diff --git a/unsloth/_gpu_init.py b/unsloth/_gpu_init.py
index e6178e60f..984057e9f 100644
--- a/unsloth/_gpu_init.py
+++ b/unsloth/_gpu_init.py
@@ -26,6 +26,7 @@ already_imported = [mod for mod in critical_modules if mod in sys.modules]
 # Fix some issues before importing other packages
 from .import_fixes import (
     fix_message_factory_issue,
+    fix_torch_check_is_size,
     check_fbgemm_gpu_version,
     disable_broken_causal_conv1d,
     disable_broken_vllm,
@@ -72,6 +73,7 @@ fix_bitsandbytes_rocm_arch_detection()
 disable_broken_causal_conv1d()
 disable_broken_vllm()
 fix_message_factory_issue()
+fix_torch_check_is_size()
 check_fbgemm_gpu_version()
 torchvision_compatibility_check()
 fix_diffusers_warnings()
@@ -81,6 +83,7 @@ del fix_bitsandbytes_rocm_arch_detection
 del disable_broken_causal_conv1d
 del disable_broken_vllm
 del fix_message_factory_issue
+del fix_torch_check_is_size
 del check_fbgemm_gpu_version
 del torchvision_compatibility_check
 del fix_diffusers_warnings
diff --git a/unsloth/import_fixes.py b/unsloth/import_fixes.py
index c5300ed4d..09de248c7 100644
--- a/unsloth/import_fixes.py
+++ b/unsloth/import_fixes.py
@@ -172,6 +172,10 @@ if not UNSLOTH_ENABLE_LOGGING:
     # Deprecation warnings from torchao
     warnings.filterwarnings("ignore", message = "`int4_weight_only` is deprecated")
     warnings.filterwarnings("ignore", message = "`int8_weight_only` is deprecated")
+    # torch._check_is_size FutureWarning (called by bitsandbytes 4-bit dequant)
+    warnings.filterwarnings(
+        "ignore", message = r"_check_is_size will be removed", category = FutureWarning
+    )
 
     # TorchAO deprecated import paths (https://github.com/pytorch/ao/issues/2752)
     warnings.filterwarnings(
@@ -253,6 +257,30 @@ if not UNSLOTH_ENABLE_LOGGING:
     )
 
 
+def fix_torch_check_is_size():
+    """Shim torch._check_is_size if a future torch removes it (bitsandbytes 4-bit
+    dequant calls it). The FutureWarning is silenced in suppress_cuda_printf."""
+    try:
+        import torch
+
+        if hasattr(torch, "_check_is_size"):
+            return
+
+        def _check_is_size(
+            i,
+            message = None,
+            *,
+            max = None,
+        ):
+            torch._check(i >= 0, message)
+            if max is not None:
+                torch._check(i <= max, message)
+
+        torch._check_is_size = _check_is_size
+    except Exception:
+        return
+
+
 # Fix up AttributeError: 'MessageFactory' object has no attribute 'GetPrototype'
 # MUST do this at the start primarily due to tensorflow causing issues
 def fix_message_factory_issue():