IQ5_K_R4 (#149)

* iq5_k_r4: Zen4

Much slower than the others.

* iq5_k_r5: WIP

* Minor

* iq5_k_r4: fix AVX2 nrc_y = 1 case

* iq5_k_r4: better Zen4

But TG is still slower than iq5_k

* iq5_k_r4: slightly better AVX2

* iq5_k_r4: NEON

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>

10 files changed, 532 insertions, 13 deletions

diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp
index 73485838..d505f493 100644
--- a/examples/quantize/quantize.cpp
+++ b/examples/quantize/quantize.cpp
@@ -61,6 +61,7 @@ static const std::vector<struct quant_option> QUANT_OPTIONS = {
     { "IQ4_K",    LLAMA_FTYPE_MOSTLY_IQ4_K,    " 4.5 bpw non-linear quantization",  },
     { "IQ4_K_R4", LLAMA_FTYPE_MOSTLY_IQ4_K_R4, "IQ4_K repacked",  },
     { "IQ5_K",    LLAMA_FTYPE_MOSTLY_IQ5_K,    " 5.5 bpw non-linear quantization",  },
+    { "IQ5_K_R4", LLAMA_FTYPE_MOSTLY_IQ5_K_R4, "IQ5_K repacked",  },
     { "IQ6_K",    LLAMA_FTYPE_MOSTLY_IQ6_K,    " 6.6 bpw non-linear quantization",  },
     { "Q4_K",     LLAMA_FTYPE_MOSTLY_Q4_K_M,   "alias for Q4_K_M", },
     { "Q4_K_R4",  LLAMA_FTYPE_MOSTLY_Q4_K_R4,  "Q4_K_S repacked", },
diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h
index 77ee0fb9..07142692 100644
--- a/ggml/include/ggml.h
+++ b/ggml/include/ggml.h
@@ -426,6 +426,7 @@ extern "C" {
         GGML_TYPE_IQ2_K_R4  = 337,
         GGML_TYPE_IQ3_K_R4  = 338,
         GGML_TYPE_IQ4_K_R4  = 339,
+        GGML_TYPE_IQ5_K_R4  = 340,
         GGML_TYPE_Q8_K_R8   = 399,
         GGML_TYPE_COUNT,
     };
@@ -502,6 +503,7 @@ extern "C" {
         GGML_FTYPE_MOSTLY_IQ2_K_R4  = 330, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ3_K_R4  = 331, // except 1d tensors
         GGML_FTYPE_MOSTLY_IQ4_K_R4  = 332, // except 1d tensors
+        GGML_FTYPE_MOSTLY_IQ5_K_R4  = 333, // except 1d tensors
         GGML_FTYPE_MOSTLY_Q8_K_R8   = 399, // except 1d tensors
     };
 
diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h
index 03cc3460..0af461c7 100644
--- a/ggml/src/ggml-common.h
+++ b/ggml/src/ggml-common.h
@@ -585,6 +585,16 @@ typedef struct {
 static_assert(sizeof(block_iq5_k) == sizeof(ggml_half) + sizeof(uint16_t) + QK_K/2 + QK_K/8 + 3*QK_K/64, "wrong iq5_k block size/padding");
 
 typedef struct {
+    ggml_half d[4];
+    uint8_t  extra[8];
+    uint8_t  scales_h[QK_K/16];
+    uint8_t  scales_l[QK_K/8 ];
+    uint8_t  qs[QK_K*2];
+    uint8_t  qh[QK_K/2];
+} block_iq5_k_r4;
+static_assert(sizeof(block_iq5_k_r4) == 4*sizeof(block_iq5_k), "wrong iq5_k_r4 block size/padding");
+
+typedef struct {
     ggml_half d;
     uint16_t extra;
     int8_t   scales[QK_K/16];
diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c
index a3beba20..d0de3d0f 100644
--- a/ggml/src/ggml-quants.c
+++ b/ggml/src/ggml-quants.c
@@ -15210,6 +15210,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
         case GGML_TYPE_IQ2_K_R4: break;
         case GGML_TYPE_IQ3_K_R4: break;
         case GGML_TYPE_IQ4_K_R4: break;
+        case GGML_TYPE_IQ5_K_R4: break;
         case GGML_TYPE_Q8_K_R8: break;
         case GGML_TYPE_BF16_R16: break;
         case GGML_TYPE_Q4_0_4_4:
diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c
index 45c873f2..526b1139 100644
--- a/ggml/src/ggml.c
+++ b/ggml/src/ggml.c
@@ -1399,6 +1399,19 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
         .nrows                    = 1,
         .row_meta_size            = 0,
     },
+    [GGML_TYPE_IQ5_K_R4] = {
+        .type_name                = "iq5_k_r4",
+        .blck_size                = QK_K,
+        .type_size                = sizeof(block_iq5_k),
+        .is_quantized             = true,
+        .to_float                 = (ggml_to_float_t) dequantize_row_iq5_k_r4,
+        .from_float               = quantize_row_iq5_k_r4,
+        .from_float_ref           = (ggml_from_float_t)quantize_row_iq5_k_r4_ref,
+        .vec_dot                  = vec_dot_iq5_k_r4_q8_k,
+        .vec_dot_type             = GGML_TYPE_Q8_K,
+        .nrows                    = 1,
+        .row_meta_size            = 0,
+    },
     [GGML_TYPE_IQ6_K] = {
         .type_name                = "iq6_k",
         .blck_size                = QK_K,
@@ -4193,6 +4206,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
         case GGML_FTYPE_MOSTLY_IQ3_K_R4:      wtype = GGML_TYPE_IQ3_K_R4; break;
         case GGML_FTYPE_MOSTLY_IQ4_K_R4:      wtype = GGML_TYPE_IQ4_K_R4; break;
         case GGML_FTYPE_MOSTLY_IQ5_K:         wtype = GGML_TYPE_IQ5_K;    break;
+        case GGML_FTYPE_MOSTLY_IQ5_K_R4:      wtype = GGML_TYPE_IQ5_K_R4; break;
         case GGML_FTYPE_MOSTLY_IQ6_K:         wtype = GGML_TYPE_IQ6_K;    break;
         case GGML_FTYPE_MOSTLY_IQ3_S:         wtype = GGML_TYPE_IQ3_S;    break;
         case GGML_FTYPE_MOSTLY_IQ2_S:         wtype = GGML_TYPE_IQ2_S;    break;
@@ -10732,6 +10746,7 @@ static void ggml_compute_forward_add(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -11190,6 +11205,7 @@ static void ggml_compute_forward_add1(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -11345,6 +11361,7 @@ static void ggml_compute_forward_acc(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -14546,6 +14563,7 @@ static void ggml_compute_forward_out_prod(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -14941,6 +14959,7 @@ static void ggml_compute_forward_set(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -15230,6 +15249,7 @@ static void ggml_compute_forward_get_rows(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -15848,6 +15868,7 @@ static void ggml_compute_forward_clamp(
         case GGML_TYPE_IQ3_K_R4:
         case GGML_TYPE_IQ4_K_R4:
         case GGML_TYPE_IQ5_K:
+        case GGML_TYPE_IQ5_K_R4:
         case GGML_TYPE_IQ6_K:
         case GGML_TYPE_IQ3_S:
         case GGML_TYPE_IQ2_S:
@@ -22694,6 +22715,7 @@ size_t ggml_quantize_chunk(
         case GGML_TYPE_IQ3_K_R4:result = quantize_iq3_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ4_K_R4:result = quantize_iq4_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ5_K:   result = quantize_iq5_k  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
+        case GGML_TYPE_IQ5_K_R4:result = quantize_iq5_k_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ6_K:   result = quantize_iq6_k  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_Q4_0_4_4: result = quantize_q4_0_4x4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_Q4_0_4_8: result = quantize_q4_0_4x8(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
diff --git a/ggml/src/iqk/iqk_mul_mat.cpp b/ggml/src/iqk/iqk_mul_mat.cpp
index bfa68c1d..3e8cbf06 100644
--- a/ggml/src/iqk/iqk_mul_mat.cpp
+++ b/ggml/src/iqk/iqk_mul_mat.cpp
@@ -185,6 +185,7 @@ struct MulMat {
             case GGML_TYPE_IQ2_K_R4:
             case GGML_TYPE_IQ3_K_R4:
             case GGML_TYPE_IQ4_K_R4:
+            case GGML_TYPE_IQ5_K_R4:
             case GGML_TYPE_IQ2_BN_R4: return 4;
             case GGML_TYPE_Q8_K_R8: return 8;
             case GGML_TYPE_BF16_R16: return 16;
@@ -3959,7 +3960,8 @@ static void mul_mat_bf16_r16_bf16(int n, const void * vx, size_t bx, const DataI
 #endif
 
