mtmd: support dots.ocr

convert_hf_to_gguf.py

@@ -3777,7 +3777,14 @@ def set_vocab(self):
         self._set_vocab_qwen()
 
 
-@ModelBase.register("Qwen2Model", "Qwen2ForCausalLM", "Qwen2AudioForConditionalGeneration", "KORMoForCausalLM", "AudioFlamingo3ForConditionalGeneration")
+@ModelBase.register(
+    "Qwen2Model",
+    "Qwen2ForCausalLM",
+    "Qwen2AudioForConditionalGeneration",
+    "KORMoForCausalLM",
+    "AudioFlamingo3ForConditionalGeneration",
+    "DotsOCRForCausalLM",
+)
 class Qwen2Model(TextModel):
     model_arch = gguf.MODEL_ARCH.QWEN2
 
@@ -3798,7 +3805,8 @@ def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iter
             name = name.replace("language_model.", "") # for InternVL
         if name.startswith("mlp") or name.startswith("multi_modal_projector") \
                 or name.startswith("vision_model") or name.startswith("audio_tower") \
-                or name.startswith("model.vision_tower") or name.startswith("model.multi_modal_projector"):
+                or name.startswith("model.vision_tower") or name.startswith("model.multi_modal_projector") \
+                or name.startswith("vision_tower."):
             # skip vision and audio tensors
             return
         yield from super().modify_tensors(data_torch, name, bid)
@@ -12819,6 +12827,37 @@ def set_vocab(self):
         special_vocab.add_to_gguf(self.gguf_writer)
 
 
+@ModelBase.register("DotsOCRForCausalLM")
+class DotsOCRVisionModel(MmprojModel):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        assert self.hparams_vision is not None
+        self.hparams_vision["image_size"] = 0 # dynamic resolution
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.DOTSOCR)
+        self.gguf_writer.add_vision_min_pixels(self.preprocessor_config["min_pixels"])
+        self.gguf_writer.add_vision_max_pixels(self.preprocessor_config["max_pixels"])
+        self.gguf_writer.add_vision_attention_layernorm_eps(self.find_vparam(["rms_norm_eps"]))
+        self.gguf_writer.add_vision_projector_scale_factor(self.find_vparam(["spatial_merge_size"]))
+        self.gguf_writer.add_vision_use_silu(True)
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        if name.startswith("vision_tower."):
+            if "vision_tower.blocks." in name and ".mlp." in name:
+                # note: to avoid naming conflicts in tensor_mapping.py, we need to handle FFN renaming here
+                # x = F.silu(self.fc1(x)) * self.fc3(x)
+                # x = self.fc2(x)
+                # fc1 -> gate, fc2 -> down, fc3 -> up
+                # mapping original names to Qwen2.5 naming scheme
+                name = name.replace("vision_tower.blocks.", "visual.blocks.")
+                name = name.replace(".fc1", ".gate_proj")
+                name = name.replace(".fc2", ".down_proj")
+                name = name.replace(".fc3", ".up_proj")
+            yield from super().modify_tensors(data_torch, name, bid)
+
+
 ###### CONVERSION LOGIC ######
 
 

docs/multimodal.md

@@ -37,6 +37,7 @@ llama-server -hf ggml-org/gemma-3-4b-it-GGUF --no-mmproj-offload
 > - PaddleOCR-VL: https://github.com/ggml-org/llama.cpp/pull/18825
 > - GLM-OCR: https://github.com/ggml-org/llama.cpp/pull/19677
 > - Deepseek-OCR: https://github.com/ggml-org/llama.cpp/pull/17400
+> - Dots.OCR: https://github.com/ggml-org/llama.cpp/pull/17575
 > - HunyuanOCR: https://github.com/ggml-org/llama.cpp/pull/21395
 
