diff --git a/Dockerfile_intel b/Dockerfile_intel
index 5bf7632c..b015760c 100644
--- a/Dockerfile_intel
+++ b/Dockerfile_intel
@@ -119,7 +119,9 @@ ENV CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0
 ENV TORCH_DEVICE_BACKEND_AUTOLOAD=0
 
 RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/oneccl_bind_pt-2.6.0%2Bxpu-cp311-cp311-linux_x86_64.whl
-RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/intel_extension_for_pytorch-2.6.10%2Bxpu-cp311-cp311-linux_x86_64.whl
+RUN git clone https://github.com/intel/intel-extension-for-pytorch && cd intel-extension-for-pytorch && git checkout d5a7036316a01ea8220eb4da78a2207c423a1166
+RUN sed -i 's/VERSION_MINOR 7/VERSION_MINOR 6/' intel-extension-for-pytorch/version.txt
+RUN cd intel-extension-for-pytorch && git submodule update --init --recursive && USE_AOT_DEVLIST='pvc,ats-m150' BUILD_SEPARATE_OPS=OFF BUILD_WITH_CPU=OFF USE_XETLA=ON python setup.py install && rm -rf /usr/src/intel-extension-for-pytorch
 # Install benchmarker
 COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark
 # Install router
diff --git a/server/text_generation_server/layers/attention/ipex.py b/server/text_generation_server/layers/attention/ipex.py
index 2b89060e..0b44072c 100644
--- a/server/text_generation_server/layers/attention/ipex.py
+++ b/server/text_generation_server/layers/attention/ipex.py
@@ -45,6 +45,8 @@ def attention(
             causal,
             block_tables,
             None,
+            k_scale=kv_scales.key_scale_cpu,
+            v_scale=kv_scales.value_scale_cpu,
         )
     else:
         ipex.llm.functional.varlen_attention(
@@ -99,6 +101,8 @@ def paged_attention(
             True,
             block_tables,
             None,
+            k_scale=kv_scales.key_scale_cpu,
+            v_scale=kv_scales.value_scale_cpu,
         )
     else:
         input_lengths = seqlen.input_lengths + seqlen.cache_lengths
@@ -114,6 +118,8 @@ def paged_attention(
             BLOCK_SIZE,
             max_s,
             None,
+            k_scale=kv_scales.key_scale_cpu,
+            v_scale=kv_scales.value_scale_cpu,
         )
     return out
 
diff --git a/server/text_generation_server/layers/attention/kv_cache.py b/server/text_generation_server/layers/attention/kv_cache.py
index aaf4d2b2..7082d3ae 100644
--- a/server/text_generation_server/layers/attention/kv_cache.py
+++ b/server/text_generation_server/layers/attention/kv_cache.py
@@ -68,15 +68,20 @@ class KVCache:
         if dtype in {torch.float8_e5m2, torch.float8_e4m3fn}:
             if not (
                 (ATTENTION == "flashinfer" and SYSTEM == "cuda")
-                or (ATTENTION == "paged" and SYSTEM in ("cuda", "rocm"))
+                or (ATTENTION == "paged" and SYSTEM in ("cuda", "rocm", "ipex"))
+                or (ATTENTION == "flashdecoding-ipex")
             ):
                 raise ValueError(
-                    "FP8 KV cache is currently only supported for flashinfer on CUDA and paged attention on CUDA and ROCm. "
+                    "FP8 KV cache is currently only supported for flashinfer on CUDA and paged attention on CUDA, ROCm and INTEL IPEX and flashdecoding in Intel IPEX "
                 )
             if SYSTEM == "rocm" and dtype == torch.float8_e5m2:
                 raise ValueError(
                     "float8_e5m2 FP8 KV cache is not supported on AMD ROCm"
                 )
+            if device.type == "cpu" and dtype == torch.float8_e4m3fn:
+                raise ValueError(
+                    "float8_e4m3fn FP8 KV cache is not supported on Intel IPEX CPU"
+                )
 
         element_size = torch.tensor([], dtype=dtype).element_size()
         if SYSTEM == "ipex" and device.type == "xpu":
@@ -133,7 +138,8 @@ class KVCache:
             return False
         elif self.dtype == torch.float8_e4m3fn and (
             (ATTENTION in ("paged", "flashinfer") and SYSTEM == "cuda")
-            or (ATTENTION == "paged" and SYSTEM == "rocm")
+            or (ATTENTION == "paged" and SYSTEM in ["rocm", "ipex"])
+            or (ATTENTION == "flashdecoding-ipex")
         ):
             log_once(logger.info, "Using FP8 KV cache scales")
             return True
@@ -141,7 +147,7 @@ class KVCache:
             # We have scales, but not the correct FP8 cache type, so warn once.
             log_once(
                 logger.info,
-                "Ignoring FP8 KV cache scales, supported only for float8_e4m3fn KV cache with flashinfer on CUDA and paged attention on ROCm",
+                "Ignoring FP8 KV cache scales, supported only for float8_e4m3fn KV cache with flashinfer on CUDA and paged attention on ROCm/IPEX and flashdecoding on IPEX",
             )
             return False
 
@@ -208,7 +214,13 @@ class KVCache:
             import intel_extension_for_pytorch as ipex
 
             ipex.llm.modules.PagedAttention.reshape_and_cache_flash(
-                key, value, key_cache, value_cache, slots
+                key,
+                value,
+                key_cache,
+                value_cache,
+                slots,
+                k_scale=kv_scales.key_scale_cpu,
+                v_scale=kv_scales.value_scale_cpu,
             )
         else:
             paged_reshape_and_cache(
@@ -268,7 +280,7 @@ def paged_reshape_and_cache(
         import intel_extension_for_pytorch as ipex
 
         ipex.llm.modules.PagedAttention.reshape_and_cache(
-            key, value, key_cache, value_cache, slots
+            key, value, key_cache, value_cache, slots, k_scale=k_scale, v_scale=v_scale
         )
     else:
         raise NotImplementedError(