 template <int nrc_y>
-IQK_ALWAYS_INLINE void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
+//IQK_ALWAYS_INLINE void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
+inline void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
         __m256i * isum, int16_t min) {
     auto t1 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 0)), shuff); // blocks  0,  1,  2,  3 for each row
     auto t2 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 1)), shuff); // blocks  4,  5,  6,  7 for each row
@@ -4008,6 +4010,46 @@ IQK_ALWAYS_INLINE void iq234_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8
 }
 
 template <int nrc_y>
+inline void iq2345_k_accum_mins(int ibl, __m256i i8scales1, __m256i i8scales2, const Q8<nrc_y, block_q8_K>& q8, __m256i shuff,
+        __m256i extra, __m256i * isum, int8_t min, int8_t delta) {
+    auto mask = _mm256_set_epi64x(0x0808080808080808, 0x0404040404040404, 0x0202020202020202, 0x0101010101010101);
+    auto vdelta = _mm256_set1_epi8(delta);
+    auto vmin   = _mm256_set1_epi8(min);
+    auto min1 = _mm256_add_epi8(vmin, _mm256_and_si256(vdelta, _mm256_cmpeq_epi8(_mm256_and_si256(extra, mask), mask)));
+    auto min2 = _mm256_add_epi8(vmin, _mm256_and_si256(vdelta, _mm256_cmpeq_epi8(_mm256_and_si256(_mm256_srli_epi16(extra, 4), mask), mask)));
+    auto t1 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 0)), shuff); // blocks  0,  1,  2,  3 for each row
+    auto t2 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales1, 1)), shuff); // blocks  4,  5,  6,  7 for each row
+    auto t3 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales2, 0)), shuff); // blocks  8,  9, 10, 11 for each row
+    auto t4 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(i8scales2, 1)), shuff); // blocks 12, 13, 14, 15 for each row
+    auto m1 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min1, 0)), shuff); // blocks  0,  1,  2,  3 for each row
+    auto m2 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min1, 1)), shuff); // blocks  4,  5,  6,  7 for each row
+    auto m3 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min2, 0)), shuff); // blocks  8,  9, 10, 11 for each row
+    auto m4 = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm256_extracti128_si256(min2, 1)), shuff); // blocks 12, 13, 14, 15 for each row
+    auto s1 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m3, 0), _mm256_extracti128_si256(m1, 0)),
+                                 MM256_SET_M128I(_mm256_extracti128_si256(t3, 0), _mm256_extracti128_si256(t1, 0))); // blocks 0, 1,  8, 9
+    auto s2 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m3, 1), _mm256_extracti128_si256(m1, 1)),
+                                 MM256_SET_M128I(_mm256_extracti128_si256(t3, 1), _mm256_extracti128_si256(t1, 1))); // blocks 2, 3, 10, 11
+    auto s3 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m4, 0), _mm256_extracti128_si256(m2, 0)),
+                                 MM256_SET_M128I(_mm256_extracti128_si256(t4, 0), _mm256_extracti128_si256(t2, 0))); // blocks 4, 5, 12, 13
+    auto s4 = _mm256_mullo_epi16(MM256_SET_M128I(_mm256_extracti128_si256(m4, 1), _mm256_extracti128_si256(m2, 1)),
+                                 MM256_SET_M128I(_mm256_extracti128_si256(t4, 1), _mm256_extracti128_si256(t2, 1))); // blocks 6, 7, 14, 15
+    for (int iy = 0; iy < nrc_y; ++iy) {
+        auto bsums = q8.load_bsums(iy, ibl);
+#ifdef HAVE_FANCY_SIMD
+        isum[iy] = _mm256_dpwssd_epi32(isum[iy], s1, _mm256_shuffle_epi32(bsums, 0x00));
+        isum[iy] = _mm256_dpwssd_epi32(isum[iy], s2, _mm256_shuffle_epi32(bsums, 0x55));
+        isum[iy] = _mm256_dpwssd_epi32(isum[iy], s3, _mm256_shuffle_epi32(bsums, 0xaa));
+        isum[iy] = _mm256_dpwssd_epi32(isum[iy], s4, _mm256_shuffle_epi32(bsums, 0xff));
+#else
+        isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s1, _mm256_shuffle_epi32(bsums, 0x00)));
+        isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s2, _mm256_shuffle_epi32(bsums, 0x55)));
+        isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s3, _mm256_shuffle_epi32(bsums, 0xaa)));
+        isum[iy] = _mm256_add_epi32(isum[iy], _mm256_madd_epi16(s4, _mm256_shuffle_epi32(bsums, 0xff)));
+#endif
+    }
+}
+
+template <int nrc_y>
 static void mul_mat_iq2_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
     GGML_ASSERT(nrc_x%4 == 0);
     Q8<nrc_y, block_q8_K> q8(info);
@@ -4268,6 +4310,159 @@ static void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataI
     }
 }
 
