diff --git a/studio/backend/core/training/worker.py b/studio/backend/core/training/worker.py
index ad421b8101..adb78c4704 100644
--- a/studio/backend/core/training/worker.py
+++ b/studio/backend/core/training/worker.py
@@ -2277,20 +2277,23 @@ def run_training_process(
     # Non-fatal: silently skipped if torch is not importable.
     if _hw.IS_ROCM:
         try:
+            import re as _re
             import torch as _torch_mem
-            import psutil as _psutil
 
             if _torch_mem.cuda.is_available():
-                _vram_total = _torch_mem.cuda.get_device_properties(0).total_memory
-                _ram_total = _psutil.virtual_memory().total
-                _is_unified = _vram_total > (_ram_total * 0.5)
+                # iGPUs (gfx1150/gfx1151 Strix Halo, Strix Point, etc.) report
+                # names ending in a digit+M suffix ("AMD Radeon 890M").
+                # Discrete cards use "RX NNNN [XT|XTX]" — no trailing M.
+                _dev_name = _torch_mem.cuda.get_device_properties(0).name
+                _is_unified = bool(_re.search(r'\d[Mm]\b', _dev_name))
                 _mem_fraction = 0.80 if _is_unified else 0.90
                 _torch_mem.cuda.set_per_process_memory_fraction(_mem_fraction)
                 logger.info(
                     "ROCm OOM guard: set_per_process_memory_fraction(%.2f) — "
-                    "%s memory host",
+                    "%s memory host (%s)",
                     _mem_fraction,
                     "unified" if _is_unified else "discrete",
+                    _dev_name,
                 )
         except Exception as _oom_guard_err:
             logger.debug("Could not set GPU memory fraction: %s", _oom_guard_err)