BE-1172 fix(3d): save Preview3DAdvanced / PreviewGaussianSplat / PreviewPointCloud to temp/, rename viewport input

* mm: split off registration helper to doer and headroom calc

* pinned_memory: implement registration comfy side

Move away from Aimdo buffer registrations which seem fraught with
danger and do it comfy side. Just start with the basic move.

* pinned_memory: do registrations as portable memory

* pinned_memory: discard async errors on registration fail

Like the good ol days.

* pinned_memory: implement abs shortfall retry

If pinned registration happens to fail despite the previous budget
ensures, consider the allocation shortfall, ensure it again, and
try again. This allows comfy pins to interoperate with other software
that might be doing substantive pinning.

.ci/windows_amd_base_files/README_VERY_IMPORTANT.txt

@@ -1,28 +1,27 @@
-As of the time of writing this you need this driver for best results:
-https://www.amd.com/en/resources/support-articles/release-notes/RN-AMDGPU-WINDOWS-PYTORCH-7-1-1.html
-
-HOW TO RUN:
-
-If you have a AMD gpu:
-
-run_amd_gpu.bat
-
-If you have memory issues you can try disabling the smart memory management by running comfyui with:
-
-run_amd_gpu_disable_smart_memory.bat
-
-IF YOU GET A RED ERROR IN THE UI MAKE SURE YOU HAVE A MODEL/CHECKPOINT IN: ComfyUI\models\checkpoints
-
-You can download the stable diffusion XL one from: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_base_1.0_0.9vae.safetensors
-
-
-RECOMMENDED WAY TO UPDATE:
-To update the ComfyUI code: update\update_comfyui.bat
-
-
-TO SHARE MODELS BETWEEN COMFYUI AND ANOTHER UI:
-In the ComfyUI directory you will find a file: extra_model_paths.yaml.example
-Rename this file to: extra_model_paths.yaml and edit it with your favorite text editor.
-
-
-
+As of the time of writing this you need a recent driver. Updating to the latest driver is recommended.
+
+HOW TO RUN:
+
+If you have a AMD gpu:
+
+run_amd_gpu.bat
+
+If you have memory issues you can try enabling the new dynamic memory management by running comfyui with:
+
+run_amd_gpu_enable_dynamic_vram.bat
+
+IF YOU GET A RED ERROR IN THE UI MAKE SURE YOU HAVE A MODEL/CHECKPOINT IN: ComfyUI\models\checkpoints
+
+You can download the stable diffusion XL one from: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_base_1.0_0.9vae.safetensors
+
+
+RECOMMENDED WAY TO UPDATE:
+To update the ComfyUI code: update\update_comfyui.bat
+
+
+TO SHARE MODELS BETWEEN COMFYUI AND ANOTHER UI:
+In the ComfyUI directory you will find a file: extra_model_paths.yaml.example
+Rename this file to: extra_model_paths.yaml and edit it with your favorite text editor.
+
+
+

comfy/model_management.py

@@ -651,8 +651,7 @@ def ensure_pin_budget(size, evict_active=False):
     to_free = shortfall + PIN_PRESSURE_HYSTERESIS
     return free_pins(to_free, evict_active=evict_active) >= shortfall
 
-def ensure_pin_registerable(size, evict_active=True):
-    shortfall = TOTAL_PINNED_MEMORY + size - MAX_PINNED_MEMORY
+def free_registrations(shortfall, evict_active=True):
     if MAX_PINNED_MEMORY <= 0:
         return False
     if shortfall <= 0:
@@ -674,6 +673,9 @@ def ensure_pin_registerable(size, evict_active=True):
                     return True
     return shortfall <= REGISTERABLE_PIN_HYSTERESIS
 
+def ensure_pin_registerable(size, evict_active=True):
+    return free_registrations(TOTAL_PINNED_MEMORY + size - MAX_PINNED_MEMORY, evict_active=evict_active)
+
 class LoadedModel:
     def __init__(self, model: ModelPatcher):
         self._set_model(model)

comfy/pinned_memory.py

@@ -89,13 +89,26 @@ def pin_memory(module, subset="weights", size=None):
         not comfy.model_management.ensure_pin_registerable(registerable_size)):
         return _steal_pin(module, stack, buckets, size, priority)
 
