diff --git a/candle-core/src/cuda_backend.rs b/candle-core/src/cuda_backend.rs
index f0f03053..97dc346e 100644
--- a/candle-core/src/cuda_backend.rs
+++ b/candle-core/src/cuda_backend.rs
@@ -1651,9 +1651,11 @@ fn gemm_config<T>(
     let lhs_m1 = lhs_stride[lhs_stride.len() - 1];
     let lhs_m2 = lhs_stride[lhs_stride.len() - 2];
     // The a tensor has dims batching, k, n (rhs)
-    let (lda, transa) = if rhs_m1 == 1 && rhs_m2 == n {
+    // We also allow for the case where the stride on the minor dimension is not as expected but
+    // there is a single element.
+    let (lda, transa) = if rhs_m1 == 1 && (rhs_m2 == n || b * k == 1) {
         (n as i32, cublasOperation_t::CUBLAS_OP_N)
-    } else if rhs_m1 == k && rhs_m2 == 1 {
+    } else if (rhs_m1 == k || b * n == 1) && rhs_m2 == 1 {
         (k as i32, cublasOperation_t::CUBLAS_OP_T)
     } else {
         Err(CudaError::MatMulNonContiguous {
@@ -1663,9 +1665,11 @@ fn gemm_config<T>(
         })?
     };
     // The b tensor has dims batching, m, k (lhs)
-    let (ldb, transb) = if lhs_m1 == 1 && lhs_m2 == k {
+    // We also allow for the case where the stride on the minor dimension is not as expected but
+    // there is a single element.
+    let (ldb, transb) = if lhs_m1 == 1 && (lhs_m2 == k || b * m == 1) {
         (k as i32, cublasOperation_t::CUBLAS_OP_N)
-    } else if lhs_m1 == m && lhs_m2 == 1 {
+    } else if (lhs_m1 == m || b * k == 1) && lhs_m2 == 1 {
         (m as i32, cublasOperation_t::CUBLAS_OP_T)
     } else {
         Err(CudaError::MatMulNonContiguous {
diff --git a/candle-core/src/tensor.rs b/candle-core/src/tensor.rs
index 92c931eb..b53b0419 100644
--- a/candle-core/src/tensor.rs
+++ b/candle-core/src/tensor.rs
@@ -2007,6 +2007,16 @@ impl Tensor {
         }
     }
 
+    /// Returns a tensor that is in row major order. This always makes a copy.
+    pub fn force_contiguous(&self) -> Result<Tensor> {
+        let shape = self.shape();
+        let mut storage = unsafe { self.device().alloc_uninit(shape, self.dtype())? };
+        self.storage()
+            .copy_strided_src(&mut storage, 0, self.layout())?;
+        let op = BackpropOp::new1(self, Op::Copy);
+        Ok(from_storage(storage, shape.clone(), op, false))
+    }
+
     /// Create a variable based on the values currently stored in a tensor. The storage is always
     /// copied.
     pub(crate) fn make_var(&self) -> Result<Tensor> {
diff --git a/candle-core/tests/tensor_tests.rs b/candle-core/tests/tensor_tests.rs
index b2475adc..af28c1c1 100644
--- a/candle-core/tests/tensor_tests.rs
+++ b/candle-core/tests/tensor_tests.rs
@@ -1135,6 +1135,30 @@ fn randn(device: &Device) -> Result<()> {
     Ok(())
 }
 
+// https://github.com/huggingface/candle/issues/1948
+fn squeeze_mm(device: &Device) -> Result<()> {
+    let seq_len = 8_usize;
+    let a = Tensor::zeros((1, seq_len, 16), DType::F32, device)?;
+    let x = a.i((.., seq_len - 1, ..))?;
+    println!(
+        "x shape:{:?}, stride:{:?}, is_contiguous:{}",
+        x.shape(),
+        x.stride(),
+        x.is_contiguous()
+    );
+
+    let w = Tensor::zeros((32, 16), DType::F32, device)?.t()?;
+    println!(
+        "w shape:{:?}, stride:{:?}, is_contiguous:{}",
+        w.shape(),
+        w.stride(),
+        w.is_contiguous()
+    );
+    let x = x.matmul(&w)?;
+    assert_eq!(x.dims(), &[1, 32]);
+    Ok(())
+}
+
 test_device!(zeros, zeros_cpu, zeros_gpu, zeros_metal);
 test_device!(ones, ones_cpu, ones_gpu, ones_metal);
 test_device!(full, full_cpu, full_gpu, full_metal);
@@ -1190,6 +1214,7 @@ test_device!(
 test_device!(randn, randn_cpu, randn_gpu, randn_metal);
 test_device!(clamp, clamp_cpu, clamp_gpu, clamp_metal);
 test_device!(var, var_cpu, var_gpu, var_metal);
+test_device!(squeeze_mm, squeeze_mm_cpu, squeeze_mm_gpu, squeeze_mm_metal);
 
 // There was originally a bug on the CPU implementation for randn
 // https://github.com/huggingface/candle/issues/381
diff --git a/candle-metal-kernels/src/lib.rs b/candle-metal-kernels/src/lib.rs
index 449bef8f..3f452331 100644
--- a/candle-metal-kernels/src/lib.rs
+++ b/candle-metal-kernels/src/lib.rs
@@ -1451,9 +1451,12 @@ pub fn call_gemm(
     let rhs_m2 = rhs_stride[rhs_stride.len() - 2];
     let lhs_m1 = lhs_stride[lhs_stride.len() - 1];
     let lhs_m2 = lhs_stride[lhs_stride.len() - 2];
-    let a_trans = if lhs_m1 == 1 && lhs_m2 == k {
+    // lhs has shape b, m, k
+    // We also allow for the case where the stride on the minor dimension is not as expected but
+    // there is a single element.
+    let a_trans = if lhs_m1 == 1 && (lhs_m2 == k || b * m == 1) {
         false
-    } else if lhs_m1 == m && lhs_m2 == 1 {
+    } else if (lhs_m1 == m || b * k == 1) && lhs_m2 == 1 {
         true
     } else {
         return Err(MetalKernelError::MatMulNonContiguous {
@@ -1462,9 +1465,10 @@ pub fn call_gemm(
             mnk: (m, n, k),
         })?;
     };
-    let b_trans = if rhs_m1 == 1 && rhs_m2 == n {
+    // rhs has shape b, k, n
+    let b_trans = if rhs_m1 == 1 && (rhs_m2 == n || b * k == 1) {
         false
-    } else if rhs_m1 == k && rhs_m2 == 1 {
+    } else if (rhs_m1 == k || b * n == 1) && rhs_m2 == 1 {
         true
     } else {
         return Err(MetalKernelError::MatMulNonContiguous {