MTP: clean-up

common/arg.cpp

@@ -335,11 +335,15 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
 struct handle_model_result {
     bool found_mmproj = false;
     common_params_model mmproj;
+
+    bool found_mtp = false;
+    common_params_model mtp;
 };
 
 static handle_model_result common_params_handle_model(struct common_params_model & model,
                                                       const std::string          & bearer_token,
-                                                      bool                         offline) {
+                                                      bool                         offline,
+                                                      bool                         search_mtp = false) {
     handle_model_result result;
 
     if (!model.docker_repo.empty()) {
@@ -354,7 +358,7 @@ static handle_model_result common_params_handle_model(struct common_params_model
         common_download_opts opts;
         opts.bearer_token = bearer_token;
         opts.offline = offline;
-        auto download_result = common_download_model(model, opts, true);
+        auto download_result = common_download_model(model, opts, true, search_mtp);
 
         if (download_result.model_path.empty()) {
             LOG_ERR("error: failed to download model from Hugging Face\n");
@@ -368,6 +372,11 @@ static handle_model_result common_params_handle_model(struct common_params_model
             result.found_mmproj = true;
             result.mmproj.path  = download_result.mmproj_path;
         }
+
+        if (!download_result.mtp_path.empty()) {
+            result.found_mtp = true;
+            result.mtp.path  = download_result.mtp_path;
+        }
     } else if (!model.url.empty()) {
         if (model.path.empty()) {
             auto f = string_split<std::string>(model.url, '#').front();
@@ -588,7 +597,11 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
 
     // handle model and download
     if (!skip_model_download) {
-        auto res = common_params_handle_model(params.model, params.hf_token, params.offline);
+        const bool spec_type_mtp = std::find(params.speculative.types.begin(),
+                                             params.speculative.types.end(),
+                                             COMMON_SPECULATIVE_TYPE_MTP) != params.speculative.types.end();
+
+        auto res = common_params_handle_model(params.model, params.hf_token, params.offline, spec_type_mtp);
         if (params.no_mmproj) {
             params.mmproj = {};
         } else if (res.found_mmproj && params.mmproj.path.empty() && params.mmproj.url.empty()) {
@@ -602,6 +615,14 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
                 break;
             }
         }
+        // when --spec-type mtp is set and no draft model was provided explicitly,
+        // fall back to the MTP head discovered alongside the -hf model
+        if (spec_type_mtp && res.found_mtp &&
+            params.speculative.draft.mparams.path.empty() &&
+            params.speculative.draft.mparams.hf_repo.empty() &&
+            params.speculative.draft.mparams.url.empty()) {
+            params.speculative.draft.mparams.path = res.mtp.path;
+        }
         common_params_handle_model(params.speculative.draft.mparams, params.hf_token, params.offline);
         common_params_handle_model(params.vocoder.model,             params.hf_token, params.offline);
     }

common/download.cpp

@@ -566,8 +566,11 @@ static hf_cache::hf_files get_split_files(const hf_cache::hf_files & files,
     return result;
 }
 
-static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
-                                          const std::string        & model) {
+// pick the best sibling GGUF whose filename contains `keyword` (e.g. "mmproj" / "MTP"),
+// preferring deeper shared directory prefix with the model, then closest quantization
+static hf_cache::hf_file find_best_sibling(const hf_cache::hf_files & files,
+                                           const std::string        & model,
+                                           const std::string        & keyword) {
     hf_cache::hf_file best;
     size_t best_depth = 0;
     int best_diff = 0;
@@ -579,20 +582,20 @@ static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
 
     for (const auto & f : files) {
         if (!string_ends_with(f.path, ".gguf") ||
-            f.path.find("mmproj") == std::string::npos) {
+            f.path.find(keyword) == std::string::npos) {
             continue;
         }
 
-        auto mmproj_parts = string_split<std::string>(f.path, '/');
-        auto mmproj_dir = mmproj_parts.end() - 1;
+        auto sib_parts = string_split<std::string>(f.path, '/');
+        auto sib_dir = sib_parts.end() - 1;
 
         auto [_, dir] = std::mismatch(model_parts.begin(), model_dir,
-                                      mmproj_parts.begin(), mmproj_dir);
-        if (dir != mmproj_dir) {
+                                      sib_parts.begin(), sib_dir);
+        if (dir != sib_dir) {
             continue;
         }
 