+    extended = False
     try:
-        hostbuf.extend(size=size)
+        hostbuf.extend(size=size, register=False)
+        extended = True
+        pin = comfy_aimdo.torch.hostbuf_to_tensor(hostbuf)[offset:offset + size]
+        pin.untyped_storage()._comfy_hostbuf = hostbuf
+        if torch.cuda.cudart().cudaHostRegister(pin.data_ptr(), size, 1) != 0:
+            comfy.model_management.discard_cuda_async_error()
+            comfy.model_management.free_registrations(size)
+            if torch.cuda.cudart().cudaHostRegister(pin.data_ptr(), size, 1) != 0:
+                comfy.model_management.discard_cuda_async_error()
+                del pin
+                hostbuf.truncate(offset, do_unregister=False)
+                return _steal_pin(module, stack, buckets, size, priority)
     except RuntimeError:
+        if extended:
+            hostbuf.truncate(offset, do_unregister=False)
         return _steal_pin(module, stack, buckets, size, priority)
 
-    module._pin = comfy_aimdo.torch.hostbuf_to_tensor(hostbuf)[offset:offset + size]
-    module._pin.untyped_storage()._comfy_hostbuf = hostbuf
+    module._pin = pin
     stack.append((module, offset))
     module._pin_registered = True
     module._pin_stack_index = len(stack) - 1

comfy_api/latest/_io.py

@@ -755,6 +755,18 @@ class File3DKSPLAT(ComfyTypeIO):
     Type = File3D
 
 
+@comfytype(io_type="FILE_3D_SPLAT_ANY")
+class File3DSplatAny(ComfyTypeIO):
+    """General 3D Gaussian splat file type - accepts any supported splat container (.ply / .spz / .splat / .ksplat)."""
+    Type = File3D
+
+
+@comfytype(io_type="FILE_3D_POINT_CLOUD_ANY")
+class File3DPointCloudAny(ComfyTypeIO):
+    """General point cloud file type - accepts any supported point cloud container (currently .ply)."""
+    Type = File3D
+
+
 @comfytype(io_type="HOOKS")
 class Hooks(ComfyTypeIO):
     if TYPE_CHECKING:
@@ -2336,6 +2348,8 @@ __all__ = [
     "File3DSPLAT",
     "File3DSPZ",
     "File3DKSPLAT",
+    "File3DSplatAny",
+    "File3DPointCloudAny",
     "Hooks",
     "HookKeyframes",
     "TimestepsRange",

comfy_api_nodes/apis/gemini.py

@@ -108,13 +108,19 @@ class GeminiVideoMetadata(BaseModel):
     startOffset: GeminiOffset | None = Field(None)
 
 
+class GeminiThinkingConfig(BaseModel):
+    includeThoughts: bool | None = Field(None)
+    thinkingLevel: str = Field(...)
+
+
 class GeminiGenerationConfig(BaseModel):
-    maxOutputTokens: int | None = Field(None, ge=16, le=8192)
+    maxOutputTokens: int | None = Field(None, ge=16, le=65536)
     seed: int | None = Field(None)
     stopSequences: list[str] | None = Field(None)
     temperature: float | None = Field(None, ge=0.0, le=2.0)
     topK: int | None = Field(None, ge=1)
     topP: float | None = Field(None, ge=0.0, le=1.0)
+    thinkingConfig: GeminiThinkingConfig | None = Field(None)
 
 
 class GeminiImageOutputOptions(BaseModel):
@@ -128,11 +134,6 @@ class GeminiImageConfig(BaseModel):
     imageOutputOptions: GeminiImageOutputOptions = Field(default_factory=GeminiImageOutputOptions)
 
 
-class GeminiThinkingConfig(BaseModel):
-    includeThoughts: bool | None = Field(None)
-    thinkingLevel: str = Field(...)
-
-
 class GeminiImageGenerationConfig(GeminiGenerationConfig):
     responseModalities: list[str] | None = Field(None)
     imageConfig: GeminiImageConfig | None = Field(None)

comfy_api_nodes/nodes_gemini.py

@@ -8,7 +8,7 @@ import os
 from enum import Enum
 from fnmatch import fnmatch
 from io import BytesIO
-from typing import Literal
+from typing import Any, Literal
 
 import torch
 from typing_extensions import override
@@ -19,6 +19,7 @@ from comfy_api_nodes.apis.gemini import (
     GeminiContent,
     GeminiFileData,
     GeminiGenerateContentRequest,
+    GeminiGenerationConfig,
     GeminiGenerateContentResponse,
     GeminiImageConfig,
     GeminiImageGenerateContentRequest,
@@ -40,13 +41,18 @@ from comfy_api_nodes.util import (
     get_number_of_images,
     sync_op,
     tensor_to_base64_string,
+    upload_audio_to_comfyapi,
+    upload_image_to_comfyapi,
     upload_images_to_comfyapi,
+    upload_video_to_comfyapi,
     validate_string,
     video_to_base64_string,
 )
 