+template <int nrc_y>
+static void mul_mat_iq5_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+    GGML_ASSERT(nrc_x%4 == 0);
+    Q8<nrc_y, block_q8_K> q8(info);
+    auto m4 = _mm256_set1_epi8(0xf);
+    auto m30 = _mm256_set1_epi8(0x30);
+    auto m32 = _mm256_set1_epi8(32);
+    auto ms  = _mm256_set1_epi8(2);
+    auto shift_shuffle = _mm256_set_epi64x(0x0707070706060606, 0x0505050504040404, 0x0303030302020202, 0x0101010100000000);
+    __m256i values[2];
+    {
+        auto val1 = _mm_loadu_si128((const __m128i *)iq5nl_values+0);
+        auto val2 = _mm_loadu_si128((const __m128i *)iq5nl_values+1);
+        values[0] = MM256_SET_M128I(val1, val1);
+        values[1] = MM256_SET_M128I(val2, val2);
+#ifdef HAVE_FANCY_SIMD
+        values[0] = _mm256_sub_epi8(values[0], _mm256_set1_epi8(-128));
+        values[1] = _mm256_sub_epi8(values[1], _mm256_set1_epi8(-128));
+#endif
+    }
+#ifdef HAVE_FANCY_SIMD
+    static const uint8_t k_shuff[32] = {0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15, 0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15};
+    auto shuff = _mm256_loadu_si256((const __m256i *)k_shuff);
+#else
+    auto s_shuffle = _mm256_set_epi64x(0x0f0e0f0e0d0c0d0c, 0x0b0a0b0a09080908, 0x0706070605040504, 0x0302030201000100);
+#endif
+    int nbl = n / QK_K;
+    __m256  acc[nrc_y] = {};
+    __m256i qx[4];
+    uint64_t stored_scales[8];
+    for (int ix = 0; ix < nrc_x; ix += 4) {
+        const block_iq5_k_r4 * iq5 = (const block_iq5_k_r4 *)((const char *)vx + (ix+0)*bx);
+        for (int ibl = 0; ibl < nbl; ++ibl) { // Block of 256
+            auto dl = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq5[ibl].d));
+            auto d4 = _mm256_set_m128(dl, dl);
+            auto extra = _mm256_set1_epi64x(*(const uint64_t *)iq5[ibl].extra);
+            auto slbits = _mm256_loadu_si256((const __m256i *)iq5[ibl].scales_l);
+            auto sl1 = _mm256_and_si256(slbits, m4);
+            auto sl2 = _mm256_and_si256(_mm256_srli_epi16(slbits, 4), m4);
+            auto shbits = _mm_loadu_si128((const __m128i*)iq5[ibl].scales_h);
+            auto sh = MM256_SET_M128I(_mm_srli_epi16(shbits, 2), shbits);
+            auto i8scales1 = _mm256_sub_epi8(_mm256_or_si256(sl1, _mm256_and_si256(m30, _mm256_slli_epi16(sh, 4))), m32);
+            auto i8scales2 = _mm256_sub_epi8(_mm256_or_si256(sl2, _mm256_and_si256(m30, sh)), m32);
+            _mm256_storeu_si256((__m256i *)stored_scales+0, i8scales1);
+            _mm256_storeu_si256((__m256i *)stored_scales+1, i8scales2);
+            __m256i isum[nrc_y] = {};
+#ifdef HAVE_FANCY_SIMD
+            if constexpr (nrc_y == 1) {
+                iq234_k_accum_mins(ibl, i8scales1, i8scales2, q8, shuff, isum, -128);
+            } else {
+                iq2345_k_accum_mins(ibl, i8scales1, i8scales2, q8, shuff, extra, isum, -128, 2);
+            }
+#endif
+            for (int ib = 0; ib < QK_K/32; ++ib) {
+#ifdef HAVE_FANCY_SIMD
+                auto scales = _mm256_cvtepi8_epi32(_mm_loadl_epi64((const __m128i *)(stored_scales + ib)));
+#else
+                auto scales = _mm256_shuffle_epi8(_mm256_cvtepi8_epi16(_mm_set1_epi64x(stored_scales[ib])), s_shuffle);
+#endif
+                auto lbits1 = _mm256_loadu_si256((const __m256i *)iq5[ibl].qs+2*ib+0);
+                auto lbits2 = _mm256_loadu_si256((const __m256i *)iq5[ibl].qs+2*ib+1);
+                auto hbits  = _mm_loadu_si128((const __m128i *)iq5[ibl].qh+ib);
+                auto hb     = MM256_SET_M128I(_mm_srli_epi16(hbits, 2), hbits);
+                qx[0] = _mm256_and_si256(lbits1, m4);
+                qx[1] = _mm256_and_si256(lbits2, m4);
+                qx[2] = _mm256_and_si256(_mm256_srli_epi16(lbits1, 4), m4);
+                qx[3] = _mm256_and_si256(_mm256_srli_epi16(lbits2, 4), m4);
+
+#ifdef HAVE_FANCY_SIMD
+                auto q5vl = _mm256_shuffle_epi8(values[0], qx[0]);
+                auto q5vh = _mm256_shuffle_epi8(values[1], qx[0]);
+                qx[0] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x01)), _mm256_set1_epi8(0x01)), q5vl, q5vh);
+
+                q5vl = _mm256_shuffle_epi8(values[0], qx[1]);
+                q5vh = _mm256_shuffle_epi8(values[1], qx[1]);
+                qx[1] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x10)), _mm256_set1_epi8(0x10)), q5vl, q5vh);
+
+                q5vl = _mm256_shuffle_epi8(values[0], qx[2]);
+                q5vh = _mm256_shuffle_epi8(values[1], qx[2]);
+                qx[2] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x02)), _mm256_set1_epi8(0x02)), q5vl, q5vh);
+
+                q5vl = _mm256_shuffle_epi8(values[0], qx[3]);
+                q5vh = _mm256_shuffle_epi8(values[1], qx[3]);
+                qx[3] = _mm256_mask_blend_epi8(_mm256_cmpeq_epi8_mask(_mm256_and_si256(hb, _mm256_set1_epi8(0x20)), _mm256_set1_epi8(0x20)), q5vl, q5vh);
+
+                if constexpr (nrc_y == 1) {
+                    auto shift = _mm256_and_si256(ms, _mm256_slli_epi16(extra, 1)); extra = _mm256_srli_epi16(extra, 1);
+                    shift = _mm256_shuffle_epi8(shift, shift_shuffle);
+                    qx[0] = _mm256_add_epi8(qx[0], shift);
+                    qx[1] = _mm256_add_epi8(qx[1], shift);
+                    qx[2] = _mm256_add_epi8(qx[2], shift);
+                    qx[3] = _mm256_add_epi8(qx[3], shift);
+                }
+#else
+
+                auto q5vl = _mm256_shuffle_epi8(values[0], qx[0]);
+                auto q5vh = _mm256_shuffle_epi8(values[1], qx[0]);
+                qx[0] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x01)), _mm256_set1_epi8(0x01)));
+
+                q5vl = _mm256_shuffle_epi8(values[0], qx[1]);
+                q5vh = _mm256_shuffle_epi8(values[1], qx[1]);
+                qx[1] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x10)), _mm256_set1_epi8(0x10)));
+
+                q5vl = _mm256_shuffle_epi8(values[0], qx[2]);
+                q5vh = _mm256_shuffle_epi8(values[1], qx[2]);
+                qx[2] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x02)), _mm256_set1_epi8(0x02)));
+
+                q5vl = _mm256_shuffle_epi8(values[0], qx[3]);
+                q5vh = _mm256_shuffle_epi8(values[1], qx[3]);
+                qx[3] = _mm256_blendv_epi8(q5vl, q5vh, _mm256_cmpeq_epi8(_mm256_and_si256(hb, _mm256_set1_epi8(0x20)), _mm256_set1_epi8(0x20)));
+
+                auto shift = _mm256_and_si256(ms, _mm256_slli_epi16(extra, 1)); extra = _mm256_srli_epi16(extra, 1);
+                shift = _mm256_shuffle_epi8(shift, shift_shuffle);
+                qx[0] = _mm256_add_epi8(qx[0], shift);
+                qx[1] = _mm256_add_epi8(qx[1], shift);
+                qx[2] = _mm256_add_epi8(qx[2], shift);
+                qx[3] = _mm256_add_epi8(qx[3], shift);
+                auto s1 = _mm256_sign_epi8(qx[0], qx[0]);
+                auto s2 = _mm256_sign_epi8(qx[1], qx[1]);
+                auto s3 = _mm256_sign_epi8(qx[2], qx[2]);
+                auto s4 = _mm256_sign_epi8(qx[3], qx[3]);
+#endif
+                for (int iy = 0; iy < nrc_y; ++iy) {
+                    auto y = _mm256_loadu_si256((const __m256i*)q8.y[iy][ibl].qs+ib);
+#ifdef HAVE_FANCY_SIMD
+                    auto sumi = _mm256_setzero_si256();
+                    sumi = _mm256_dpbusd_epi32(sumi, qx[0], _mm256_shuffle_epi32(y, 0x00));
+                    sumi = _mm256_dpbusd_epi32(sumi, qx[1], _mm256_shuffle_epi32(y, 0x55));
+                    sumi = _mm256_dpbusd_epi32(sumi, qx[2], _mm256_shuffle_epi32(y, 0xaa));
+                    sumi = _mm256_dpbusd_epi32(sumi, qx[3], _mm256_shuffle_epi32(y, 0xff));
+                    isum[iy] = _mm256_add_epi32(isum[iy], _mm256_mullo_epi32(scales, sumi));
+#else
+                    auto sumi1 = _mm256_maddubs_epi16(s1, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0x00), qx[0]));
+                    auto sumi2 = _mm256_maddubs_epi16(s2, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0x55), qx[1]));
+                    auto sumi3 = _mm256_maddubs_epi16(s3, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0xaa), qx[2]));
+                    auto sumi4 = _mm256_maddubs_epi16(s4, _mm256_sign_epi8(_mm256_shuffle_epi32(y, 0xff), qx[3]));
+                    isum[iy] = _mm256_add_epi32(isum[iy], _mm256_add_epi32(_mm256_madd_epi16(scales, sumi1), _mm256_madd_epi16(scales, sumi2)));
+                    isum[iy] = _mm256_add_epi32(isum[iy], _mm256_add_epi32(_mm256_madd_epi16(scales, sumi3), _mm256_madd_epi16(scales, sumi4)));
+#endif
+                }
+            }
+            for (int iy = 0; iy < nrc_y; ++iy) {
+                acc[iy] = _mm256_fmadd_ps(_mm256_mul_ps(d4, _mm256_set1_ps(q8.scale(iy, ibl))), _mm256_cvtepi32_ps(isum[iy]), acc[iy]);
+            }
+        }
+        for (int iy = 0; iy < nrc_y; ++iy) {
+            auto sum = _mm_add_ps(_mm256_castps256_ps128(acc[iy]), _mm256_extractf128_ps(acc[iy], 1));
+            acc[iy] = _mm256_setzero_ps();
+            info.store(ix+0, iy, sum);
+        }
+    }
+}
+
 template <typename Bits>
 inline void multiply_add_1(int j, const Bits& bits, const __m256i * scales, const __m256i * q8, __m256i * sumi) {
     if (j == 0) {
@@ -6371,6 +6566,18 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) {
             mm.funcs[7] = mul_mat_iq4_k_r4_q8_k<8>;
             expected_typeB = GGML_TYPE_Q8_K;
             break;
+        case GGML_TYPE_IQ5_K_R4:
+            assert (ne00 % QK_K == 0);
+            mm.funcs[0] = mul_mat_iq5_k_r4_q8_k<1>;
+            mm.funcs[1] = mul_mat_iq5_k_r4_q8_k<2>;
+            mm.funcs[2] = mul_mat_iq5_k_r4_q8_k<3>;
+            mm.funcs[3] = mul_mat_iq5_k_r4_q8_k<4>;
+            mm.funcs[4] = mul_mat_iq5_k_r4_q8_k<5>;
+            mm.funcs[5] = mul_mat_iq5_k_r4_q8_k<6>;
+            mm.funcs[6] = mul_mat_iq5_k_r4_q8_k<7>;
+            mm.funcs[7] = mul_mat_iq5_k_r4_q8_k<8>;
+            expected_typeB = GGML_TYPE_Q8_K;
+            break;
         case GGML_TYPE_IQ2_K_R4:
             assert (ne00 % QK_K == 0);
             mm.funcs[0] = mul_mat_iq2_k_r4_q8_k<1>;
@@ -9071,18 +9278,23 @@ void mul_mat_iq4_xs_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& i
     }
 }
 
