diff --git a/ggml/src/ggml-metal/ggml-metal-context.m b/ggml/src/ggml-metal/ggml-metal-context.m
index b45e72093600..41b6b776bdef 100644
--- a/ggml/src/ggml-metal/ggml-metal-context.m
+++ b/ggml/src/ggml-metal/ggml-metal-context.m
@@ -79,6 +79,10 @@
     // error state - set when a command buffer fails during synchronize
     // once set, graph_compute will return GGML_STATUS_FAILED until the backend is recreated
     bool has_error;
+
+    // lookups that found no buffer while THIS context encoded its current graph (counted by the
+    // encode blocks through ggml_metal_nil_sink_set; read once every block has finished)
+    uint64_t nil_lookups;
 };
 
 ggml_metal_t ggml_metal_init(ggml_metal_device_t dev) {
@@ -441,6 +445,10 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph *
         return GGML_STATUS_FAILED;
     }
 
+    // a lookup that finds no buffer during this graph's encode means some op ran on the wrong
+    // memory: the graph is reported failed, never as a success computed on stale bytes
+    __atomic_store_n(&ctx->nil_lookups, 0, __ATOMIC_RELAXED);
+
     // number of nodes encoded by the main thread (empirically determined)
     const int n_main = MAX(64, 0.1*gf->n_nodes);
 
@@ -611,6 +619,12 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph *
         }
     }
 
+    if (__atomic_load_n(&ctx->nil_lookups, __ATOMIC_RELAXED) != 0) {
+        GGML_LOG_ERROR("%s: %llu tensor lookup(s) found no buffer while encoding this graph: its result is not trusted\n",
+                __func__, (unsigned long long) __atomic_load_n(&ctx->nil_lookups, __ATOMIC_RELAXED));
+        return GGML_STATUS_FAILED;
+    }
+
     return GGML_STATUS_SUCCESS;
 }
 
@@ -704,6 +718,7 @@ void ggml_metal_set_n_cb(ggml_metal_t ctx, int n_cb) {
             ctx->debug_graph,
             ctx->debug_fusion);
 
+        ggml_metal_nil_sink_set(&ctx->nil_lookups); // this block's lookups count against this graph
         for (int idx = 0; idx < ggml_metal_op_n_nodes(ctx_op); ++idx) {
             const int res = ggml_metal_op_encode(ctx_op, idx);
             if (res == 0) {
@@ -712,6 +727,7 @@ void ggml_metal_set_n_cb(ggml_metal_t ctx, int n_cb) {
 
             idx += res - 1;
         }
+        ggml_metal_nil_sink_set(NULL);
 
         ggml_metal_op_free(ctx_op);
 
diff --git a/ggml/src/ggml-metal/ggml-metal-device.h b/ggml/src/ggml-metal/ggml-metal-device.h
index 51f563fa2020..d4ed162acbbf 100644
--- a/ggml/src/ggml-metal/ggml-metal-device.h
+++ b/ggml/src/ggml-metal/ggml-metal-device.h
@@ -346,6 +346,9 @@ void   ggml_metal_buffer_clear        (ggml_metal_buffer_t buf, uint8_t value);
 // Metal buffer based on the host memory pointer
 //
 struct ggml_metal_buffer_id ggml_metal_buffer_get_id(ggml_metal_buffer_t buf, const struct ggml_tensor * t);
+// where this thread's lookups that find no buffer are counted (the graph compute it encodes
+// for; NULL: not counted). See ggml_metal_buffer_get_id.
+void ggml_metal_nil_sink_set(uint64_t * sink);
 
 // [MOE-GATHER #23] GPU virtual address of a host pointer inside this Metal buffer (MTLBuffer.gpuAddress
 // + intra-buffer delta), or 0 when the pointer is not covered / the OS lacks gpuAddress. Cross-buffer
diff --git a/ggml/src/ggml-metal/ggml-metal-device.m b/ggml/src/ggml-metal/ggml-metal-device.m
index 82215837c8fa..c916ca8a1657 100644
--- a/ggml/src/ggml-metal/ggml-metal-device.m
+++ b/ggml/src/ggml-metal/ggml-metal-device.m
@@ -2378,6 +2378,17 @@ void ggml_metal_buffer_clear(ggml_metal_buffer_t buf, uint8_t value) {
     }
 }
 