-        size_t depth = dir - mmproj_parts.begin();
+        size_t depth = dir - sib_parts.begin();
         auto bits = extract_quant_bits(f.path);
         auto diff = std::abs(bits - model_bits);
 
@@ -606,6 +609,16 @@ static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
     return best;
 }
 
+static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
+                                          const std::string        & model) {
+    return find_best_sibling(files, model, "mmproj");
+}
+
+static hf_cache::hf_file find_best_mtp(const hf_cache::hf_files & files,
+                                       const std::string        & model) {
+    return find_best_sibling(files, model, "MTP");
+}
+
 static bool gguf_filename_is_model(const std::string & filepath) {
     if (!string_ends_with(filepath, ".gguf")) {
         return false;
@@ -617,7 +630,8 @@ static bool gguf_filename_is_model(const std::string & filepath) {
     }
 
     return filename.find("mmproj")  == std::string::npos &&
-           filename.find("imatrix") == std::string::npos;
+           filename.find("imatrix") == std::string::npos &&
+           filename.find("MTP")     == std::string::npos;
 }
 
 static hf_cache::hf_file find_best_model(const hf_cache::hf_files & files,
@@ -673,11 +687,13 @@ struct hf_plan {
     hf_cache::hf_file primary;
     hf_cache::hf_files model_files;
     hf_cache::hf_file mmproj;
+    hf_cache::hf_file mtp;
 };
 
 static hf_plan get_hf_plan(const common_params_model  & model,
                            const common_download_opts & opts,
-                           bool download_mmproj) {
+                           bool download_mmproj,
+                           bool download_mtp) {
     hf_plan plan;
     hf_cache::hf_files all;
 
@@ -723,6 +739,10 @@ static hf_plan get_hf_plan(const common_params_model  & model,
         plan.mmproj = find_best_mmproj(all, primary.path);
     }
 
+    if (download_mtp) {
+        plan.mtp = find_best_mtp(all, primary.path);
+    }
+
     return plan;
 }
 
@@ -756,21 +776,25 @@ static std::vector<download_task> get_url_tasks(const common_params_model & mode
 
 common_download_model_result common_download_model(const common_params_model  & model,
                                                    const common_download_opts & opts,
-                                                   bool download_mmproj) {
+                                                   bool download_mmproj,
+                                                   bool download_mtp) {
     common_download_model_result result;
     std::vector<download_task> tasks;
     hf_plan hf;
 
     bool is_hf = !model.hf_repo.empty();
 
     if (is_hf) {
-        hf = get_hf_plan(model, opts, download_mmproj);
+        hf = get_hf_plan(model, opts, download_mmproj, download_mtp);
         for (const auto & f : hf.model_files) {
             tasks.push_back({f.url, f.local_path});
         }
         if (!hf.mmproj.path.empty()) {
             tasks.push_back({hf.mmproj.url, hf.mmproj.local_path});
         }
+        if (!hf.mtp.path.empty()) {
+            tasks.push_back({hf.mtp.url, hf.mtp.local_path});
+        }
     } else if (!model.url.empty()) {
         tasks = get_url_tasks(model);
     } else {
@@ -807,6 +831,10 @@ common_download_model_result common_download_model(const common_params_model  &
         if (!hf.mmproj.path.empty()) {
             result.mmproj_path = hf_cache::finalize_file(hf.mmproj);
         }
+
+        if (!hf.mtp.path.empty()) {
+            result.mtp_path = hf_cache::finalize_file(hf.mtp);
+        }
     } else {
         result.model_path = model.path;
     }
@@ -946,7 +974,8 @@ std::vector<common_cached_model_info> common_list_cached_models() {
     for (const auto & f : files) {
         auto split = get_gguf_split_info(f.path);
         if (split.index != 1 || split.tag.empty() ||
-            split.prefix.find("mmproj") != std::string::npos) {
+            split.prefix.find("mmproj") != std::string::npos ||
+            split.prefix.find("MTP")    != std::string::npos) {
             continue;
         }
         if (seen.insert(f.repo_id + ":" + split.tag).second) {

common/download.h

@@ -59,6 +59,7 @@ struct common_download_opts {
 struct common_download_model_result {
     std::string model_path;
     std::string mmproj_path;
+    std::string mtp_path;
 };
 