 GEMINI_BASE_ENDPOINT = "/proxy/vertexai/gemini"
 GEMINI_MAX_INPUT_FILE_SIZE = 20 * 1024 * 1024  # 20 MB
+GEMINI_URL_INPUT_BUDGET = 10
+GEMINI_MAX_INLINE_BYTES = 18 * 1024 * 1024
 GEMINI_IMAGE_SYS_PROMPT = (
     "You are an expert image-generation engine. You must ALWAYS produce an image.\n"
     "Interpret all user input—regardless of "
@@ -285,6 +291,140 @@ def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | N
     return final_price / 1_000_000.0
 
 
+def create_video_parts(video_input: Input.Video) -> list[GeminiPart]:
+    """Convert a single video input to Gemini API compatible parts (inline MP4/H.264)."""
+    base_64_string = video_to_base64_string(
+        video_input, container_format=Types.VideoContainer.MP4, codec=Types.VideoCodec.H264
+    )
+    return [
+        GeminiPart(
+            inlineData=GeminiInlineData(
+                mimeType=GeminiMimeType.video_mp4,
+                data=base_64_string,
+            )
+        )
+    ]
+
+
+def create_audio_parts(audio_input: Input.Audio) -> list[GeminiPart]:
+    """Convert an audio input to Gemini API compatible parts (one inline MP3 part per batch item)."""
+    audio_parts: list[GeminiPart] = []
+    for batch_index in range(audio_input["waveform"].shape[0]):
+        # Recreate an IO.AUDIO object for the given batch dimension index
+        audio_at_index = Input.Audio(
+            waveform=audio_input["waveform"][batch_index].unsqueeze(0),
+            sample_rate=audio_input["sample_rate"],
+        )
+        # Convert to MP3 format for compatibility with Gemini API
+        audio_bytes = audio_to_base64_string(
+            audio_at_index,
+            container_format="mp3",
+            codec_name="libmp3lame",
+        )
+        audio_parts.append(
+            GeminiPart(
+                inlineData=GeminiInlineData(
+                    mimeType=GeminiMimeType.audio_mp3,
+                    data=audio_bytes,
+                )
+            )
+        )
+    return audio_parts
+
+
+def _flatten_images(images: list[Input.Image]) -> list[torch.Tensor]:
+    """Expand any batched image tensors into individual (H, W, C) frames, preserving order."""
+    frames: list[torch.Tensor] = []
+    for img in images:
+        if len(img.shape) == 4:
+            frames.extend(img[i] for i in range(img.shape[0]))
+        else:
+            frames.append(img)
+    return frames
+
+
+def _flatten_audio(audios: list[Input.Audio]) -> list[Input.Audio]:
+    """Expand any batched audio inputs into individual single-clip audio inputs, preserving order."""
+    clips: list[Input.Audio] = []
+    for audio in audios:
+        waveform = audio["waveform"]
+        for i in range(waveform.shape[0]):
+            clips.append(Input.Audio(waveform=waveform[i].unsqueeze(0), sample_rate=audio["sample_rate"]))
+    return clips
+
+
+async def _media_url_part(cls: type[IO.ComfyNode], kind: str, payload: Any) -> GeminiPart:
+    """Upload a single media unit to ComfyAPI storage and return a fileData (URL) part."""
+    if kind == "image":
+        url = await upload_image_to_comfyapi(cls, payload, mime_type="image/png", wait_label="Uploading image")
+        return GeminiPart(fileData=GeminiFileData(mimeType=GeminiMimeType.image_png, fileUri=url))
+    if kind == "audio":
+        url = await upload_audio_to_comfyapi(
+            cls, payload, container_format="mp3", codec_name="libmp3lame", mime_type="audio/mp3"
+        )
+        return GeminiPart(fileData=GeminiFileData(mimeType=GeminiMimeType.audio_mp3, fileUri=url))
+    url = await upload_video_to_comfyapi(cls, payload, wait_label="Uploading video")
+    return GeminiPart(fileData=GeminiFileData(mimeType=GeminiMimeType.video_mp4, fileUri=url))
+
+
+def _media_inline_part(kind: str, payload: Any) -> tuple[GeminiPart, int]:
+    """Encode a single media unit as an inline base64 part; returns (part, base64_length)."""
+    if kind == "image":
+        data = tensor_to_base64_string(payload, mime_type="image/webp")
+        mime = GeminiMimeType.image_webp
+    elif kind == "audio":
+        data = audio_to_base64_string(payload, container_format="mp3", codec_name="libmp3lame")
+        mime = GeminiMimeType.audio_mp3
+    else:
+        data = video_to_base64_string(
+            payload, container_format=Types.VideoContainer.MP4, codec=Types.VideoCodec.H264
+        )
+        mime = GeminiMimeType.video_mp4
+    return GeminiPart(inlineData=GeminiInlineData(mimeType=mime, data=data)), len(data)
+
+
+async def build_gemini_media_parts(
+    cls: type[IO.ComfyNode],
+    images: list[Input.Image],
+    audios: list[Input.Audio],
+    videos: list[Input.Video],
+    *,
+    url_budget: int = GEMINI_URL_INPUT_BUDGET,
+    max_inline_bytes: int = GEMINI_MAX_INLINE_BYTES,
+) -> list[GeminiPart]:
+    """Build Gemini parts for multimodal inputs (images, audio, video).
+
+    fileData URLs are preferred for every media type: the upload is fetched directly by the
+    model, keeping the request body tiny regardless of media size. The URL budget is shared
+    across all media and assigned largest-first (video, then audio, then images), so that if it
+    is ever exhausted the inline-base64 overflow is limited to the smallest items. Total inline
+    payload is capped by `max_inline_bytes`.
+    """
+    units: list[tuple[str, Any]] = (
+        [("video", v) for v in videos]
+        + [("audio", a) for a in _flatten_audio(audios)]
+        + [("image", f) for f in _flatten_images(images)]
+    )
+
+    parts: list[GeminiPart] = []
+    url_used = 0
+    inline_bytes = 0
+    for kind, payload in units:
+        if url_used < url_budget:
+            parts.append(await _media_url_part(cls, kind, payload))
+            url_used += 1
+            continue
+        part, nbytes = _media_inline_part(kind, payload)
+        inline_bytes += nbytes
+        if inline_bytes > max_inline_bytes:
+            raise ValueError(
+                f"Too much media to send inline (over {max_inline_bytes // (1024 * 1024)}MB after the first "
+                f"{url_budget} inputs are uploaded as URLs). Reduce the number or size of attached media."
+            )
+        parts.append(part)
+    return parts
+
+
 class GeminiNode(IO.ComfyNode):
     """
     Node to generate text responses from a Gemini model.
@@ -407,58 +547,9 @@ class GeminiNode(IO.ComfyNode):
                 )
                 """,
             ),
+            is_deprecated=True,
         )
 