-template <int nrc_y, bool is_iq2k>
+template <int nrc_y, int k_shift>
 inline void iq3_4_add_shift(int ibl, const Q8<nrc_y, block_q8_K>& q8, const int8x16x4_t& i8scales, uint8x16_t extra,
         int32x4_t * isum) {
-    auto ms = is_iq2k ? vdupq_n_s8(5) : vdupq_n_s8(4);
+    auto ms = vdupq_n_s8(k_shift);
     int8x16_t s8_1, s8_2;
-    if constexpr (is_iq2k) {
+    if constexpr (k_shift == 5) {
         auto m1 = vdupq_n_u8(1);
         s8_1 = vmulq_s8(i8scales.val[0], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
         s8_2 = vmulq_s8(i8scales.val[1], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
     } else {
-        s8_1 = vmulq_s8(i8scales.val[0], vandq_u8(ms, vshlq_n_u8(extra, 2)));
-        s8_2 = vmulq_s8(i8scales.val[1], vandq_u8(ms, extra));
+        if constexpr (k_shift == 4) {
+            s8_1 = vmulq_s8(i8scales.val[0], vandq_u8(ms, vshlq_n_u8(extra, 2)));
+            s8_2 = vmulq_s8(i8scales.val[1], vandq_u8(ms, extra));
+        } else {
+            s8_1 = vmulq_s8(i8scales.val[0], vandq_u8(ms, vshlq_n_u8(extra, 1)));
+            s8_2 = vmulq_s8(i8scales.val[1], vandq_u8(ms, vshrq_n_u8(extra, 1)));
+        }
     }
     auto s16_1 = vmovl_s8(vget_low_s8 (s8_1));
     auto s16_2 = vmovl_s8(vget_high_s8(s8_1));
@@ -9100,13 +9312,18 @@ inline void iq3_4_add_shift(int ibl, const Q8<nrc_y, block_q8_K>& q8, const int8
         isum[iy] = vmlal_lane_s16(isum[iy], vget_low_s16 (s16_4), b8, 2);
         isum[iy] = vmlal_lane_s16(isum[iy], vget_high_s16(s16_4), b8, 3);
     }
-    if constexpr (is_iq2k) {
+    if constexpr (k_shift == 5) {
         auto m1 = vdupq_n_u8(1);
         s8_1 = vmulq_s8(i8scales.val[2], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
         s8_2 = vmulq_s8(i8scales.val[3], vandq_s8(ms, vceqq_u8(vandq_u8(extra, m1), m1))); extra = vshrq_n_u8(extra, 2);
     } else {
-        s8_1 = vmulq_s8(i8scales.val[2], vandq_u8(ms, vshrq_n_u8(extra, 2)));
-        s8_2 = vmulq_s8(i8scales.val[3], vandq_u8(ms, vshrq_n_u8(extra, 4)));
+        if constexpr (k_shift == 4) {
+            s8_1 = vmulq_s8(i8scales.val[2], vandq_u8(ms, vshrq_n_u8(extra, 2)));
+            s8_2 = vmulq_s8(i8scales.val[3], vandq_u8(ms, vshrq_n_u8(extra, 4)));
+        } else {
+            s8_1 = vmulq_s8(i8scales.val[2], vandq_u8(ms, vshrq_n_u8(extra, 3)));
+            s8_2 = vmulq_s8(i8scales.val[3], vandq_u8(ms, vshrq_n_u8(extra, 5)));
+        }
     }
     s16_1 = vmovl_s8(vget_low_s8 (s8_1));
     s16_2 = vmovl_s8(vget_high_s8(s8_1));
@@ -9162,7 +9379,7 @@ void mul_mat_iq2_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
             i8scales.val[3] = vaddq_s8(vshrq_n_u8(sl.val[1], 4), vdupq_n_s8(-8));
             int32x4_t isum[nrc_y] = {};
             if constexpr (nrc_y == 1) {
-                iq3_4_add_shift<nrc_y, true>(ibl, q8, i8scales, extra, isum);
+                iq3_4_add_shift<nrc_y, 5>(ibl, q8, i8scales, extra, isum);
             }
             for (int is = 0; is < 2; ++is) {
                 i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
@@ -9275,7 +9492,7 @@ void mul_mat_iq3_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
             i8scales.val[3] = vmulq_s8(i8scales.val[3], vorrq_u8(vceqq_u8(vandq_u8(sh, smask.val[1]), smask.val[1]), vdupq_n_u8(1)));
             int32x4_t isum[nrc_y] = {};
             if constexpr (nrc_y == 1) {
-                iq3_4_add_shift<nrc_y, false>(ibl, q8, i8scales, extra, isum);
+                iq3_4_add_shift<nrc_y, 4>(ibl, q8, i8scales, extra, isum);
             }
             for (int is = 0; is < 2; ++is) {
                 i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
@@ -9382,7 +9599,7 @@ void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
             i8scales.val[3] = vaddq_s8(vorrq_u8(vshrq_n_u8(sl.val[1], 4), vandq_u8(vshrq_n_u8(sh, 2), m3)), m32);
             int32x4_t isum[nrc_y] = {};
             if constexpr (nrc_y == 1) {
-                iq3_4_add_shift<nrc_y, false>(ibl, q8, i8scales, extra, isum);
+                iq3_4_add_shift<nrc_y, 4>(ibl, q8, i8scales, extra, isum);
             }
             for (int is = 0; is < 2; ++is) {
                 i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
@@ -9443,6 +9660,114 @@ void mul_mat_iq4_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& in
     }
 }
 