+// Lookups that found no buffer holding a tensor's bytes are counted into the graph compute
+// that is encoding on this thread (ggml_metal_nil_sink_set): such a lookup hands the kernel a
+// nil buffer, the op reads or writes nothing it was meant to, and the graph goes on with stale
+// memory (Metal OUT_PROD read stale scratch in every LoRA backward that way, one log line each).
+// Per compute, never process-wide: a training graph's lookup must not fail a decode beside it.
+static _Thread_local uint64_t * g_ggml_metal_nil_sink = NULL;
+
+void ggml_metal_nil_sink_set(uint64_t * sink) {
+    g_ggml_metal_nil_sink = sink;
+}
+
 struct ggml_metal_buffer_id ggml_metal_buffer_get_id(ggml_metal_buffer_t buf, const struct ggml_tensor * t) {
     struct ggml_metal_buffer_id res = { nil, 0 };
 
@@ -2399,6 +2410,9 @@ struct ggml_metal_buffer_id ggml_metal_buffer_get_id(ggml_metal_buffer_t buf, co
     }
 
     GGML_LOG_ERROR("%s: error: tensor '%s' buffer is nil\n", __func__, t->name);
+    if (g_ggml_metal_nil_sink != NULL) {
+        __atomic_fetch_add(g_ggml_metal_nil_sink, 1, __ATOMIC_RELAXED);
+    }
 
     return res;
 }
diff --git a/ggml/src/ggml-opt.cpp b/ggml/src/ggml-opt.cpp
index cfd2d51cbd64..5220ec5f65b4 100644
--- a/ggml/src/ggml-opt.cpp
+++ b/ggml/src/ggml-opt.cpp
@@ -1090,7 +1090,14 @@ void ggml_opt_eval(ggml_opt_context_t opt_ctx, ggml_opt_result_t result) {
         }
     }
 
-    ggml_backend_sched_graph_compute(opt_ctx->backend_sched, opt_ctx->allocated_graph_copy);
+    const enum ggml_status status = ggml_backend_sched_graph_compute(opt_ctx->backend_sched, opt_ctx->allocated_graph_copy);
+    if (status != GGML_STATUS_SUCCESS) {
+        // the step's gradients (and the optimizer update inside this graph) were computed on
+        // memory the backend says it did not have: the run must stop, never continue on them
+        opt_ctx->refusal = std::string("the backend failed to compute the training graph (") + ggml_status_to_string(status)
+            + "): this step's gradients are not trusted, so the run stopped and nothing was written";
+        GGML_LOG_ERROR("%s: %s\n", __func__, opt_ctx->refusal.c_str());
+    }
     opt_ctx->iter += opt_ctx->allocated_graph == opt_ctx->gb_opt;
     opt_ctx->opt_i = (opt_ctx->opt_i + 1) % opt_ctx->opt_period;
 
diff --git a/src/llama-context.cpp b/src/llama-context.cpp
index e360daac87ca..27a26d0948c9 100644
--- a/src/llama-context.cpp
+++ b/src/llama-context.cpp
@@ -3537,6 +3537,15 @@ void llama_context::opt_epoch_iter(
                 GGML_ASSERT(row == n_outputs);
             }
             ggml_opt_eval(opt_ctx, result);
+            if (const char * why = ggml_opt_refusal(opt_ctx); why[0] != '\0') {
+                // the backend failed the graph (ggml_opt_eval): the run fails, as a refused graph does
+                opt_failure = why;
+                LLAMA_LOG_ERROR("%s: %s: stopping the epoch\n", __func__, why);
+                ggml_free(ctx_compute_opt);
+                opt_alloc_failed.store(true);
+                opt_stop_requested.store(true);
+                return;
+            }
             if (callback) {
                 callback(train, opt_ctx, dataset, result, idata_in_loop + (pos_ctx + pos_batch)/n_ubatch + 1, ndata_in_loop, t_loop_start);
             }