diff --git a/models/demos/llama3/tt/llama_mlp.py b/models/demos/llama3/tt/llama_mlp.py
index 4ea55b8865b..664b080e92c 100644
--- a/models/demos/llama3/tt/llama_mlp.py
+++ b/models/demos/llama3/tt/llama_mlp.py
@@ -90,6 +90,8 @@ def forward(self, x: ttnn.Tensor, mode) -> ttnn.Tensor:
 
         # In decode mode (seqlen <= 32) do DRAM sharded matmuls
         # These use HiFi2; this drops 1 bit of the activations but would be FLOP-bound on 12 cores with HiFi4
+        out_memory_config = x.memory_config()
+        out_memory_config.shard_spec = None
         w1_out = ttnn.linear(
             x,
             self.w1,
@@ -101,7 +103,7 @@ def forward(self, x: ttnn.Tensor, mode) -> ttnn.Tensor:
             core_grid=None,  # FIXME: validate on TG ttnn.CoreGrid(y=8, x=8) if not pc_1 else None,
             dtype=ttnn.bfloat8_b if TG else ttnn.bfloat16,
             program_config=pc_1,
-            memory_config=x.memory_config(),
+            memory_config=out_memory_config,
         )
 
         w3_out = ttnn.linear(
@@ -115,7 +117,7 @@ def forward(self, x: ttnn.Tensor, mode) -> ttnn.Tensor:
             core_grid=None,  # FIXME: validate on TG ttnn.CoreGrid(y=8, x=8) if not pc_3 else None,
             dtype=ttnn.bfloat16,
             program_config=pc_3,
-            memory_config=x.memory_config(),
+            memory_config=out_memory_config,
         )
         ttnn.deallocate(x)
 
@@ -192,6 +194,8 @@ def forward(self, x: ttnn.Tensor, mode) -> ttnn.Tensor:
             if mode == "decode":
                 w2_in = ttnn.to_memory_config(w2_in, ttnn.L1_MEMORY_CONFIG)
 
+        w2_out_memory_config = w2_in.memory_config()
+        w2_out_memory_config.shard_spec = None
         w2_out = ttnn.linear(
             w2_in,
             self.w2,
@@ -201,7 +205,7 @@ def forward(self, x: ttnn.Tensor, mode) -> ttnn.Tensor:
             memory_config=(
                 (ttnn.L1_WIDTH_SHARDED_MEMORY_CONFIG if mode == "decode" else ttnn.DRAM_MEMORY_CONFIG)
                 if TG
-                else w2_in.memory_config()
+                else w2_out_memory_config
             ),
             core_grid=None,  # FIXME: validate on TG ttnn.CoreGrid(y=8, x=8) if not pc_2 else None,
         )
diff --git a/tests/ttnn/unit_tests/operations/test_experimental.py b/tests/ttnn/unit_tests/operations/test_experimental.py
index a8e76c120fa..f30ea9f01bf 100644
--- a/tests/ttnn/unit_tests/operations/test_experimental.py
+++ b/tests/ttnn/unit_tests/operations/test_experimental.py
@@ -169,6 +169,11 @@ def test_ttnn_matmul_dram_sharded(device, m_size, k_size, n_size):
     shard_shape = (32, 1024)
     shard_spec = ttnn.ShardSpec(shard_grid, shard_shape, ttnn.ShardOrientation.ROW_MAJOR)
     sharded_mem_config = ttnn.MemoryConfig(ttnn.TensorMemoryLayout.WIDTH_SHARDED, ttnn.BufferType.L1, shard_spec)
+    out_shard_shape = (32, 128)
+    out_shard_spec = ttnn.ShardSpec(shard_grid, out_shard_shape, ttnn.ShardOrientation.ROW_MAJOR)
+    out_sharded_mem_config = ttnn.MemoryConfig(
+        ttnn.TensorMemoryLayout.WIDTH_SHARDED, ttnn.BufferType.L1, out_shard_spec
+    )
     input_tensor_in0 = ttnn.to_memory_config(input_tensor_in0, sharded_mem_config)
 