+template <int nrc_y>
+void mul_mat_iq5_k_r4_q8_k(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+    GGML_ASSERT(nrc_x%4 == 0);
+    Q8<nrc_y, block_q8_K> q8(info);
+    auto m4 = vdupq_n_u8(0xf);
+    auto m3 = vdupq_n_u8(0x30);
+    auto ms = vdupq_n_u8(2);
+    auto m32 = vdupq_n_s8(-32);
+    auto m10 = vdupq_n_u8(0x10);
+    uint8x16x2_t shift_shuffle = {
+        vreinterpretq_u8_u64(uint64x2_t{0x0101010100000000, 0x0303030302020202}),
+        vreinterpretq_u8_u64(uint64x2_t{0x0505050504040404, 0x0707070706060606})
+    };
+    auto values = vld1q_s8_x2(iq5nl_values);
+    int nbl = n / QK_K;
+    int8x16_t qx[4];
+    int8x16x4_t i8scales;
+    int16x8x4_t i16scales;
+    float32x4_t acc[nrc_y] = {};
+    for (int ix = 0; ix < nrc_x; ix += 4) {
+        const block_iq5_k_r4 * iq5 = (const block_iq5_k_r4 *)((const char *)vx + ix*bx);
+        for (int ibl = 0; ibl < nbl; ++ibl) {
+            auto d4 = vcvt_f32_f16(vld1_f16((const float16_t *)iq5[ibl].d));
+            auto extra8 = vld1_u8(iq5[ibl].extra);
+            uint8x16_t extra;
+            if constexpr (nrc_y == 1) {
+                extra = vcombine_u8(extra8, vshr_n_u8(extra8,1));
+            } else {
+                extra = vcombine_u8(extra8, extra8);
+            }
+            auto sl = vld1q_u8_x2(iq5[ibl].scales_l);
+            auto sh = vld1q_u8(iq5[ibl].scales_h);
+            i8scales.val[0] = vaddq_s8(vorrq_u8(vandq_u8(sl.val[0],  m4), vandq_u8(vshlq_n_u8(sh, 4), m3)), m32);
+            i8scales.val[1] = vaddq_s8(vorrq_u8(vandq_u8(sl.val[1],  m4), vandq_u8(vshlq_n_u8(sh, 2), m3)), m32);
+            i8scales.val[2] = vaddq_s8(vorrq_u8(vshrq_n_u8(sl.val[0], 4), vandq_u8(sh, m3)), m32);
+            i8scales.val[3] = vaddq_s8(vorrq_u8(vshrq_n_u8(sl.val[1], 4), vandq_u8(vshrq_n_u8(sh, 2), m3)), m32);
+            int32x4_t isum[nrc_y] = {};
+            if constexpr (nrc_y == 1) {
+                iq3_4_add_shift<nrc_y, 2>(ibl, q8, i8scales, extra, isum);
+            }
+            for (int is = 0; is < 2; ++is) {
+                i16scales.val[0] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+0]));
+                i16scales.val[1] = vmovl_s8(vget_high_s8(i8scales.val[2*is+0]));
+                i16scales.val[2] = vmovl_s8(vget_low_s8 (i8scales.val[2*is+1]));
+                i16scales.val[3] = vmovl_s8(vget_high_s8(i8scales.val[2*is+1]));
+                for (int ib = 0; ib < 4; ++ib) {
+                    auto lbits = vld1q_u8_x4(iq5[ibl].qs + 256*is + 64*ib);
+                    auto hbits = vld1q_u8(iq5[ibl].qh + 64*is + 16*ib);
+                    qx[0] = vorrq_u8(vandq_u8(lbits.val[0],  m4), vandq_u8(m10, vshlq_n_u8(hbits, 4))); // aligns with 1st half of qx[0] in AVX2
+                    qx[1] = vorrq_u8(vandq_u8(lbits.val[2],  m4), vandq_u8(m10, hbits));                // aligns with 1st half of qx[1] in AVX2
+                    qx[2] = vorrq_u8(vshrq_n_u8(lbits.val[0], 4), vandq_u8(m10, vshlq_n_u8(hbits, 3))); // aligns with 1st half of qx[2] in AVX2
+                    qx[3] = vorrq_u8(vshrq_n_u8(lbits.val[2], 4), vandq_u8(m10, vshrq_n_u8(hbits, 1))); // aligns with 1st half of qx[3] in AVX2
+                    uint8x16_t shifts;
+                    if constexpr (nrc_y == 1) {
+                        qx[0] = vqtbl2q_s8(values, qx[0]);  //  0...3 from the 4 rows
+                        qx[1] = vqtbl2q_s8(values, qx[1]);  //  4...7
+                        qx[2] = vqtbl2q_s8(values, qx[2]);  //  8..11
+                        qx[3] = vqtbl2q_s8(values, qx[3]);  // 12..15
+                    } else {
+                        shifts = vandq_u8(ms, vshlq_n_u8(extra, 1));
+                        auto shift = vqtbl1q_u8(shifts, shift_shuffle.val[0]);
+                        extra = vshrq_n_u8(extra, 1);
+                        qx[0] = vaddq_s8(shift, vqtbl2q_s8(values, qx[0]));  //  0...3 from the 4 rows
+                        qx[1] = vaddq_s8(shift, vqtbl2q_s8(values, qx[1]));  //  4...7
+                        qx[2] = vaddq_s8(shift, vqtbl2q_s8(values, qx[2]));  //  8..11
+                        qx[3] = vaddq_s8(shift, vqtbl2q_s8(values, qx[3]));  // 12..15
+                    }
+                    auto scales = vmovl_s16(vget_low_s16 (i16scales.val[ib]));
+                    for (int iy = 0; iy < nrc_y; ++iy) {
+                        auto y = vld1q_s8(q8.y[iy][ibl].qs+128*is+32*ib);
+                        auto sumi = interleaved_dotq(qx, y);
+                        isum[iy] = vmlaq_s32(isum[iy], scales, sumi);
+                    }
+                    qx[0] = vorrq_u8(vandq_u8(lbits.val[1],  m4), vandq_u8(m10, vshlq_n_u8(hbits, 2))); // aligns with 2nd half of qx[0] in AVX2
+                    qx[1] = vorrq_u8(vandq_u8(lbits.val[3],  m4), vandq_u8(m10, vshrq_n_u8(hbits, 2))); // aligns with 2nd half of qx[1] in AVX2
+                    qx[2] = vorrq_u8(vshrq_n_u8(lbits.val[1], 4), vandq_u8(m10, vshlq_n_u8(hbits, 1))); // aligns with 2nd half of qx[2] in AVX2
+                    qx[3] = vorrq_u8(vshrq_n_u8(lbits.val[3], 4), vandq_u8(m10, vshrq_n_u8(hbits, 3))); // aligns with 2nd half of qx[3] in AVX2
+                    if constexpr (nrc_y == 1) {
+                        qx[0] = vqtbl2q_s8(values, qx[0]);  //  0...3 from the 4 rows
+                        qx[1] = vqtbl2q_s8(values, qx[1]);  //  4...7
+                        qx[2] = vqtbl2q_s8(values, qx[2]);  //  8..11
+                        qx[3] = vqtbl2q_s8(values, qx[3]);  // 12..15
+                    } else {
+                        auto shift = vqtbl1q_u8(shifts, shift_shuffle.val[1]);
+                        qx[0] = vaddq_s8(shift, vqtbl2q_s8(values, qx[0]));  //  0...3 from the 4 rows
+                        qx[1] = vaddq_s8(shift, vqtbl2q_s8(values, qx[1]));  //  4...7
+                        qx[2] = vaddq_s8(shift, vqtbl2q_s8(values, qx[2]));  //  8..11
+                        qx[3] = vaddq_s8(shift, vqtbl2q_s8(values, qx[3]));  // 12..15
+                    }
+                    scales = vmovl_s16(vget_high_s16(i16scales.val[ib]));
+                    for (int iy = 0; iy < nrc_y; ++iy) {
+                        auto y = vld1q_s8(q8.y[iy][ibl].qs+128*is+32*ib+16);
+                        auto sumi = interleaved_dotq(qx, y);
+                        isum[iy] = vmlaq_s32(isum[iy], scales, sumi);
+                    }
+                }
+            }
+            for (int iy = 0; iy < nrc_y; ++iy) {
+                acc[iy] = vfmaq_f32(acc[iy], vmulq_f32(d4, vdupq_n_f32(q8.scale(iy, ibl))), vcvtq_f32_s32(isum[iy]));
+            }
+        }
+        for (int iy = 0; iy < nrc_y; ++iy) {
+            info.store(ix, iy, acc[iy]);
+            acc[iy] = vdupq_n_f32(0.f);
+        }
+    }
+}
+
 IQK_ALWAYS_INLINE void prepare_q4_k_quants(const uint8x16_t& m4, const uint8x16x4_t& bits, int8x16_t * qx) {
     qx[0] = vandq_u8(bits.val[0], m4);   //  0...3 from the 4 rows
     qx[1] = vandq_u8(bits.val[1], m4);   // 16..19
@@ -10282,6 +10607,10 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) {
             SET_MUL_MAT_FUNCTIONS(m, mul_mat_iq4_k_r4_q8_k);
             expected_Btype = GGML_TYPE_Q8_K;
             break;
+        case GGML_TYPE_IQ5_K_R4:
+            SET_MUL_MAT_FUNCTIONS(m, mul_mat_iq5_k_r4_q8_k);
+            expected_Btype = GGML_TYPE_Q8_K;
+            break;
         case GGML_TYPE_Q4_0_R4:
             SET_MUL_MAT_FUNCTIONS_T(m, mul_mat_qx_r4_q8_0, Q4_0_R4_Dequantizer);
             expected_Btype = GGML_TYPE_Q8_0;
diff --git a/ggml/src/iqk/iqk_quantize.cpp b/ggml/src/iqk/iqk_quantize.cpp
index 3408d054..0007dc04 100644
--- a/ggml/src/iqk/iqk_quantize.cpp
+++ b/ggml/src/iqk/iqk_quantize.cpp
@@ -4685,6 +4685,142 @@ void vec_dot_iq4_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t
 }
 
