diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index 5d48980eb..464de8039 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -2719,7 +2719,7 @@ class StarCoder2Model(Model):
 
 @Model.register("Rwkv6ForCausalLM")
 class RwkvModel(Model):
-    model_arch = gguf.MODEL_ARCH.RWKV
+    model_arch = gguf.MODEL_ARCH.RWKV6
 
     def set_vocab(self):
         assert (self.dir_model / "rwkv_vocab_v20230424.txt").is_file()
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index 32b902480..ebeb200aa 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -211,7 +211,7 @@ class MODEL_ARCH(IntEnum):
     GEMMA        = auto()
     GEMMA2       = auto()
     STARCODER2   = auto()
-    RWKV         = auto()
+    RWKV6        = auto()
     MAMBA        = auto()
     XVERSE       = auto()
     COMMAND_R    = auto()
@@ -365,7 +365,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
     MODEL_ARCH.GEMMA:          "gemma",
     MODEL_ARCH.GEMMA2:         "gemma2",
     MODEL_ARCH.STARCODER2:     "starcoder2",
-    MODEL_ARCH.RWKV:           "rwkv",
+    MODEL_ARCH.RWKV6:          "rwkv6",
     MODEL_ARCH.MAMBA:          "mamba",
     MODEL_ARCH.XVERSE:         "xverse",
     MODEL_ARCH.COMMAND_R:      "command-r",
@@ -908,7 +908,7 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.FFN_DOWN,
         MODEL_TENSOR.FFN_UP,
     ],
-    MODEL_ARCH.RWKV: [
+    MODEL_ARCH.RWKV6: [
         MODEL_TENSOR.TOKEN_EMBD,
         MODEL_TENSOR.TOKEN_EMBD_NORM,
         MODEL_TENSOR.OUTPUT_NORM,
diff --git a/src/llama.cpp b/src/llama.cpp
index 93f003b39..f28e5f743 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -212,7 +212,7 @@ enum llm_arch {
     LLM_ARCH_JAIS,
     LLM_ARCH_NEMOTRON,
     LLM_ARCH_EXAONE,
-    LLM_ARCH_RWKV,
+    LLM_ARCH_RWKV6,
     LLM_ARCH_UNKNOWN,
 };
 
@@ -260,7 +260,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_JAIS,            "jais"         },
     { LLM_ARCH_NEMOTRON,        "nemotron"     },
     { LLM_ARCH_EXAONE,          "exaone"       },
-    { LLM_ARCH_RWKV,            "rwkv"         },
+    { LLM_ARCH_RWKV6,           "rwkv6"        },
     { LLM_ARCH_UNKNOWN,         "(unknown)"    },
 };
 
@@ -1371,7 +1371,7 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
         },
     },
     {
-        LLM_ARCH_RWKV,
+        LLM_ARCH_RWKV6,
         {
             { LLM_TENSOR_TOKEN_EMBD,                "token_embd" },
             { LLM_TENSOR_TOKEN_EMBD_NORM,           "token_embd_norm" },
@@ -5903,7 +5903,7 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
-        case LLM_ARCH_RWKV:
+        case LLM_ARCH_RWKV6:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
                 ml.get_key(LLM_KV_WKV_HEAD_SIZE, hparams.wkv_head_size);
@@ -8338,7 +8338,7 @@ static bool llm_load_tensors(
                         layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
                     }
                 } break;
-            case LLM_ARCH_RWKV:
+            case LLM_ARCH_RWKV6:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
 
@@ -9361,7 +9361,7 @@ static struct ggml_tensor * llm_build_mamba(
     return cur;
 }
 
-static struct ggml_tensor * llm_build_time_mix(
+static struct ggml_tensor * llm_build_time_mix_rwkv6(
     struct ggml_context * ctx,
     const struct llama_layer * layer,
     struct ggml_tensor * cur,
@@ -9522,7 +9522,7 @@ static struct ggml_tensor * llm_build_time_mix(
     return ggml_mul_mat(ctx, layer->time_mix_output, cur);
 }
 
-static struct ggml_tensor * llm_build_channel_mix(
+static struct ggml_tensor * llm_build_channel_mix_rwkv6(
     struct ggml_context * ctx,
     const struct llama_layer * layer,
     struct ggml_tensor * cur,
@@ -15064,7 +15064,7 @@ struct llm_build_context {
         return gf;
     }
 
-    ggml_cgraph * build_rwkv() {
+    ggml_cgraph * build_rwkv6() {
         ggml_cgraph *gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false);
 
         // Token shift state dimensions should be 2 * n_emb
@@ -15112,7 +15112,7 @@ struct llm_build_context {
                 n_embd, n_tokens
             );
 
-            cur = ggml_add(ctx0, cur, llm_build_time_mix(ctx0, layer, x_norm, x_prev, &wkv_states, state_seq));
+            cur = ggml_add(ctx0, cur, llm_build_time_mix_rwkv6(ctx0, layer, x_norm, x_prev, &wkv_states, state_seq));
             ggml_build_forward_expand(gf, cur);
             ggml_build_forward_expand(
                 gf,
@@ -15148,7 +15148,7 @@ struct llm_build_context {
                 ggml_view_1d(ctx0, tmp, n_embd * n_tokens, 0),
                 n_embd, n_tokens
             );
-            cur = ggml_add(ctx0, cur, llm_build_channel_mix(ctx0, layer, x_norm, x_prev));
+            cur = ggml_add(ctx0, cur, llm_build_channel_mix_rwkv6(ctx0, layer, x_norm, x_prev));
             ggml_build_forward_expand(gf, cur);
             ggml_build_forward_expand(
                 gf,
@@ -15444,9 +15444,9 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_exaone();
             } break;
-        case LLM_ARCH_RWKV:
+        case LLM_ARCH_RWKV6:
             {
-                result = llm.build_rwkv();
+                result = llm.build_rwkv6();
             } break;
         default:
             GGML_ABORT("fatal error");
@@ -18477,7 +18477,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_T5:
         case LLM_ARCH_T5ENCODER:
         case LLM_ARCH_JAIS:
-        case LLM_ARCH_RWKV:
+        case LLM_ARCH_RWKV6:
             return LLAMA_ROPE_TYPE_NONE;
 
         // use what we call a normal RoPE, operating on pairs of consecutive head values
@@ -18646,7 +18646,7 @@ llama_token llama_model_decoder_start_token(const struct llama_model * model) {
 bool llama_model_is_recurrent(const struct llama_model * model) {
     switch (model->arch) {
         case LLM_ARCH_MAMBA:  return true;
-        case LLM_ARCH_RWKV:   return true;
+        case LLM_ARCH_RWKV6:   return true;
         default:              return false;
     }
 }