-    @classmethod
-    def create_video_parts(cls, video_input: Input.Video) -> list[GeminiPart]:
-        """Convert video input to Gemini API compatible parts."""
-
-        base_64_string = video_to_base64_string(
-            video_input, container_format=Types.VideoContainer.MP4, codec=Types.VideoCodec.H264
-        )
-        return [
-            GeminiPart(
-                inlineData=GeminiInlineData(
-                    mimeType=GeminiMimeType.video_mp4,
-                    data=base_64_string,
-                )
-            )
-        ]
-
-    @classmethod
-    def create_audio_parts(cls, audio_input: Input.Audio) -> list[GeminiPart]:
-        """
-        Convert audio input to Gemini API compatible parts.
-
-        Args:
-            audio_input: Audio input from ComfyUI, containing waveform tensor and sample rate.
-
-        Returns:
-            List of GeminiPart objects containing the encoded audio.
-        """
-        audio_parts: list[GeminiPart] = []
-        for batch_index in range(audio_input["waveform"].shape[0]):
-            # Recreate an IO.AUDIO object for the given batch dimension index
-            audio_at_index = Input.Audio(
-                waveform=audio_input["waveform"][batch_index].unsqueeze(0),
-                sample_rate=audio_input["sample_rate"],
-            )
-            # Convert to MP3 format for compatibility with Gemini API
-            audio_bytes = audio_to_base64_string(
-                audio_at_index,
-                container_format="mp3",
-                codec_name="libmp3lame",
-            )
-            audio_parts.append(
-                GeminiPart(
-                    inlineData=GeminiInlineData(
-                        mimeType=GeminiMimeType.audio_mp3,
-                        data=audio_bytes,
-                    )
-                )
-            )
-        return audio_parts
-
     @classmethod
     async def execute(
         cls,
@@ -482,9 +573,9 @@ class GeminiNode(IO.ComfyNode):
         if images is not None:
             parts.extend(await create_image_parts(cls, images))
         if audio is not None:
-            parts.extend(cls.create_audio_parts(audio))
+            parts.extend(create_audio_parts(audio))
         if video is not None:
-            parts.extend(cls.create_video_parts(video))
+            parts.extend(create_video_parts(video))
         if files is not None:
             parts.extend(files)
 