 ## Pre-quantized models

gguf-py/gguf/constants.py

@@ -4122,6 +4122,7 @@ class VisionProjectorType:
     LIGHTONOCR = "lightonocr"
     COGVLM = "cogvlm"
     JANUS_PRO = "janus_pro"
+    DOTSOCR = "dots_ocr"
     DEEPSEEKOCR = "deepseekocr"
     LFM2A = "lfm2a" # audio
     MUSIC_FLAMINGO = "musicflamingo" # audio

gguf-py/gguf/tensor_mapping.py

@@ -1359,6 +1359,7 @@ class TensorNameMap:
             "visual.merger.mlp.{bid}", # qwen2vl
             "mlp_AR.linear_{bid}", # PaddleOCR-VL
             "merger.mlp.{bid}",
+            "vision_tower.merger.mlp.{bid}", # dots.ocr
             "vit.perceive.proj.{bid}", # HunyuanOCR (proj.0 = conv1, proj.2 = conv2)
         ),
 
@@ -1406,11 +1407,13 @@ class TensorNameMap:
             "siglip2.vision_model.embeddings.patch_embedding",
             "vision_model.radio_model.model.patch_generator.embedder", # Nemotron Nano v2 VL
             "model.vision_tower.patch_embedder.input_proj", # gemma4
+            "vision_tower.patch_embed.patchifier.proj", # dots.ocr
             "vision_model.conv1", # Step3-VL
         ),
 
         MODEL_TENSOR.V_ENC_EMBD_NORM: (
             "visual.post_conv_layernorm", # glm4v
+            "vision_tower.patch_embed.patchifier.norm", # dots.ocr
         ),
 
         MODEL_TENSOR.V_ENC_EMBD_POS: (
@@ -1441,6 +1444,7 @@ class TensorNameMap:
 
         MODEL_TENSOR.V_ENC_ATTN_QKV: (
             "visual.blocks.{bid}.attn.qkv", # qwen3vl
+            "vision_tower.blocks.{bid}.attn.qkv", # dots.ocr
             "model.vision.transformer.layers.{bid}.attention.query_key_value", # cogvlm
             "model.vision_model.transformer.layers.{bid}.self_attn.qkv_proj", # Deepseek-OCR CLIP
             "vision_tower.encoder.blocks.{bid}.wqkv", # Kimi-K2.5
@@ -1526,6 +1530,7 @@ class TensorNameMap:
             "model.vision_model.transformer.layers.{bid}.layer_norm1", # Deepseek-OCR CLIP
             "siglip2.vision_model.encoder.layers.{bid}.layer_norm1",
             "vision_model.radio_model.model.blocks.{bid}.norm1", # Nemotron Nano v2 VL
+            "vision_tower.blocks.{bid}.norm1", # dots.ocr
             "vision_model.transformer.resblocks.{bid}.ln_1", # Step3-VL
         ),
 
@@ -1547,6 +1552,7 @@ class TensorNameMap:
             "siglip2.vision_model.encoder.layers.{bid}.self_attn.out_proj", # youtuvl
             "vision_model.radio_model.model.blocks.{bid}.attn.proj", # Nemotron Nano v2 VL
             "vision_model.model.layers.{bid}.self_attn.o_proj.linear", # gemma4
+            "vision_tower.blocks.{bid}.attn.proj", # dots.ocr
             "vision_model.transformer.resblocks.{bid}.attn.out_proj", # Step3-VL
         ),
 
@@ -1567,6 +1573,7 @@ class TensorNameMap:
             "siglip2.vision_model.encoder.layers.{bid}.layer_norm2",
             "vision_model.radio_model.model.blocks.{bid}.norm2", # Nemotron Nano v2 VL
             "vision_model.model.layers.{bid}.pre_feedforward_layernorm", # gemma4
+            "vision_tower.blocks.{bid}.norm2", # dots.ocr
             "vision_model.transformer.resblocks.{bid}.ln_2", # Step3-VL
         ),
 