 //
+// ========================================= iq5_k_r4
+//
+
+void quantize_row_iq5_k_r4_ref(const float * x, block_iq5_k_r4 * y, int64_t k) {
+    quantize_iq5_k_r4(x, (void *)y, 4, k/4, nullptr);
+}
+
+void quantize_row_iq5_k_r4(const float * x, void * y, int64_t k) {
+    quantize_iq5_k_r4(x, y, 4, k/4, nullptr);
+}
+
+namespace {
+inline void convert_iq5_k(const block_iq5_k& x, uint8_t * L) {
+    const uint8_t * qs = x.qs;
+    const uint8_t * qh = x.qh;
+    int shift = 0;
+    for (int ib64 = 0; ib64 < QK_K/64; ++ib64) {
+        for (int j = 0; j < 16; ++j) {
+            L[j+ 0] = (qs[j+ 0] & 0xf) | (((qh[j+ 0] >> shift) & 1) << 4);
+            L[j+16] = (qs[j+16] & 0xf) | (((qh[j+16] >> shift) & 1) << 4);
+            L[j+32] = (qs[j+ 0] >>  4) | (((qh[j+ 0] >> shift) & 2) << 3);
+            L[j+48] = (qs[j+16] >>  4) | (((qh[j+16] >> shift) & 2) << 3);
+        }
+        L  += 64;
+        qs += 32;
+        shift += 2;
+        if (shift == 8) { qh += 32; shift = 0; }
+    }
+}
+}
+
+static void repack_iq5_k(int nrows, int n_per_row, const block_iq5_k * x, block_iq5_k_r4 * y) {
+    GGML_ASSERT(nrows%4 == 0);
+    GGML_ASSERT(n_per_row%QK_K == 0);
+    int nblock = n_per_row/QK_K;
+    const block_iq5_k * x4[4];
+    uint8_t L[QK_K];
+    for (int row = 0; row < nrows; row += 4) {
+        for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k;
+        for (int ibl = 0; ibl < nblock; ++ibl) {
+            std::memset(y[ibl].extra, 0, 8);
+            std::memset(y[ibl].scales_l, 0, QK_K/8);
+            std::memset(y[ibl].scales_h, 0, QK_K/16);
+            for (int k = 0; k < 4; ++k) {
+                y[ibl].d[k] = x4[k][ibl].d;
+                auto extra = x4[k][ibl].extra;
+                convert_iq5_k(x4[k][ibl], L);
+                for (int ib = 0; ib < QK_K/32; ++ib) {
+                    if (extra & 1) y[ibl].extra[k+0] |= (1 << ib);
+                    if (extra & 2) y[ibl].extra[k+4] |= (1 << ib);
+                    extra >>= 2;
+                    uint8_t sl1 = x4[k][ibl].scales_l[ib] & 0xf;
+                    uint8_t sl2 = x4[k][ibl].scales_l[ib] >>  4;
+                    uint8_t sh  = x4[k][ibl].scales_h[ib/2] >> 4*(ib%2);
+                    uint8_t sh1 = (sh >> 0) & 3;
+                    uint8_t sh2 = (sh >> 2) & 3;
+                    int i = 8*ib + k;
+                    y[ibl].scales_l[i%32] |= (sl1 << 4*(i/32));
+                    y[ibl].scales_h[i%16] |= (sh1 << 2*(i/16));
+                    i += 4;
+                    y[ibl].scales_l[i%32] |= (sl2 << 4*(i/32));
+                    y[ibl].scales_h[i%16] |= (sh2 << 2*(i/16));
+                    for (int i = 0; i < 4; ++i) {
+                        y[ibl].qs[64*ib+4*k+i+ 0] = (L[32*ib+i+ 0] & 0xf) | ((L[32*ib+i+ 8] & 0xf) << 4);  //  0....3 +  8...11 from each row
+                        y[ibl].qs[64*ib+4*k+i+16] = (L[32*ib+i+16] & 0xf) | ((L[32*ib+i+24] & 0xf) << 4);  // 16...19 + 24...27 from each row
+                        y[ibl].qs[64*ib+4*k+i+32] = (L[32*ib+i+ 4] & 0xf) | ((L[32*ib+i+12] & 0xf) << 4);  //  4....7 + 12...15 from each row
+                        y[ibl].qs[64*ib+4*k+i+48] = (L[32*ib+i+20] & 0xf) | ((L[32*ib+i+28] & 0xf) << 4);  // 20...23 + 28...31 from each row
+                        y[ibl].qh[16*ib+4*k+i   ] = ((L[32*ib+i+ 0] >> 4) << 0) | ((L[32*ib+i+ 8] >> 4) << 1) | ((L[32*ib+i+16] >> 4) << 2) | ((L[32*ib+i+24] >> 4) << 3)
+                                                  | ((L[32*ib+i+ 4] >> 4) << 4) | ((L[32*ib+i+12] >> 4) << 5) | ((L[32*ib+i+20] >> 4) << 6) | ((L[32*ib+i+28] >> 4) << 7);
+                    }
+                }
+            }
+        }
+        x += 4*nblock;
+        y += nblock;
+    }
+}
+
+size_t quantize_iq5_k_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) {
+    GGML_ASSERT(nrows%4 == 0);
+    GGML_ASSERT(n_per_row%QK_K == 0);
+    char * qcur = (char *)dst;
+    auto row_size = ggml_row_size(GGML_TYPE_IQ5_K, n_per_row);
+    std::vector<char> qtmp(4*row_size);
+    for (int row = 0; row < nrows; row += 4) {
+        quantize_iq5_k(src, (void *)qtmp.data(), 4, n_per_row, imatrix);
+        repack_iq5_k(4, n_per_row, (const block_iq5_k *)qtmp.data(), (block_iq5_k_r4 *)qcur);
+        qcur += 4*row_size;
+        src += 4*n_per_row;
+    }
+    return nrows*row_size;
+}
+
+void dequantize_row_iq5_k_r4(const block_iq5_k_r4 * x, float * y, int64_t k) {
+    auto n_per_row = k/4;
+    float * y4[4] = {y, y + n_per_row, y + 2*n_per_row, y + 3*n_per_row};
+    int nblock = n_per_row/QK_K;
+    for (int ibl = 0; ibl < nblock; ++ibl) {
+        for (int k = 0; k < 4; ++k) {
+            const float d = GGML_FP16_TO_FP32(x[ibl].d[k]);
+            for (int ib = 0; ib < QK_K/32; ++ib) {
+                int is = 8*ib + k;
+                float dl1 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
+                is += 4;
+                float dl2 = d * ((((x[ibl].scales_l[is%32] >> 4*(is/32)) & 0xf) | (((x[ibl].scales_h[is%16] >> 2*(is/16)) & 3) << 4)) - 32);
+                auto values1 = iq5nl_values + (x[ibl].extra[k+0] & (1 << ib) ? 32 : 0);
+                auto values2 = iq5nl_values + (x[ibl].extra[k+4] & (1 << ib) ? 32 : 0);
+                for (int i = 0; i < 4; ++i) {
+                    y4[k][QK_K*ibl+32*ib+i+ 0] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+ 0] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 0) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+ 8] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+ 0] >>  4) | (((x[ibl].qh[16*ib+4*k+i] >> 1) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+16] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+16] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 2) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+24] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+16] >>  4) | (((x[ibl].qh[16*ib+4*k+i] >> 3) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+ 4] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+32] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 4) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+12] = dl1 * values1[(x[ibl].qs[64*ib+4*k+i+32] >>  4) | (((x[ibl].qh[16*ib+4*k+i] >> 5) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+20] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+48] & 0xf) | (((x[ibl].qh[16*ib+4*k+i] >> 6) & 1) << 4)];
+                    y4[k][QK_K*ibl+32*ib+i+28] = dl2 * values2[(x[ibl].qs[64*ib+4*k+i+48] >>  4) | (((x[ibl].qh[16*ib+4*k+i] >> 7) & 1) << 4)];
+                }
+            }
+        }
+    }
+}
+
+void vec_dot_iq5_k_r4_q8_k(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) {
+#if GGML_USE_IQK_MULMAT
+    if (iqk_mul_mat(1, 1, n, GGML_TYPE_IQ5_K_R4, vx, 0, GGML_TYPE_Q8_K, vy, 0, s, 0, 0, 1)) {
+        return;
+    }
+#endif
+    GGML_ASSERT(n%QK4_NL == 0);
+    GGML_ASSERT(nrc == 1);
+    GGML_UNUSED(bs);
+    GGML_UNUSED(bx);
+    GGML_UNUSED(by);
+}
+
+//
 // ========================================= q8_k_r8
 //
 