@@ -512,6 +603,210 @@ class GeminiNode(IO.ComfyNode):
         return IO.NodeOutput(output_text or "Empty response from Gemini model...")
 
 
+GEMINI_V2_MODELS: dict[str, str] = {
+    "Gemini 3.1 Pro": "gemini-3.1-pro-preview",
+    "Gemini 3.1 Flash-Lite": "gemini-3.1-flash-lite-preview",
+}
+
+
+def _gemini_text_model_inputs(thinking_default: str) -> list[Input]:
+    """Per-model inputs revealed by the model DynamicCombo (shared media + sampling controls)."""
+    return [
+        IO.Autogrow.Input(
+            "images",
+            template=IO.Autogrow.TemplateNames(
+                IO.Image.Input("image"),
+                names=[f"image_{i}" for i in range(1, 17)],
+                min=0,
+            ),
+            tooltip="Optional image(s) to use as context for the model. Up to 16 images.",
+        ),
+        IO.Autogrow.Input(
+            "audio",
+            template=IO.Autogrow.TemplateNames(
+                IO.Audio.Input("audio"),
+                names=["audio_1"],
+                min=0,
+            ),
+            tooltip="Optional audio clip to use as context for the model.",
+        ),
+        IO.Autogrow.Input(
+            "video",
+            template=IO.Autogrow.TemplateNames(
+                IO.Video.Input("video"),
+                names=["video_1"],
+                min=0,
+            ),
+            tooltip="Optional video clip to use as context for the model.",
+        ),
+        IO.Custom("GEMINI_INPUT_FILES").Input(
+            "files",
+            optional=True,
+            tooltip="Optional file(s) to use as context for the model. "
+            "Accepts inputs from the Gemini Input Files node.",
+        ),
+        IO.Combo.Input(
+            "thinking_level",
+            options=["LOW", "HIGH"],
+            default=thinking_default,
+            tooltip="How hard the model reasons internally before answering. "
+            "HIGH improves quality on difficult tasks but costs more (thinking) tokens and is slower.",
+        ),
+        IO.Float.Input(
+            "temperature",
+            default=1.0,
+            min=0.0,
+            max=2.0,
+            step=0.01,
+            tooltip="Controls randomness. Lower is more focused/deterministic, higher is more creative.",
+            advanced=True,
+        ),
+        IO.Float.Input(
+            "top_p",
+            default=0.95,
+            min=0.0,
+            max=1.0,
+            step=0.01,
+            tooltip="Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top_p.",
+            advanced=True,
+        ),
+        IO.Int.Input(
+            "max_output_tokens",
+            default=32768,
+            min=16,
+            max=65536,
+            tooltip="Maximum tokens to generate, including the model's internal thinking. "
+            "With thinking_level HIGH, a low value can leave no room for the answer; raise this if "
+            "responses come back empty or truncated. The model stops early when finished, so a higher "
+            "cap costs nothing extra for short replies.",
+            advanced=True,
+        ),
+    ]
+
+
+class GeminiNodeV2(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="GeminiNodeV2",
+            display_name="Google Gemini",
+            category="partner/text/Gemini",
+            essentials_category="Text Generation",
+            description="Generate text responses with Google's Gemini models. Provide a text prompt and, "
+            "optionally, one or more images, audio clips, videos, or files as multimodal context.",
+            inputs=[
+                IO.String.Input(
+                    "prompt",
+                    multiline=True,
+                    default="",
+                    tooltip="Text input to the model. Include detailed instructions, questions, or context.",
+                ),
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option("Gemini 3.1 Pro", _gemini_text_model_inputs("HIGH")),
+                        IO.DynamicCombo.Option("Gemini 3.1 Flash-Lite", _gemini_text_model_inputs("LOW")),
+                    ],
+                    tooltip="The Gemini model used to generate the response.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=42,
+                    min=0,
+                    max=2147483647,
+                    control_after_generate=True,
+                    tooltip="Seed for sampling. Set to 0 for a random seed. Deterministic output isn't guaranteed.",
+                ),
+                IO.String.Input(
+                    "system_prompt",
+                    multiline=True,
+                    default="",
+                    optional=True,
+                    advanced=True,
+                    tooltip="Foundational instructions that dictate the model's behavior.",
+                ),
+            ],
+            outputs=[
+                IO.String.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["model"]),
+                expr="""
+                (