@@ -1649,6 +1656,7 @@ class TensorNameMap:
             "vision_encoder.ln_pre", # pixtral
             "vision_model.layernorm_pre", # llama4
             "model.vision_model.pre_layrnorm", # Deepseek-OCR CLIP
+            "vision_tower.patch_embed.patchifier.norm", # dots.ocr
             "vision_model.ln_pre", # Step3-VL
         ),
 
@@ -1664,6 +1672,7 @@ class TensorNameMap:
 
         MODEL_TENSOR.V_MM_POST_NORM: (
             "visual.merger.post_projection_norm", # glm4v
+            "vision_tower.post_trunk_norm", # dots.ocr
             "vit.perceive.after_rms", # HunyuanOCR
         ),
 
@@ -1680,6 +1689,7 @@ class TensorNameMap:
             "model.vision.linear_proj.norm1", # cogvlm
             "mlp_AR.pre_norm", # PaddleOCR-VL
             "merger.ln_q",
+            "vision_tower.merger.ln_q", # dots.ocr
         ),
 
         MODEL_TENSOR.V_MM_SOFT_EMB_NORM: (

tools/mtmd/CMakeLists.txt

@@ -17,6 +17,7 @@ add_library(mtmd
             models/models.h
             models/cogvlm.cpp
             models/conformer.cpp
+            models/dotsocr.cpp
             models/gemma4v.cpp
             models/glm4v.cpp
             models/hunyuanocr.cpp

tools/mtmd/clip-impl.h

@@ -266,6 +266,7 @@ enum projector_type {
     PROJECTOR_TYPE_LIGHTONOCR,
     PROJECTOR_TYPE_COGVLM,
     PROJECTOR_TYPE_JANUS_PRO,
+    PROJECTOR_TYPE_DOTS_OCR,
     PROJECTOR_TYPE_DEEPSEEKOCR,
     PROJECTOR_TYPE_LFM2A,
     PROJECTOR_TYPE_GLM4V,
@@ -308,6 +309,7 @@ static std::map<projector_type, std::string> PROJECTOR_TYPE_NAMES = {
     { PROJECTOR_TYPE_LIGHTONOCR,"lightonocr"},
     { PROJECTOR_TYPE_COGVLM,    "cogvlm"},
     { PROJECTOR_TYPE_JANUS_PRO, "janus_pro"},
+    { PROJECTOR_TYPE_DOTS_OCR,  "dots_ocr"},
     { PROJECTOR_TYPE_DEEPSEEKOCR,"deepseekocr"},
     { PROJECTOR_TYPE_LFM2A,     "lfm2a"},
     { PROJECTOR_TYPE_GLM4V,     "glm4v"},

