a/candle-nn/src/ops.rs b/candle-nn/src/ops.rs
index b37c778c88..5e5d83a467 100644
--- a/candle-nn/src/ops.rs
+++ b/candle-nn/src/ops.rs
@@ -1094,6 +1094,7 @@ impl candle::CustomOp3 for Sdpa {
                 k_l.stride(),
                 k.buffer(),
                 v_l.start_offset(),
+                v_l.stride(),
                 v.buffer(),
                 &output,
                 self.scale,