+                  $m := widgets.model;
+                  $contains($m, "lite") ? {
+                    "type": "list_usd",
+                    "usd": [0.00025, 0.0015],
+                    "format": { "approximate": true, "separator": "-", "suffix": " per 1K tokens" }
+                  } : {
+                    "type": "list_usd",
+                    "usd": [0.002, 0.012],
+                    "format": { "approximate": true, "separator": "-", "suffix": " per 1K tokens" }
+                  }
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        prompt: str,
+        model: dict,
+        seed: int,
+        system_prompt: str = "",
+    ) -> IO.NodeOutput:
+        validate_string(prompt, strip_whitespace=True, min_length=1)
+        model_id = GEMINI_V2_MODELS[model["model"]]
+
+        parts: list[GeminiPart] = [GeminiPart(text=prompt)]
+        images = [t for t in (model.get("images") or {}).values() if t is not None]
+        audios = [a for a in (model.get("audio") or {}).values() if a is not None]
+        videos = [v for v in (model.get("video") or {}).values() if v is not None]
+        if images or audios or videos:
+            parts.extend(await build_gemini_media_parts(cls, images, audios, videos))
+        files = model.get("files")
+        if files is not None:
+            parts.extend(files)
+
+        gemini_system_prompt = None
+        if system_prompt:
+            gemini_system_prompt = GeminiSystemInstructionContent(parts=[GeminiTextPart(text=system_prompt)], role=None)
+
+        response = await sync_op(
+            cls,
+            endpoint=ApiEndpoint(path=f"{GEMINI_BASE_ENDPOINT}/{model_id}", method="POST"),
+            data=GeminiGenerateContentRequest(
+                contents=[
+                    GeminiContent(
+                        role=GeminiRole.user,
+                        parts=parts,
+                    )
+                ],
+                generationConfig=GeminiGenerationConfig(
+                    temperature=model["temperature"],
+                    topP=model["top_p"],
+                    maxOutputTokens=model["max_output_tokens"],
+                    seed=seed if seed > 0 else None,
+                    thinkingConfig=GeminiThinkingConfig(thinkingLevel=model["thinking_level"]),
+                ),
+                systemInstruction=gemini_system_prompt,
+            ),
+            response_model=GeminiGenerateContentResponse,
+            price_extractor=calculate_tokens_price,
+        )
+
+        output_text = get_text_from_response(response)
+        return IO.NodeOutput(output_text or "Empty response from Gemini model...")
+
+
 class GeminiInputFiles(IO.ComfyNode):
     """
     Loads and formats input files for use with the Gemini API.
@@ -1129,6 +1424,26 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
                     tooltip="Foundational instructions that dictate an AI's behavior.",
                     advanced=True,
                 ),
+                IO.Float.Input(
+                    "temperature",
+                    default=1.0,
+                    min=0.0,
+                    max=2.0,
+                    step=0.01,
+                    optional=True,
+                    tooltip="Controls randomness in generation. Lower is more focused/deterministic.",
+                    advanced=True,
+                ),
+                IO.Float.Input(
+                    "top_p",
+                    default=0.95,
+                    min=0.0,
+                    max=1.0,
+                    step=0.01,
+                    optional=True,
+                    tooltip="Nucleus sampling threshold. Lower is more focused, higher more diverse.",
+                    advanced=True,
+                ),
             ],
             outputs=[
                 IO.Image.Output(),
@@ -1165,6 +1480,8 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
         seed: int,
         response_modalities: str,
         system_prompt: str = "",
+        temperature: float = 1.0,
+        top_p: float = 0.95,
     ) -> IO.NodeOutput:
         validate_string(prompt, strip_whitespace=True, min_length=1)
         model_choice = model["model"]
@@ -1204,6 +1521,8 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
                     responseModalities=(["IMAGE"] if response_modalities == "IMAGE" else ["TEXT", "IMAGE"]),
                     imageConfig=image_config,
                     thinkingConfig=GeminiThinkingConfig(thinkingLevel=model["thinking_level"]),
+                    temperature=temperature,
+                    topP=top_p,
                 ),
                 systemInstruction=gemini_system_prompt,
             ),
@@ -1222,6 +1541,7 @@ class GeminiExtension(ComfyExtension):
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
         return [
             GeminiNode,
+            GeminiNodeV2,
             GeminiImage,
             GeminiImage2,
             GeminiNanoBanana2,