tools/mtmd/clip.cpp

@@ -853,6 +853,10 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
             {
                 builder = std::make_unique<clip_graph_pixtral>(ctx, img);
             } break;
+        case PROJECTOR_TYPE_DOTS_OCR:
+            {
+                builder = std::make_unique<clip_graph_dotsocr>(ctx, img);
+            } break;
         case PROJECTOR_TYPE_QWEN2VL:
         case PROJECTOR_TYPE_QWEN25VL:
             {
@@ -1269,6 +1273,14 @@ struct clip_model_loader {
                         get_u32(KEY_PREPROC_IMAGE_SIZE, hparams.image_longest_edge, false);
                         hparams.set_warmup_n_tokens(256); // avoid OOM on warmup
                     } break;
+                case PROJECTOR_TYPE_DOTS_OCR:
+                    {
+                        hparams.rope_theta = 10000.0f;
+                        get_u32(KEY_PROJ_SCALE_FACTOR, hparams.n_merge);
+                        get_u32(KEY_IMAGE_MIN_PIXELS, hparams.image_min_pixels);
+                        get_u32(KEY_IMAGE_MAX_PIXELS, hparams.image_max_pixels);
+                        hparams.set_warmup_n_tokens(46*46); // avoid OOM on warmup
+                    } break;
                 case PROJECTOR_TYPE_KIMIVL:
                     {
                         hparams.image_resize_algo = RESIZE_ALGO_BILINEAR;
@@ -1983,6 +1995,17 @@ struct clip_model_loader {
                     model.mm_input_norm_w   = get_tensor(TN_MM_INP_NORM, false);
                     model.mm_patch_merger_w = get_tensor(string_format(TN_MM_PATCH_MERGER, "weight"), false);
                 } break;
+            case PROJECTOR_TYPE_DOTS_OCR:
+                {
+                    model.mm_0_w = get_tensor(string_format(TN_LLAVA_PROJ, 0, "weight"));
+                    model.mm_0_b = get_tensor(string_format(TN_LLAVA_PROJ, 0, "bias"));
+                    model.mm_2_w = get_tensor(string_format(TN_LLAVA_PROJ, 2, "weight"));
+                    model.mm_2_b = get_tensor(string_format(TN_LLAVA_PROJ, 2, "bias"));
+                    model.mm_input_norm_w = get_tensor(TN_MM_INP_NORM);
+                    model.mm_input_norm_b = get_tensor(TN_MM_INP_NORM_B);
+                    // post_trunk_norm: applied after all ViT blocks, before the merger
+                    model.post_ln_w = get_tensor(string_format(TN_MM_POST_NORM, "weight"));
+                } break;
             case PROJECTOR_TYPE_ULTRAVOX:
                 {
                     model.conv1d_1_w = get_tensor(string_format(TN_CONV1D, 1, "weight"));
@@ -2763,6 +2786,7 @@ int clip_n_output_tokens(const struct clip_ctx * ctx, struct clip_image_f32 * im
                 n_patches = x_patch * y_patch;
             } break;
         case PROJECTOR_TYPE_PADDLEOCR:
+        case PROJECTOR_TYPE_DOTS_OCR:
             {
                 // dynamic size
                 int n_merge = ctx->model.hparams.n_merge;
@@ -3071,6 +3095,28 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
                     }
                 }
 
+                set_input_i32("positions", positions);
+            } break;
+        case PROJECTOR_TYPE_DOTS_OCR:
+            {
+                const int pw = image_size_width / patch_size;
+                const int ph = image_size_height / patch_size;
+                const int n_pos = ph * pw;
+                std::vector<int> positions(n_pos * 4);
+                int ptr = 0;
+
+                // flat layout: [h, w, h, w] for each patch
+                // patches are in raster order (matching conv2d output)
+                for (int y = 0; y < ph; y++) {
+                    for (int x = 0; x < pw; x++) {
+                        positions[          ptr] = y;
+                        positions[  n_pos + ptr] = x;
+                        positions[2*n_pos + ptr] = y;
+                        positions[3*n_pos + ptr] = x;
+                        ptr++;
+                    }
+                }
+
                 set_input_i32("positions", positions);
             } break;
         case PROJECTOR_TYPE_QWEN25VL:
@@ -3388,6 +3434,7 @@ int clip_n_mmproj_embd(const struct clip_ctx * ctx) {
         case PROJECTOR_TYPE_PHI4:
         case PROJECTOR_TYPE_PIXTRAL:
         case PROJECTOR_TYPE_LIGHTONOCR:
+        case PROJECTOR_TYPE_DOTS_OCR:
             return ctx->model.mm_2_w->ne[1];
         case PROJECTOR_TYPE_MLP_NORM:
             return ctx->model.mm_3_b->ne[0];