     # in1 shard config
@@ -203,7 +208,7 @@ def test_ttnn_matmul_dram_sharded(device, m_size, k_size, n_size):
         input_tensor_in0,
         input_tensor_in1,
         program_config=program_config,
-        memory_config=sharded_mem_config,
+        memory_config=out_sharded_mem_config,
         dtype=ttnn.bfloat16,
         compute_kernel_config=compute_kernel_config,
     )
diff --git a/tests/ttnn/unit_tests/operations/test_matmul.py b/tests/ttnn/unit_tests/operations/test_matmul.py
index 1bb4cb64bf6..cc775e2ec53 100644
--- a/tests/ttnn/unit_tests/operations/test_matmul.py
+++ b/tests/ttnn/unit_tests/operations/test_matmul.py
@@ -2089,7 +2089,7 @@ def test_interleaved_input_sharded_output_matmul(device):
 
     out_mem_config = ttnn.create_sharded_memory_config(
         shape=(32, 256),
-        core_grid=ttnn.CoreGrid(x=1, y=8),
+        core_grid=ttnn.CoreGrid(x=8, y=1),
         strategy=ttnn.ShardStrategy.WIDTH,
         orientation=ttnn.ShardOrientation.ROW_MAJOR,
     )
@@ -2100,8 +2100,8 @@ def test_interleaved_input_sharded_output_matmul(device):
 
     # Block sharded
     out_mem_config = ttnn.create_sharded_memory_config(
-        shape=(32, 256),
-        core_grid=ttnn.CoreGrid(x=1, y=8),
+        shape=(256, 256),
+        core_grid=ttnn.CoreGrid(x=1, y=1),
         strategy=ttnn.ShardStrategy.BLOCK,
         orientation=ttnn.ShardOrientation.ROW_MAJOR,
     )
diff --git a/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp b/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp
index 3d72eb55267..f86614e667f 100644
--- a/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp
+++ b/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp
@@ -1426,10 +1426,10 @@ void Matmul::validate(
 
     TT_FATAL(optional_input_tensors.size() == 1, "Error");
 
+    const auto output_tensor_spec = this->compute_output_specs(input_tensors, {}, optional_input_tensors).at(0);
     if (is_optional_output_tensor) {
         const auto& optional_output_tensor_c = optional_output_tensors.at(0);
         const auto& optional_output_tensor_shape = optional_output_tensor_c->get_logical_shape();
-        const auto output_tensor_spec = this->compute_output_specs(input_tensors, {}, optional_input_tensors).at(0);
         TT_FATAL(
             optional_output_tensor_shape == output_tensor_spec.logical_shape(),
             "Shape of Optional Output Tensor {} doesnt match Output Tensor {}",
@@ -1446,6 +1446,23 @@ void Matmul::validate(
             "tensor {}",
             optional_output_tensor_c->memory_config(),
             this->output_mem_config);
+    } else {
+        TT_FATAL(
+            output_tensor_spec.memory_config().memory_layout == this->output_mem_config.memory_layout,
+            "Mismatch between computed {} and provided {} mem config memory layout",
+            output_tensor_spec.memory_config().memory_layout,
+            this->output_mem_config.memory_layout);
+        TT_FATAL(
+            output_tensor_spec.memory_config().buffer_type == this->output_mem_config.buffer_type,
+            "Mismatch between computed {} and provided {} mem config buffer type",
+            output_tensor_spec.memory_config().buffer_type,
+            this->output_mem_config.buffer_type);
+        // Needs to be an assert, there are too many existing models not specifying shard spec correctly.
+        TT_ASSERT(
+            output_tensor_spec.memory_config() == this->output_mem_config,
+            "Mismatch between computed {} and provided {} mem config",
+            output_tensor_spec.memory_config(),
+            this->output_mem_config);
     }
 
     TT_FATAL(this->bcast_batch.has_value(), "Error: bcast_batch field should have been automatically populated");
diff --git a/ttnn/cpp/ttnn/operations/matmul/matmul_pybind.cpp b/ttnn/cpp/ttnn/operations/matmul/matmul_pybind.cpp
index 5dff12923c7..d729a5f5247 100644
--- a/ttnn/cpp/ttnn/operations/matmul/matmul_pybind.cpp
+++ b/ttnn/cpp/ttnn/operations/matmul/matmul_pybind.cpp
@@ -270,6 +270,7 @@ void py_module(py::module& module) {
         - Note: there are various additional constraints related to specific program
           configs chosen. Please look at the error messages carefully and fix
           problems appropriately.
+        - Note: if memory_config is provided, it will be compared to what matmul wants to use. The shard spec can be set to None to not compare it.
         - Note: If optional output tensor is specified, then dtype and memory config need to be checked as follows:
           - if they are default then they should be set based on optional output tensor
           - if the are not default then they should be compared and if there is a difference an error is reported