comfy_extras/nodes_custom_sampler.py

@@ -933,9 +933,10 @@ class Guider_DualModel(comfy.samplers.CFGGuider):
 
     def predict_noise(self, x, timestep, model_options={}, seed=None):
         positive = self.conds.get("positive", None)
-        if self.uncond_inner is None:  # cfg == 1 or no negative -> single model, cond only
-            return comfy.samplers.calc_cond_batch(self.inner_model, [positive], x, timestep, model_options)[0]
         cond = comfy.samplers.calc_cond_batch(self.inner_model, [positive], x, timestep, model_options)[0]
+        # uncond model not loaded (base cfg==1/no negative), or cfg driven to 1.0 this step -> single model, cond only
+        if self.uncond_inner is None or (math.isclose(self.cfg, 1.0) and not model_options.get("disable_cfg1_optimization", False)):
+            return cond
 
         uncond_model_options = model_options
         if "multigpu_clones" in model_options: # TODO: support multigpu instead of just running uncond on a single GPU
@@ -1140,7 +1141,7 @@ class CFGOverride(io.ComfyNode):
         return io.Schema(
             node_id="CFGOverride",
             display_name="CFG Override",
-            description="Override cfg to a fixed value over a [start, end] percent slice of the steps. "
+            description="Override cfg to a fixed value over a [start, end] percent (sigma) range. "
                         "With multiple overrides, the one nearest the sampler wins on overlap.",
             category="sampling/custom_sampling",
             inputs=[

comfy_extras/nodes_gaussian_splat.py

@@ -488,7 +488,7 @@ class SplatToFile3D(IO.ComfyNode):
                                        "spz: Niantic gzip-compressed (~10x smaller), base color only "
                                        ),
             ],
-            outputs=[IO.File3DAny.Output(display_name="model_3d")],
+            outputs=[IO.File3DSplatAny.Output(display_name="model_3d")],
         )
 
     @classmethod
@@ -516,7 +516,7 @@ class File3DToSplat(IO.ComfyNode):
             inputs=[
                 IO.MultiType.Input(
                     IO.File3DAny.Input("model_3d"),
-                    types=[IO.File3DPLY, IO.File3DSPLAT, IO.File3DKSPLAT, IO.File3DSPZ],
+                    types=[IO.File3DSplatAny, IO.File3DPLY, IO.File3DSPLAT, IO.File3DKSPLAT, IO.File3DSPZ],
                     tooltip="A gaussian splat 3D file",
                 ),
             ],

comfy_extras/nodes_load_3d.py

@@ -51,6 +51,14 @@ class Load3D(IO.ComfyNode):
             ],
         )
 
+    @classmethod
+    def validate_inputs(cls, model_file, **kwargs) -> bool | str:
+        if not model_file or model_file == "none":
+            return True
+        if not folder_paths.exists_annotated_filepath(model_file):
+            return f"Invalid 3D model file: {model_file}"
+        return True
+
     @classmethod
     def execute(cls, model_file, image, **kwargs) -> IO.NodeOutput:
         image_path = folder_paths.get_annotated_filepath(image['image'])
@@ -136,7 +144,7 @@ class Preview3DAdvanced(IO.ComfyNode):
             is_output_node=True,
             inputs=[
                 IO.MultiType.Input(
-                    "model_file",
+                    "model_3d",
                     types=[
                         IO.File3DGLB,
                         IO.File3DGLTF,
@@ -148,14 +156,14 @@ class Preview3DAdvanced(IO.ComfyNode):
                     ],
                     tooltip="3D model file from an upstream 3D node.",
                 ),
-                IO.Load3D.Input("image"),
+                IO.Load3D.Input("viewport_state"),
                 IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
                 IO.Load3DModelInfo.Input("model_3d_info", optional=True, advanced=True),
                 IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
                 IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
             ],
             outputs=[
-                IO.File3DAny.Output(display_name="model_file"),
+                IO.File3DAny.Output(display_name="model_3d"),
                 IO.Load3DCamera.Output(display_name="camera_info"),
                 IO.Load3DModelInfo.Output(display_name="model_3d_info"),
                 IO.Int.Output(display_name="width"),
@@ -164,16 +172,143 @@ class Preview3DAdvanced(IO.ComfyNode):
         )
 
