diff --git a/src/infinicore/nn/embedding.cc b/src/infinicore/nn/embedding.cc
index 7b02f93ce..03928177a 100644
--- a/src/infinicore/nn/embedding.cc
+++ b/src/infinicore/nn/embedding.cc
@@ -45,7 +45,7 @@ Embedding::Embedding(size_t num_embeddings,
 Tensor Embedding::forward(const Tensor &indices) const {
     // TODO: Implement on-device embedding for all devices, then remove the condition and the classic approach
     auto device_type = device_.getType();
-    if (device_type == Device::Type::NVIDIA || device_type == Device::Type::ILUVATAR || device_type == Device::Type::METAX || device_type == Device::Type::MOORE || device_type == Device::Type::ALI || device_type == Device::Type::QY) {
+    if (device_type == Device::Type::NVIDIA || device_type == Device::Type::ILUVATAR || device_type == Device::Type::CAMBRICON || device_type == Device::Type::METAX || device_type == Device::Type::MOORE || device_type == Device::Type::ALI || device_type == Device::Type::QY) {
         // Use op::embedding which supports device-side input and batch dimension
         return op::embedding(indices->contiguous()->to(device_), weight_);
     }
diff --git a/src/infiniop/ops/embedding/bang/embedding_bang.h b/src/infiniop/ops/embedding/bang/embedding_bang.h
new file mode 100644
index 000000000..bc665a1a3
--- /dev/null
+++ b/src/infiniop/ops/embedding/bang/embedding_bang.h
@@ -0,0 +1,8 @@
+#ifndef __EMBEDDING_BANG_H__
+#define __EMBEDDING_BANG_H__
+
+#include "../embedding.h"
+
+DESCRIPTOR(bang)
+
+#endif // __EMBEDDING_BANG_H__
diff --git a/src/infiniop/ops/embedding/bang/embedding_bang.mlu b/src/infiniop/ops/embedding/bang/embedding_bang.mlu
new file mode 100644
index 000000000..01ff3812d
--- /dev/null
+++ b/src/infiniop/ops/embedding/bang/embedding_bang.mlu
@@ -0,0 +1,182 @@
+#include "../../../devices/bang/common_bang.h"
+#include "embedding_bang.h"
+
+#include <algorithm>
+
+__nram__ char nram_buffer[NRAM_MAX_SIZE];
+
+template <typename T, typename IndexType>
+__mlu_global__ void embeddingKernel(
+    T *__restrict__ output,
+    const IndexType *__restrict__ indices,
+    const T *__restrict__ weight,
+    size_t num_indices,
+    size_t embedding_dim,
+    size_t vocab_size) {
+    if (num_indices == 0 || embedding_dim == 0) {
+        return;
+    }
+
+    size_t chunk_target = 512;
+    size_t parts_by_dim = (embedding_dim + chunk_target - 1) / chunk_target;
+    size_t max_parts_by_tasks = std::max<size_t>(1, taskDim / num_indices);
+    size_t parts_per_row = std::max<size_t>(1, std::min(parts_by_dim, max_parts_by_tasks));
+    size_t part_size = (embedding_dim + parts_per_row - 1) / parts_per_row;
+    size_t logical_tasks = num_indices * parts_per_row;
+    size_t max_chunk = NRAM_MAX_SIZE / sizeof(T);
+    T *cache = reinterpret_cast<T *>(nram_buffer);
+
+    for (size_t logical = taskId; logical < logical_tasks; logical += taskDim) {
+        size_t row = logical / parts_per_row;
+        size_t part = logical - row * parts_per_row;
+        size_t start = part * part_size;
+        size_t end = std::min(embedding_dim, start + part_size);
+        if (start >= end) {
+            continue;
+        }
+
+        IndexType index_val = indices[row];
