fix(metal): correct Q4_0 contiguous kernel nibble extraction

- Extract all 8 nibbles per uint32_t with proper bit shifts
- Use il-based offset for uint32_t selection (qs[il/8] and qs[il/8+2])
- Apply bias correction once per block instead of 4x accumulated

ggml/src/ggml-metal/ggml-metal-common.cpp

@@ -394,20 +394,30 @@ void ggml_graph_optimize(ggml_cgraph * gf) {
         // fuse only ops that start with these operations
         // can be expanded when needed
         if (node.op() == GGML_OP_ADD ||
+            node.op() == GGML_OP_SUB ||
+            node.op() == GGML_OP_MUL ||
+            node.op() == GGML_OP_DIV ||
             node.op() == GGML_OP_NORM ||
             node.op() == GGML_OP_RMS_NORM) {
             ops[0] = node.op();
 
             int f = i + 1;
             while (f < n && f < i + MAX_FUSE) {
-                // conservatively allow fusing only these ops
+                // bin ops (ADD/SUB/MUL/DIV) must be same type to fuse
-                // can be expanded when needed
+                // NORM/RMS_NORM can chain with MUL/ADD
+                if (node.op() == GGML_OP_ADD ||
+                    node.op() == GGML_OP_SUB ||
+                    node.op() == GGML_OP_MUL ||
+                    node.op() == GGML_OP_DIV) {
+                    if (gf->nodes[f]->op != node.op()) break;
+                } else {
                     if (gf->nodes[f]->op != GGML_OP_ADD &&
                         gf->nodes[f]->op != GGML_OP_MUL &&
                         gf->nodes[f]->op != GGML_OP_NORM &&
                         gf->nodes[f]->op != GGML_OP_RMS_NORM) {
                         break;
                     }
+                }
                 ops[f - i] = gf->nodes[f]->op;
                 f++;
             }

ggml/src/ggml-metal/ggml-metal-device.cpp

@@ -732,6 +732,7 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv(ggml_meta
     int nr1 = 1; // number of src1 rows per threadgroup
 
     size_t smem = 0; // shared memory
+    bool contig = false;
 
     const ggml_type tsrc0 = op->src[0]->type;
     const ggml_type tsrc1 = op->src[1]->type;
@@ -766,6 +767,7 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv(ggml_meta
             {
                 nsg = N_SG_Q4_0;
                 nr0 = N_R0_Q4_0;
+                contig = ne00 >= 256;
             } break;
         case GGML_TYPE_Q4_1:
             {
@@ -877,7 +879,7 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_mul_mv(ggml_meta
             }
     };
 
-    snprintf(base, 256, "kernel_mul_mv_%s_%s%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1), suffix);
+    snprintf(base, 256, "kernel_mul_mv_%s_%s%s%s", ggml_type_name(tsrc0), ggml_type_name(tsrc1), contig ? "_c" : "", suffix);
     snprintf(name, 256, "%s_nsg=%d", base, nsg);
 
     ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name);

ggml/src/ggml-metal/ggml-metal-ops.cpp

@@ -3118,19 +3118,15 @@ int ggml_metal_op_bin(ggml_metal_op_t ctx, int idx) {
 
     int n_fuse = 1;
 
-    // c[0] = add(a,    b[0])
+    // c[0] = op(a,     b[0])
-    // c[1] = add(c[0], b[1])
+    // c[1] = op(c[0],  b[1])
-    // c[2] = add(c[1], b[2])
+    // c[2] = op(c[1],  b[2])
     // ...
     if (use_fusion) {
-        fops[0] = GGML_OP_ADD;
+        ggml_op cur_op = op->op;
-        fops[1] = GGML_OP_ADD;
+        for (int i = 0; i < 8; ++i) {
-        fops[2] = GGML_OP_ADD;
+            fops[i] = cur_op;
-        fops[3] = GGML_OP_ADD;
+        }
-        fops[4] = GGML_OP_ADD;
-        fops[5] = GGML_OP_ADD;
-        fops[6] = GGML_OP_ADD;
-        fops[7] = GGML_OP_ADD;
 