 // Download model from HuggingFace repo or URL
@@ -83,12 +84,14 @@ struct common_download_model_result {
 // when opts.offline=true, no network requests are made
 // when download_mmproj=true, searches for mmproj in same directory as model or any parent directory
 // then with the closest quantization bits
+// when download_mtp=true, applies the same sibling search for an MTP-head GGUF
 //
-// returns result with model_path and mmproj_path (empty on failure)
+// returns result with model_path, mmproj_path and mtp_path (empty when not found / on failure)
 common_download_model_result common_download_model(
     const common_params_model & model,
     const common_download_opts & opts = {},
-    bool download_mmproj = false
+    bool download_mmproj = false,
+    bool download_mtp    = false
 );
 
 // returns list of cached models

common/speculative.cpp

@@ -1198,7 +1198,7 @@ common_speculative * common_speculative_init(common_params_speculative & params,
                 LOG_WRN("%s: draft model is not specified - cannot use 'draft' type\n", __func__);
                 has_draft = false;
             }
-        } else if (has_draft_model) {
+        } else if (has_draft_model && !has_mtp && !has_draft_eagle3) {
             LOG_WRN("%s: draft model is specified but 'draft' speculative type is not explicitly enabled - enabling it\n", __func__);
             has_draft = true;
         }

convert_hf_to_gguf.py

@@ -5559,24 +5559,77 @@ class _Qwen35MtpMixin:
     gguf_writer: gguf.GGUFWriter
     block_count: int
     tensor_map: gguf.TensorNameMap
+    fname_out: Path
+    ftype: Any
+    metadata: Any
+
+    # When true, `--mtp` was passed: filter out trunk weights so the resulting
+    # GGUF carries only the MTP head and the shared embeddings/output tensors.
+    mtp_only: bool = False
+
+    # When true, `--no-mtp` was passed: drop `mtp.*` tensors and report block_count
+    # as the trunk-only layer count, producing a GGUF with no MTP head.
+    no_mtp: bool = False
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self.block_count = self.hparams["num_hidden_layers"] + self.hparams.get("mtp_num_hidden_layers", 0)
+        self.block_count = self.hparams["num_hidden_layers"]
+        if not self.no_mtp:
+            self.block_count += self.hparams.get("mtp_num_hidden_layers", 0)
         self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
 
+    @classmethod
+    def filter_tensors(cls, item):
+        name, _ = item
+        if name.startswith("mtp."):
+            # Qwen3Next drops `mtp.*` tensors; Qwen3.5/3.6 use them by default. `--no-mtp` opts out.
+            if cls.no_mtp:
+                return None
+            return item
+        return super().filter_tensors(item)  # ty: ignore[unresolved-attribute]
+
     def set_gguf_parameters(self):
         super().set_gguf_parameters()  # ty: ignore[unresolved-attribute]
+        if self.no_mtp:
+            return
         if (n := self.hparams.get("mtp_num_hidden_layers", 0)) > 0:
             self.gguf_writer.add_nextn_predict_layers(n)
 
+    def prepare_metadata(self, vocab_only: bool):
+        super().prepare_metadata(vocab_only=vocab_only)  # ty: ignore[unresolved-attribute]
+
+        if not self.mtp_only:
+            return
+
+        output_type: str = self.ftype.name.partition("_")[2]
+
+        if self.fname_out.is_dir():
+            fname_default: str = gguf.naming_convention(
+                self.metadata.name, self.metadata.basename, self.metadata.finetune,
+                self.metadata.version, size_label=None, output_type=output_type, model_type=None)
+            self.fname_out = self.fname_out / f"{Path(fname_default).stem}-MTP.gguf"
+        else:
+            stem = self.fname_out.stem
+            self.fname_out = self.fname_out.parent / f"{stem}-MTP{self.fname_out.suffix}"
+
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         # Multimodal Qwen3.5/3.6 wrap the text model under `model.language_model.*`.
         if name.startswith("model.language_model."):
             name = "model." + name[len("model.language_model."):]
         elif name.startswith("language_model."):
             name = name[len("language_model."):]
 