+        if (index_val < 0 || static_cast<size_t>(index_val) >= vocab_size) {
+            continue;
+        }
+
+        const T *src = weight + static_cast<size_t>(index_val) * embedding_dim + start;
+        T *dst = output + row * embedding_dim + start;
+        size_t processed = 0;
+        size_t len = end - start;
+        while (processed < len) {
+            size_t current = std::min(max_chunk, len - processed);
+            __memcpy(cache, src + processed, current * sizeof(T), GDRAM2NRAM);
+            __memcpy(dst + processed, cache, current * sizeof(T), NRAM2GDRAM);
+            processed += current;
+        }
+    }
+}
+
+template <typename T, typename IndexType>
+static infiniStatus_t launchEmbedding(
+    int core_per_cluster,
+    int cluster_count,
+    cnrtQueue_t queue,
+    void *output,
+    const void *input,
+    const void *weight,
+    size_t num_indices,
+    size_t embedding_dim,
+    size_t vocab_size) {
+    cnrtDim3_t kernel_dim;
+    kernel_dim.x = core_per_cluster;
+    kernel_dim.y = cluster_count;
+    kernel_dim.z = 1;
+
+    embeddingKernel<T, IndexType><<<kernel_dim, cnrtFuncTypeUnion1, queue>>>(
+        reinterpret_cast<T *>(output),
+        reinterpret_cast<const IndexType *>(input),
+        reinterpret_cast<const T *>(weight),
+        num_indices,
+        embedding_dim,
+        vocab_size);
+    cnrtQueueSync(queue);
+    return INFINI_STATUS_SUCCESS;
+}
+
+namespace op::embedding::bang {
+
+struct Descriptor::Opaque {
+    std::shared_ptr<device::bang::Handle::Internal> internal;
+};
+
+Descriptor::~Descriptor() {
+    delete _opaque;
+}
+
+infiniStatus_t Descriptor::create(
+    infiniopHandle_t handle,
+    Descriptor **desc_ptr,
+    infiniopTensorDescriptor_t output_desc,
+    infiniopTensorDescriptor_t input_desc,
+    infiniopTensorDescriptor_t weight_desc) {
+
+    auto input_shape = input_desc->shape();
+    auto weight_shape = weight_desc->shape();
+
+    CHECK_OR_RETURN(weight_shape.size() == 2, INFINI_STATUS_BAD_TENSOR_SHAPE);
+    CHECK_OR_RETURN(output_desc->shape().size() == input_shape.size() + 1, INFINI_STATUS_BAD_TENSOR_SHAPE);
+
+    auto output_shape = output_desc->shape();
+    size_t embedding_dim = weight_shape[1];
+    CHECK_OR_RETURN(output_shape.back() == embedding_dim, INFINI_STATUS_BAD_TENSOR_SHAPE);
+
+    for (size_t i = 0; i < input_shape.size(); ++i) {
+        CHECK_OR_RETURN(output_shape[i] == input_shape[i], INFINI_STATUS_BAD_TENSOR_SHAPE);
+    }
+
+    auto input_dtype = input_desc->dtype();
+    auto weight_dtype = weight_desc->dtype();
+    CHECK_OR_RETURN(input_dtype == INFINI_DTYPE_I32 || input_dtype == INFINI_DTYPE_I64,
+                    INFINI_STATUS_BAD_TENSOR_DTYPE);
+    CHECK_OR_RETURN(weight_dtype == INFINI_DTYPE_F32 || weight_dtype == INFINI_DTYPE_F16 || weight_dtype == INFINI_DTYPE_BF16,
+                    INFINI_STATUS_BAD_TENSOR_DTYPE);
+    CHECK_OR_RETURN(output_desc->dtype() == weight_dtype, INFINI_STATUS_BAD_TENSOR_DTYPE);
+
+    size_t num_indices = 1;
+    for (auto dim : input_shape) {
+        num_indices *= dim;
+    }
+    size_t vocab_size = weight_shape[0];
+
+    auto handle_bang = reinterpret_cast<device::bang::Handle *>(handle);