tools/mtmd/models/dotsocr.cpp

@@ -0,0 +1,49 @@
+#include "models.h"
+
+ggml_cgraph * clip_graph_dotsocr::build() {
+    const int n_pos            = n_patches;
+    const int num_position_ids = n_pos * 4; // m-rope requires 4 dim per position
+
+    // note: similar to PaddleOCR
+    int mrope_sections[4] = {d_head/4, d_head/4, d_head/4, d_head/4};
+
+    ggml_tensor * positions = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, num_position_ids);
+    ggml_set_name(positions, "positions");
+    ggml_set_input(positions);
+
+    auto add_pos = [&](ggml_tensor * cur, const clip_layer &) {
+        return ggml_rope_multi(
+                    ctx0, cur, positions, nullptr,
+                    d_head/2, mrope_sections, GGML_ROPE_TYPE_VISION,
+                    32768, 10000, 1, 0, 1, 32, 1);
+    };
+
+    ggml_tensor * inp = build_inp();
+    ggml_tensor * cur = build_vit(
+                            inp, n_patches,
+                            NORM_TYPE_RMS,
+                            hparams.ffn_op,
+                            nullptr,
+                            add_pos);
+
+    cb(cur, "vit_out", -1);
+
+    // dots.ocr patch merger + projector
+    {
+        GGML_ASSERT(hparams.n_merge > 0);
+        cur = build_norm(cur, model.mm_input_norm_w, model.mm_input_norm_b, NORM_TYPE_NORMAL, 1e-6, -1);
+        cur = build_patch_merge_permute(cur, hparams.n_merge);
+        cb(cur, "after_patch_merger", -1);
+        cur = build_ffn(cur,
+            model.mm_0_w, model.mm_0_b,
+            nullptr, nullptr, // no gate
+            model.mm_2_w, model.mm_2_b,
+            FFN_GELU_ERF, -1); // nn.GELU() defaults to exact erf-based GELU
+        cb(cur, "after_projector", -1);
+    }
+
+    // build the graph
+    ggml_build_forward_expand(gf, cur);
+
+    return gf;
+}

tools/mtmd/models/models.h

@@ -73,6 +73,11 @@ struct clip_graph_paddleocr : clip_graph {
     ggml_cgraph * build() override;
 };
 
+struct clip_graph_dotsocr : clip_graph {
+    clip_graph_dotsocr(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
+    ggml_cgraph * build() override;
+};
+
 struct clip_graph_cogvlm : clip_graph {
     clip_graph_cogvlm(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
     ggml_cgraph * build() override;

tools/mtmd/mtmd.cpp

@@ -375,6 +375,13 @@ struct mtmd_context {
                     img_end = "<|im_end|>";
                     image_preproc = std::make_unique<mtmd_image_preprocessor_longest_edge>(ctx_v);
                 } break;
+            case PROJECTOR_TYPE_DOTS_OCR:
+                {
+                    // <|img|> ... (image embeddings) ... <|endofimg|>
+                    img_beg = "<|img|>";
+                    img_end = "<|endofimg|>";
+                    image_preproc = std::make_unique<mtmd_image_preprocessor_dyn_size>(ctx_v);
+                } break;
             case PROJECTOR_TYPE_NEMOTRON_V2_VL:
                 {
                     image_preproc = std::make_unique<mtmd_image_preprocessor_fixed_size>(ctx_v);

tools/mtmd/tests.sh

@@ -89,6 +89,7 @@ add_test_vision "ggml-org/LFM2-VL-450M-GGUF:Q8_0"
 add_test_vision "ggml-org/granite-docling-258M-GGUF:Q8_0"
 add_test_vision "ggml-org/LightOnOCR-1B-1025-GGUF:Q8_0"
 add_test_vision "ggml-org/DeepSeek-OCR-GGUF:Q8_0" -p "Free OCR." --chat-template deepseek-ocr
+add_test_vision "ggml-org/dots.ocr-GGUF:Q8_0" -p "OCR"
 add_test_vision "ggml-org/HunyuanOCR-GGUF:Q8_0" -p "OCR"
 
 add_test_audio  "ggml-org/ultravox-v0_5-llama-3_2-1b-GGUF:Q8_0"