diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h
index 93ab7ea446..5e61c44f34 100644
--- a/ggml/src/ggml-common.h
+++ b/ggml/src/ggml-common.h
@@ -378,8 +378,8 @@ typedef struct {
 } block_iq3_xxs;
 static_assert(sizeof(block_iq3_xxs) == sizeof(ggml_half) + 3*(QK_K/8), "wrong iq3_xxs block size/padding");
 
-// 3.4375 bpw
 #define IQ3S_N_SCALE QK_K/64
+// 3.4375 bpw
 typedef struct {
     ggml_half d;
     uint8_t qs[QK_K/4];
diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp
index 7f854d0cb0..3e56b2b86c 100644
--- a/src/llama-quant.cpp
+++ b/src/llama-quant.cpp
@@ -84,10 +84,22 @@ struct quantize_state_impl {
     int n_ffn_down     = 0;
     int n_ffn_gate     = 0;
     int n_ffn_up       = 0;
+    int n_ffn_down_exp = 0;
+    int n_ffn_gate_exp = 0;
+    int n_ffn_up_exp   = 0;
+    int n_ffn_down_shexp = 0;
+    int n_ffn_gate_shexp = 0;
+    int n_ffn_up_shexp   = 0;
     int i_attention_wv = 0;
     int i_ffn_down     = 0;
     int i_ffn_gate     = 0;
     int i_ffn_up       = 0;
+    int i_ffn_down_exp = 0;
+    int i_ffn_gate_exp = 0;
+    int i_ffn_up_exp   = 0;
+    int i_ffn_down_shexp = 0;
+    int i_ffn_gate_shexp = 0;
+    int i_ffn_up_shexp   = 0;
 
     int n_k_quantized = 0;
     int n_fallback    = 0;
@@ -175,6 +187,23 @@ static void llama_tensor_dequantize_impl(
     workers.clear();
 }
 
+// Check if ftype is specifically IQ2_S or IQ2_M
+static inline bool is_iq2s_or_iq2m(llama_ftype ftype) {
+    return ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M;
+}
+
+// Check if ftype belongs to the IQ1 group
+static inline bool is_iq1_group(llama_ftype ftype) {
+    return ftype == LLAMA_FTYPE_MOSTLY_IQ1_S || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M;
+}
+
+// Returns the appropriate type for expert _exps tensors based on ftype
+static inline ggml_type get_expert_exps_type(llama_ftype ftype) {
+    if (is_iq1_group(ftype))         return GGML_TYPE_IQ2_XXS;
+    if (is_iq2s_or_iq2m(ftype))      return GGML_TYPE_IQ3_XXS;
+    /* otherwise */                  return GGML_TYPE_IQ2_XS;
+}
+
 static ggml_type llama_tensor_get_type(quantize_state_impl & qs, ggml_type new_type, const ggml_tensor * tensor, llama_ftype ftype) {
     const std::string name = ggml_get_name(tensor);
 