diff --git a/ggml/src/iqk/iqk_quantize.h b/ggml/src/iqk/iqk_quantize.h
index 7c568ded..b8604caa 100644
--- a/ggml/src/iqk/iqk_quantize.h
+++ b/ggml/src/iqk/iqk_quantize.h
@@ -139,6 +139,12 @@ size_t quantize_q6_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT ds
 void   dequantize_row_q6_k_r4(const block_q6_k_r4  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
 void   vec_dot_q6_k_r4_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 
+void   quantize_row_iq5_k_r4_ref(const float * GGML_RESTRICT x, block_iq5_k_r4  * GGML_RESTRICT y, int64_t k);
+void   quantize_row_iq5_k_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+size_t quantize_iq5_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+void   dequantize_row_iq5_k_r4(const block_iq5_k_r4  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void   vec_dot_iq5_k_r4_q8_k(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
+
 void   quantize_row_iq4_k_r4_ref(const float * GGML_RESTRICT x, block_iq4_k_r4  * GGML_RESTRICT y, int64_t k);
 void   quantize_row_iq4_k_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 size_t quantize_iq4_k_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
diff --git a/include/llama.h b/include/llama.h
index e63d76fe..7267fbd4 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -196,6 +196,7 @@ extern "C" {
         LLAMA_FTYPE_MOSTLY_IQ2_K_R4      = 338, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_IQ3_K_R4      = 339, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_IQ4_K_R4      = 340, // except 1d tensors
+        LLAMA_FTYPE_MOSTLY_IQ5_K_R4      = 341, // except 1d tensors
         LLAMA_FTYPE_MOSTLY_Q8_K_R8       = 399, // except 1d tensors
 
         LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
diff --git a/src/llama.cpp b/src/llama.cpp
index 68e59758..f04d7f6f 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -3876,6 +3876,7 @@ struct llama_model_loader {
                 case GGML_TYPE_IQ4_K:   ftype = LLAMA_FTYPE_MOSTLY_IQ4_K;   break;
                 case GGML_TYPE_IQ4_K_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ4_K_R4;break;
                 case GGML_TYPE_IQ5_K:   ftype = LLAMA_FTYPE_MOSTLY_IQ5_K;   break;
+                case GGML_TYPE_IQ5_K_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ5_K_R4;break;
                 case GGML_TYPE_IQ6_K:   ftype = LLAMA_FTYPE_MOSTLY_IQ6_K;   break;
                 case GGML_TYPE_IQ3_S:   ftype = LLAMA_FTYPE_MOSTLY_IQ3_S;   break;
                 case GGML_TYPE_Q4_0_4_4: ftype = LLAMA_FTYPE_MOSTLY_Q4_0_4_4; break;
@@ -4601,6 +4602,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
         case LLAMA_FTYPE_MOSTLY_IQ4_K:    return "IQ4_K - 4.5 bpw";
         case LLAMA_FTYPE_MOSTLY_IQ4_K_R4: return "IQ4_K_R4 - 4.5 bpw";
         case LLAMA_FTYPE_MOSTLY_IQ5_K:    return "IQ5_K - 5.5 bpw";
+        case LLAMA_FTYPE_MOSTLY_IQ5_K_R4: return "IQ5_K_R4 - 5.5 bpw";
         case LLAMA_FTYPE_MOSTLY_IQ6_K:    return "IQ6_K - 6.6 bpw";
         case LLAMA_FTYPE_MOSTLY_IQ1_BN:   return "IQ1_BN - 1.625 bpw Bitnet";
         case LLAMA_FTYPE_MOSTLY_IQ2_BN:   return "IQ2_BN - 2.00 bpw Bitnet";
@@ -15854,6 +15856,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
             else if (new_type == GGML_TYPE_IQ4_K_R4) {
                 new_type = GGML_TYPE_IQ4_K;
             }
+            else if (new_type == GGML_TYPE_IQ5_K_R4) {
+                new_type = GGML_TYPE_IQ5_K;
+            }
             else if (new_type == GGML_TYPE_Q4_0_R4) {
                 new_type = GGML_TYPE_Q4_0;
             }
@@ -16150,7 +16155,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
         new_type == GGML_TYPE_IQ2_KS  || new_type == GGML_TYPE_IQ4_KSS || new_type == GGML_TYPE_Q6_K_R4 ||
         new_type == GGML_TYPE_Q5_K_R4 || new_type == GGML_TYPE_Q3_K_R4 || new_type == GGML_TYPE_Q2_K_R4 ||
         new_type == GGML_TYPE_IQ4_K_R4|| new_type == GGML_TYPE_Q8_K_R8 || new_type == GGML_TYPE_IQ3_K_R4||
-        new_type == GGML_TYPE_IQ2_K_R4) {
+        new_type == GGML_TYPE_IQ2_K_R4|| new_type == GGML_TYPE_IQ5_K_R4) {
         int nx = tensor->ne[0];
         int ny = tensor->ne[1];
         if (nx % QK_K != 0) {
@@ -16193,6 +16198,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
             case GGML_TYPE_Q4_K_R4:
             case GGML_TYPE_Q4_K:   new_type = GGML_TYPE_Q5_0;   break;
             case GGML_TYPE_IQ5_K:
+            case GGML_TYPE_IQ5_K_R4:
             case GGML_TYPE_Q5_K_R4:
             case GGML_TYPE_Q5_K:   new_type = GGML_TYPE_Q6_0;   break;
             case GGML_TYPE_IQ6_K:
@@ -16325,6 +16331,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
         case LLAMA_FTYPE_MOSTLY_IQ4_K:   default_type = GGML_TYPE_IQ4_K;   break;
         case LLAMA_FTYPE_MOSTLY_IQ4_K_R4:default_type = GGML_TYPE_IQ4_K_R4;break;
         case LLAMA_FTYPE_MOSTLY_IQ5_K:   default_type = GGML_TYPE_IQ5_K;   break;
+        case LLAMA_FTYPE_MOSTLY_IQ5_K_R4:default_type = GGML_TYPE_IQ5_K_R4;break;
         case LLAMA_FTYPE_MOSTLY_IQ6_K:   default_type = GGML_TYPE_IQ6_K;   break;
         case LLAMA_FTYPE_MOSTLY_IQ3_S:   default_type = GGML_TYPE_IQ3_S;   break;
         case LLAMA_FTYPE_MOSTLY_IQ3_M:   default_type = GGML_TYPE_IQ3_S;   break;
@@ -16741,6 +16748,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
                 if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ4_K;
                 else chunk_size_multiplier = 4;
             }
+            else if (new_type == GGML_TYPE_IQ5_K_R4) {
+                if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ5_K;
+                else chunk_size_multiplier = 4;
+            }
             else if (new_type == GGML_TYPE_BF16_R16) {
                 if (tensor->ne[1] % 16 != 0) new_type = GGML_TYPE_BF16;
                 else chunk_size_multiplier = 16;