+        if self.mtp_only:
+            # In --mtp mode keep only the MTP block plus the shared embedding/output tensors
+            # that the standalone MTP graph references at inference time.
+            keep = (
+                name.startswith("mtp.") or
+                name in ("model.embed_tokens.weight", "model.norm.weight", "lm_head.weight") or
+                name in ("embed_tokens.weight", "norm.weight")
+            )
+            if not keep:
+                return
+
         # Remap MTP block tensors to llama.cpp's layer-indexed nextn naming.
         # HF: mtp.layers.0.*  (transformer block at MTP slot 0)
         #     mtp.fc / mtp.pre_fc_norm_embedding / mtp.pre_fc_norm_hidden / mtp.norm
@@ -14034,6 +14087,14 @@ def parse_args() -> argparse.Namespace:
         "--mmproj", action="store_true",
         help="(Experimental) Export multimodal projector (mmproj) for vision models. This will only work on some vision models. A prefix 'mmproj-' will be added to the output file name.",
     )
+    parser.add_argument(
+        "--mtp", action="store_true",
+        help="(Experimental) Export only the multi-token prediction (MTP) head as a separate GGUF, suitable for use as a speculative draft. Output file name will get a '-MTP' suffix.",
+    )
+    parser.add_argument(
+        "--no-mtp", action="store_true",
+        help="(Experimental) Exclude the multi-token prediction (MTP) head from the converted GGUF. Pair with --mtp on a second run to publish trunk and MTP as two files. Note: the split form duplicates embeddings, so the bundled default is more space-efficient overall.",
+    )
     parser.add_argument(
         "--mistral-format", action="store_true",
         help="Whether the model is stored following the Mistral format.",
@@ -14193,6 +14254,18 @@ def main() -> None:
         else:
             model_class = MistralModel
 
+        if args.mtp and args.no_mtp:
+            logger.error("--mtp and --no-mtp are mutually exclusive")
+            sys.exit(1)
+
+        if (args.mtp or args.no_mtp) and not issubclass(model_class, _Qwen35MtpMixin):
+            logger.error("--mtp / --no-mtp are only supported for Qwen3.5/3.6 text variants today")
+            sys.exit(1)
+
+        # set on the class so __init__ sees the correct mode when computing block_count
+        if args.no_mtp:
+            model_class.no_mtp = True
+
         model_instance = model_class(dir_model, output_type, fname_out,
                                      is_big_endian=args.bigendian, use_temp_file=args.use_temp_file,
                                      eager=args.no_lazy,
@@ -14205,6 +14278,9 @@ def main() -> None:
                                      fuse_gate_up_exps=args.fuse_gate_up_exps
                                      )
 
+        if args.mtp:
+            model_instance.mtp_only = True
+
         if args.vocab_only:
             logger.info("Exporting model vocab...")
             model_instance.write_vocab()

include/llama.h

@@ -198,6 +198,11 @@ extern "C" {
         LLAMA_SPLIT_MODE_TENSOR = 3,
     };
 
+    enum llama_context_type {
+        LLAMA_CONTEXT_TYPE_DEFAULT     = 0,
+        LLAMA_CONTEXT_TYPE_MTP         = 1,
+    };
+
     // TODO: simplify (https://github.com/ggml-org/llama.cpp/pull/9294#pullrequestreview-2286561979)
     typedef struct llama_token_data {
         llama_token id; // token id
@@ -339,6 +344,7 @@ extern "C" {
         int32_t  n_threads;         // number of threads to use for generation
         int32_t  n_threads_batch;   // number of threads to use for batch processing
 
+        enum llama_context_type      ctx_type;          // set the context type (e.g. MTP)
         enum llama_rope_scaling_type rope_scaling_type; // RoPE scaling type, from `enum llama_rope_scaling_type`
         enum llama_pooling_type      pooling_type;      // whether to pool (sum) embedding results by sequence id
         enum llama_attention_type    attention_type;    // attention type to use for embeddings

src/llama-arch.cpp

@@ -41,8 +41,6 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_QWEN3VLMOE,       "qwen3vlmoe"       },
     { LLM_ARCH_QWEN35,           "qwen35"           },
     { LLM_ARCH_QWEN35MOE,        "qwen35moe"        },
-    { LLM_ARCH_QWEN35_MTP,       "qwen35_mtp"       },
-    { LLM_ARCH_QWEN35MOE_MTP,    "qwen35moe_mtp"    },
     { LLM_ARCH_PHI2,             "phi2"             },
     { LLM_ARCH_PHI3,             "phi3"             },
     { LLM_ARCH_PHIMOE,           "phimoe"           },