diff --git a/unsloth/kernels/cross_entropy_loss.py b/unsloth/kernels/cross_entropy_loss.py
index e0af458a96..d3b618582e 100644
--- a/unsloth/kernels/cross_entropy_loss.py
+++ b/unsloth/kernels/cross_entropy_loss.py
@@ -300,6 +300,7 @@ class Fast_CrossEntropyLoss(torch.autograd.Function):
         if n_chunks == 1:
             # For small vocabs <= 65336 like Llama, Mistral
             BLOCK_SIZE, num_warps = calculate_settings(vocab_size)
+            if is_cdna(): num_warps = num_warps // 2
             logsumexp = torch.empty(n_rows, dtype = torch.float32, device = device)
 
             with torch_gpu_device(device):
diff --git a/unsloth/models/mistral.py b/unsloth/models/mistral.py
index b547739df2..faab2d30b1 100644
--- a/unsloth/models/mistral.py
+++ b/unsloth/models/mistral.py
@@ -298,12 +298,7 @@ def MistralForCausalLM_fast_forward(
     else:
         RETURN_LOGITS = os.environ.get("UNSLOTH_RETURN_LOGITS", "0") == "1"
         # < 1024 Normal Unsloth uses less VRAM!
-        if DEVICE_TYPE == "hip":
-            # [TODO] AMD GPUs fail on chunked_cross_entropy loss!
-            # RuntimeError: Triton Error [HIP]:  Code: 1, Messsage: invalid argument
-            RETURN_LOGITS = False
-        elif bsz*q_len <= 1024:
-            RETURN_LOGITS = True
+        if bsz * q_len <= 1024: RETURN_LOGITS = True
 
         if not RETURN_LOGITS and labels is not None:
             n_items = kwargs.get("num_items_in_batch", None) or kwargs.get("n_items", None)