@@ -242,7 +271,7 @@ static ggml_type llama_tensor_get_type(quantize_state_impl & qs, ggml_type new_t
                 ftype == LLAMA_FTYPE_MOSTLY_IQ1_S   || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M) {
                 new_type = GGML_TYPE_Q2_K;
             }
-            else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) {
+            else if (is_iq2s_or_iq2m(ftype)) {
                 new_type = GGML_TYPE_IQ3_S;
             }
             else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) {
@@ -256,7 +285,7 @@ static ggml_type llama_tensor_get_type(quantize_state_impl & qs, ggml_type new_t
                ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M    || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M) {
         if (name.find("attn_v.weight") != std::string::npos) {
             if (qs.model.hparams.n_gqa() >= 4 || qs.model.hparams.n_expert >= 4) new_type = GGML_TYPE_Q4_K;
-            else new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+            else new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
             ++qs.i_attention_wv;
         }
         else if (qs.model.hparams.n_expert >= 8 && name.find("attn_k.weight") != std::string::npos) {
@@ -266,11 +295,11 @@ static ggml_type llama_tensor_get_type(quantize_state_impl & qs, ggml_type new_t
             new_type = GGML_TYPE_Q4_K;
         }
         else if (qs.model.hparams.n_expert >= 8 && name.find("attn_kv_b.weight") != std::string::npos) {
-            if (qs.i_attention_wv < qs.n_attention_wv/16) {
+            if (qs.i_attention_wv < qs.n_attention_wv/8) {
                 new_type = GGML_TYPE_Q4_K;
             }
             else if (use_more_bits(qs.i_attention_wv, qs.n_attention_wv)) {
-                new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+                new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
             }
             ++qs.i_attention_wv;
         }
@@ -278,47 +307,83 @@ static ggml_type llama_tensor_get_type(quantize_state_impl & qs, ggml_type new_t
             new_type = GGML_TYPE_Q4_K;
         }
         else if (qs.model.hparams.n_expert >= 8 && name.find("attn_q_b.weight") != std::string::npos) {
-            new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+            new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
         }
-        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_down") != std::string::npos) {
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_down.weight") != std::string::npos) {
             if (qs.i_ffn_down < qs.n_ffn_down/16) {
                 new_type = GGML_TYPE_Q4_K;
             }
             else if (qs.i_ffn_down < qs.n_ffn_down/8) {
-                new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+                new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
             }
             ++qs.i_ffn_down;
         }
-        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_gate") != std::string::npos) {           
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_gate.weight") != std::string::npos) {           
             if (qs.i_ffn_gate < qs.n_ffn_gate/16) {
                 new_type = GGML_TYPE_Q4_K;
             }
-            else if (qs.i_ffn_gate < qs.n_ffn_gate/8 || qs.i_ffn_gate >= 7*qs.n_ffn_gate/8) {
-                new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+            else if (qs.i_ffn_gate < qs.n_ffn_gate/8) {
+                new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
             }
             ++qs.i_ffn_gate;
         }
-        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_up") != std::string::npos) {     
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_up.weight") != std::string::npos) {     
             if (qs.i_ffn_up < qs.n_ffn_up/16) {
                 new_type = GGML_TYPE_Q4_K;
             }
             else if (qs.i_ffn_up < qs.n_ffn_up/8) {
-                new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+                new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
             }
             ++qs.i_ffn_up;
         }
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_down_exps.weight") != std::string::npos) {
+            if (qs.i_ffn_down_exp < qs.n_ffn_down_exp/8) {
+                new_type = get_expert_exps_type(ftype);
+            }
+            ++qs.i_ffn_down_exp;
+        }
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_gate_exps.weight") != std::string::npos) {
+            if (qs.i_ffn_gate_exp < qs.n_ffn_gate_exp/8) {
+                new_type = get_expert_exps_type(ftype);
+            }
+            ++qs.i_ffn_gate_exp;
+        }
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_up_exps.weight") != std::string::npos) {
+            if (qs.i_ffn_up_exp < qs.n_ffn_up_exp/8) {
+                new_type = get_expert_exps_type(ftype);
+            }
+            ++qs.i_ffn_up_exp;
+        }
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_down_shexp.weight") != std::string::npos) {
+            if (use_more_bits(qs.i_ffn_down_shexp, qs.n_ffn_down_shexp)) {
+                new_type = GGML_TYPE_Q4_K;
+            }
+            ++qs.i_ffn_down_shexp;
+        }
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_gate_shexp.weight") != std::string::npos) {
+            if (use_more_bits(qs.i_ffn_gate_shexp, qs.n_ffn_gate_shexp)) {
+                new_type = GGML_TYPE_Q4_K;
+            }
+            ++qs.i_ffn_gate_shexp;
+        }
+        else if (qs.model.hparams.n_expert >= 8 && name.find("ffn_up_shexp.weight") != std::string::npos) {
+            if (use_more_bits(qs.i_ffn_up_shexp, qs.n_ffn_up_shexp)) {
+                new_type = GGML_TYPE_Q4_K;
+            }
+            ++qs.i_ffn_up_shexp;
+        }
         else if (name.find("ffn_down") != std::string::npos) {
             if (qs.i_ffn_down < qs.n_ffn_down/8) {
-                new_type = ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
+                new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_IQ3_S : GGML_TYPE_Q2_K;
             }
             ++qs.i_ffn_down;
         }
         else if (name.find("attn_output.weight") != std::string::npos) {
             if (qs.model.hparams.n_expert >= 8) {
-                new_type = GGML_TYPE_Q5_K;
+                new_type = is_iq2s_or_iq2m(ftype) ? GGML_TYPE_Q5_K : GGML_TYPE_Q4_K;
             } else {
-                if (ftype == LLAMA_FTYPE_MOSTLY_IQ1_S || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M) new_type = GGML_TYPE_IQ2_XXS;
-                else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) new_type = GGML_TYPE_IQ3_S;
+                if (is_iq1_group(ftype)) new_type = GGML_TYPE_IQ2_XXS;
+                else if (is_iq2s_or_iq2m(ftype)) new_type = GGML_TYPE_IQ3_S;
             }
         }
     } else if (name.find("attn_v.weight") != std::string::npos) {
@@ -465,38 +530,28 @@ static ggml_type llama_tensor_get_type(quantize_state_impl & qs, ggml_type new_t
             new_type = GGML_TYPE_IQ3_XXS;
         }
         ++qs.i_ffn_up;
-    } else if (name.find("attn_kv_a_mqa") != std::string::npos) {
-        if (qs.model.hparams.n_expert >= 8) {
+    } else if (qs.model.hparams.n_expert >= 8 && name.find("attn_kv_a_mqa.weight") != std::string::npos) {
+        new_type = GGML_TYPE_Q8_0;
+    } else if (qs.model.hparams.n_expert >= 8 && name.find("attn_kv_b.weight") != std::string::npos) {
+        new_type = GGML_TYPE_Q4_K;
+        if (qs.i_attention_wv < qs.n_attention_wv/16) {
             new_type = GGML_TYPE_Q8_0;
+        } else if (use_more_bits(qs.i_attention_wv, qs.n_attention_wv)) {
+            new_type = GGML_TYPE_Q6_K;
         }
-    } else if (name.find("attn_kv_b.weight") != std::string::npos) {
-        if (qs.model.hparams.n_expert >= 8) {
-            new_type = GGML_TYPE_Q4_K;
-            if (qs.i_attention_wv < qs.n_attention_wv/16) {
-                new_type = GGML_TYPE_Q8_0;
-            } else if (use_more_bits(qs.i_attention_wv, qs.n_attention_wv)) {
-                new_type = GGML_TYPE_Q6_K;
-            }
-            else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L || ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS) new_type = GGML_TYPE_Q5_K;
-            else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q6_K;
-        }
+        else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L || ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS) new_type = GGML_TYPE_Q5_K;
+        else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q6_K;
         ++qs.i_attention_wv;
-    } else if (name.find("attn_q_b.weight") != std::string::npos) {
-        if (qs.model.hparams.n_expert >= 8) {
-            if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L || ftype == LLAMA_FTYPE_MOSTLY_IQ3_M) {
-                new_type = GGML_TYPE_Q4_K;
-            }
-            else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M) new_type = GGML_TYPE_Q5_K;
-            else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q6_K;
-        }
-    } else if (name.find("attn_q_a.weight") != std::string::npos) {
-        if (qs.model.hparams.n_expert >= 8) {
-            if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L || ftype == LLAMA_FTYPE_MOSTLY_IQ3_M) {
-                new_type = GGML_TYPE_Q4_K;
-            }
-            else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M) new_type = GGML_TYPE_Q5_K;
-            else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q6_K;
+    } else if (qs.model.hparams.n_expert >= 8 &&name.find("attn_q_b.weight") != std::string::npos) {
+        if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L || ftype == LLAMA_FTYPE_MOSTLY_IQ3_M) {
+            new_type = GGML_TYPE_Q4_K;
         }
+        else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_S) new_type = GGML_TYPE_Q5_K;
+        else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q6_K;
+    } else if (qs.model.hparams.n_expert >= 8 && name.find("attn_q_a.weight") != std::string::npos) {
+        new_type = GGML_TYPE_Q5_K;
+        if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_S) new_type = GGML_TYPE_Q6_K;
+        else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q8_0;
     }
 