         // note: in metal, we sometimes encode the graph in parallel so we have to avoid fusing ops
         //       across splits. idx_end indicates the last node in the current split
@@ -3165,7 +3161,7 @@ int ggml_metal_op_bin(ggml_metal_op_t ctx, int idx) {
         ++n_fuse;
 
         if (debug_fusion > 1 && n_fuse > 1) {
-            GGML_LOG_DEBUG("%s: fuse: ADD x %d\n", __func__, n_fuse);
+            GGML_LOG_DEBUG("%s: fuse: %s x %d\n", __func__, ggml_op_name(cur_op), n_fuse);
         }
     }
 

ggml/src/ggml-metal/ggml-metal.metal

@@ -3533,6 +3533,94 @@ kernel void kernel_mul_mv_q4_0_f32(
     mul_vec_q_n_f32_impl<block_q4_0, N_R0_Q4_0, constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
 }
 
+// Q4_0 kernel with contiguous uint32_t weight reads (MLX-style)
+// Each thread reads 4 contiguous uint32_t packs per block instead of
+// 8 strided uint16_t reads, improving memory coalescing on Apple GPUs.
+kernel void kernel_mul_mv_q4_0_f32_c(
+        constant ggml_metal_kargs_mul_mv & args,
+        device const char * src0,
+        device const char * src1,
+        device       char * dst,
+        threadgroup  char * shmem [[threadgroup(0)]],
+        uint3  tgpig[[threadgroup_position_in_grid]],
+        ushort tiisg[[thread_index_in_simdgroup]],
+        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
+    const short NSG = FC_mul_mv_nsg;
+
+    constexpr short NR0 = N_R0_Q4_0;
+    constexpr short NW  = N_SIMDWIDTH;
+
+    const int nb = args.ne00 / QK4_0;
+
+    const int r0 = (tgpig.x * NSG + sgitg) * NR0;
+    const int r1 =  tgpig.y;
+    const int im =  tgpig.z;
+
+    const uint i12 = im % args.ne12;
+    const uint i13 = im / args.ne12;
+
+    const uint64_t offset1 = r1 * args.nb11 + (i12) * args.nb12 + (i13) * args.nb13;
+
+    device const float * y = (device const float *) (src1 + offset1);
+
+    device const block_q4_0 * ax[NR0];
+    FOR_UNROLL (int row = 0; row < NR0; ++row) {
+        const uint64_t offset0 = (r0 + row) * args.nb01 + (i12 / args.r2) * args.nb02 + (i13 / args.r3) * args.nb03;
+        ax[row] = (device const block_q4_0 *) ((device char *) src0 + offset0);
+    }
+
+    float sumf[NR0] = {0.f};
+
+    const short ix  = (tiisg / (NW / 16));
+    const short il  = (tiisg % (NW / 16)) * 8;
+    const int   ib0 = ix;
+
+    const uint q_off = il / 8;
+
+    device const float * yb = y + ib0 * QK4_0 + il;
+
+    for (int ib = ib0; ib < nb; ib += 16) {
+        float sumy = 0.f;
+
+        FOR_UNROLL (short i = 0; i < 8; i += 2) {
+            sumy += yb[i + 0] + yb[i + 1] + yb[i + 16] + yb[i + 17];
+        }
+
+        FOR_UNROLL (short row = 0; row < NR0; row++) {
+            const float d = ax[row][ib].d;
+            device const uint32_t * qs = (device const uint32_t *) (ax[row][ib].qs);
+
+            const uint32_t q0 = qs[q_off];
+            const uint32_t q1 = qs[q_off + 2];
+
+            float acc = 0.f;
+
+            FOR_UNROLL (short i = 0; i < 8; i += 2) {
+                const uint ni = i / 2;
+
+                acc += ((q0 >> (4 * ni)) & 0xF) * yb[i + 0]
+                     + ((q0 >> (4 * (ni + 1))) & 0xF) * yb[i + 1]
+                     + ((q1 >> (4 * ni)) & 0xF) * yb[i + 16]
+                     + ((q1 >> (4 * (ni + 1))) & 0xF) * yb[i + 17];
+            }
+
+            sumf[row] += d * (acc + sumy * -8.f);
+        }
+
+        yb += QK4_0 * 16;
+    }
+
+    device float * dst_f32 = (device float *) dst + im * args.ne0 * args.ne1 + r1 * args.ne0;
+
+    for (int row = 0; row < NR0; ++row) {
+        const float tot = simd_sum(sumf[row]);
+
+        if (tiisg == 0 && r0 + row < args.ne01) {
+            dst_f32[r0 + row] = tot;
+        }
+    }
+}
+
 kernel void kernel_mul_mv_q4_1_f32(
         constant ggml_metal_kargs_mul_mv & args,
         device const char * src0,