+    *desc_ptr = new Descriptor(
+        num_indices,
+        embedding_dim,
+        vocab_size,
+        input_dtype,
+        weight_dtype,
+        new Opaque{handle_bang->internal()},
+        handle->device,
+        handle->device_id);
+    return INFINI_STATUS_SUCCESS;
+}
+
+infiniStatus_t Descriptor::calculate(
+    void *output,
+    const void *input,
+    const void *weight,
+    void *stream) const {
+    if (_num_indices == 0) {
+        return INFINI_STATUS_SUCCESS;
+    }
+
+    auto queue = reinterpret_cast<cnrtQueue_t>(stream);
+    int core_per_cluster = _opaque->internal->getCorePerCluster();
+    int cluster_count = _opaque->internal->getClusterCount();
+
+#define DISPATCH(T, IndexType)                                         \
+    return launchEmbedding<T, IndexType>(                              \
+        core_per_cluster, cluster_count, queue, output, input, weight, \
+        _num_indices, _embedding_dim, _vocab_size)
+
+    if (_input_dtype == INFINI_DTYPE_I32) {
+        if (_weight_dtype == INFINI_DTYPE_F32) {
+            DISPATCH(float, int32_t);
+        } else if (_weight_dtype == INFINI_DTYPE_F16) {
+            DISPATCH(half, int32_t);
+        } else if (_weight_dtype == INFINI_DTYPE_BF16) {
+            DISPATCH(bfloat16_t, int32_t);
+        }
+    } else if (_input_dtype == INFINI_DTYPE_I64) {
+        if (_weight_dtype == INFINI_DTYPE_F32) {
+            DISPATCH(float, int64_t);
+        } else if (_weight_dtype == INFINI_DTYPE_F16) {
+            DISPATCH(half, int64_t);
+        } else if (_weight_dtype == INFINI_DTYPE_BF16) {
+            DISPATCH(bfloat16_t, int64_t);
+        }
+    }
+
+#undef DISPATCH
+
+    return INFINI_STATUS_BAD_TENSOR_DTYPE;
+}
+
+} // namespace op::embedding::bang
diff --git a/src/infiniop/ops/embedding/operator.cc b/src/infiniop/ops/embedding/operator.cc
index 4741945c7..525ced0af 100644
--- a/src/infiniop/ops/embedding/operator.cc
+++ b/src/infiniop/ops/embedding/operator.cc
@@ -2,6 +2,10 @@
 #include "../../handle.h"
 #include "infiniop/ops/embedding.h"
 
+#ifdef ENABLE_CAMBRICON_API
+#include "bang/embedding_bang.h"
+#endif
+
 #ifdef ENABLE_CPU_API
 #include "cpu/embedding_cpu.h"
 #endif
@@ -57,6 +61,9 @@ __INFINI_C infiniStatus_t infiniopCreateEmbeddingDescriptor(
 #ifdef ENABLE_MOORE_API
         CREATE(INFINI_DEVICE_MOORE, moore);
 #endif
+#ifdef ENABLE_CAMBRICON_API
+        CREATE(INFINI_DEVICE_CAMBRICON, bang);
+#endif
 
     default:
         return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;
@@ -103,6 +110,9 @@ __INFINI_C infiniStatus_t infiniopEmbedding(
 #ifdef ENABLE_MOORE_API
         CALCULATE(INFINI_DEVICE_MOORE, moore);
 #endif
+#ifdef ENABLE_CAMBRICON_API
+        CALCULATE(INFINI_DEVICE_CAMBRICON, bang);
+#endif
 
     default:
         return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;
@@ -143,6 +153,9 @@ __INFINI_C infiniStatus_t infiniopDestroyEmbeddingDescriptor(infiniopEmbeddingDe
 #ifdef ENABLE_MOORE_API
         DESTROY(INFINI_DEVICE_MOORE, moore);
 #endif
+#ifdef ENABLE_CAMBRICON_API
+        DESTROY(INFINI_DEVICE_CAMBRICON, bang);
+#endif
 
     default:
         return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;