     //    if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q3_K;
@@ -793,11 +848,25 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
             ++qs.n_attention_wv;
         } else if (name == LLM_TN(model.arch)(LLM_TENSOR_OUTPUT, "weight")) {
             qs.has_output = true;
+        } else if (name.find("ffn_gate_exps.weight") != std::string::npos) {
+            ++qs.n_ffn_gate_exp;
+        } else if (name.find("ffn_gate_shexp.weight") != std::string::npos) {
+            ++qs.n_ffn_gate_shexp;
+        } else if (name.find("ffn_down_exps.weight") != std::string::npos) {
+            ++qs.n_ffn_down_exp;
+        } else if (name.find("ffn_down_shexp.weight") != std::string::npos) {
+            ++qs.n_ffn_down_shexp;
+        } else if (name.find("ffn_up_exps.weight") != std::string::npos) {
+            ++qs.n_ffn_up_exp;
+        } else if (name.find("ffn_up_shexp.weight") != std::string::npos) {
+            ++qs.n_ffn_up_shexp;
         }
 
         is_clip_model |= name.rfind("mm.", 0) == 0; // check the "mm." prefix
     }
 
+    GGML_ASSERT(qs.n_ffn_down_exp != 0);
+
     qs.n_ffn_down = qs.n_ffn_gate = qs.n_ffn_up = (int)model.hparams.n_layer;
 
     // sanity checks for models that have attention layers