     @classmethod
-    def execute(cls, model_file: Types.File3D, image, width: int, height: int, **kwargs) -> IO.NodeOutput:
-        filename = f"preview3d_advanced_{uuid.uuid4().hex}.{model_file.format}"
-        model_file.save_to(os.path.join(folder_paths.get_output_directory(), filename))
+    def execute(cls, model_3d: Types.File3D, viewport_state, width: int, height: int, **kwargs) -> IO.NodeOutput:
+        filename = f"preview3d_advanced_{uuid.uuid4().hex}.{model_3d.format}"
+        model_3d.save_to(os.path.join(folder_paths.get_temp_directory(), filename))
 
         camera_info_input = kwargs.get("camera_info", None)
-        camera_info = camera_info_input if camera_info_input is not None else image['camera_info']
+        camera_info = camera_info_input if camera_info_input is not None else viewport_state['camera_info']
         model_3d_info_input = kwargs.get("model_3d_info", None)
-        model_3d_info = model_3d_info_input if model_3d_info_input is not None else image.get('model_3d_info', [])
+        model_3d_info = model_3d_info_input if model_3d_info_input is not None else viewport_state.get('model_3d_info', [])
         return IO.NodeOutput(
-            model_file,
+            model_3d,
+            camera_info,
+            model_3d_info,
+            width,
+            height,
+            ui=UI.PreviewUI3DAdvanced(filename, camera_info, model_3d_info),
+        )
+
+
+class PreviewGaussianSplat(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="PreviewGaussianSplat",
+            display_name="Preview Splat",
+            category="3d",
+            is_experimental=True,
+            is_output_node=True,
+            search_aliases=[
+                "view splat",
+                "view gaussian",
+                "view gaussian splat",
+                "preview gaussian",
+                "preview gaussian splat",
+                "view 3dgs",
+                "preview 3dgs",
+                "preview ply",
+                "preview spz",
+                "preview splat",
+                "preview ksplat",
+            ],
+            inputs=[
+                IO.MultiType.Input(
+                    "model_3d",
+                    types=[
+                        IO.File3DSplatAny,
+                        IO.File3DPLY,
+                        IO.File3DSPLAT,
+                        IO.File3DSPZ,
+                        IO.File3DKSPLAT,
+                    ],
+                    tooltip="A gaussian splat 3D file.",
+                ),
+                IO.Load3D.Input("viewport_state"),
+                IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
+                IO.Load3DModelInfo.Input("model_3d_info", optional=True, advanced=True),
+                IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
+                IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
+            ],
+            outputs=[
+                IO.File3DSplatAny.Output(display_name="model_3d"),
+                IO.Load3DCamera.Output(display_name="camera_info"),
+                IO.Load3DModelInfo.Output(display_name="model_3d_info"),
+                IO.Int.Output(display_name="width"),
+                IO.Int.Output(display_name="height"),
+            ],
+        )
+
+    @classmethod
+    def execute(cls, model_3d: Types.File3D, viewport_state, width: int, height: int, **kwargs) -> IO.NodeOutput:
+        filename = f"preview_splat_{uuid.uuid4().hex}.{model_3d.format}"
+        model_3d.save_to(os.path.join(folder_paths.get_temp_directory(), filename))
+
+        camera_info_input = kwargs.get("camera_info", None)
+        camera_info = camera_info_input if camera_info_input is not None else viewport_state['camera_info']
+        model_3d_info_input = kwargs.get("model_3d_info", None)
+        model_3d_info = model_3d_info_input if model_3d_info_input is not None else viewport_state.get('model_3d_info', [])
+        return IO.NodeOutput(
+            model_3d,
+            camera_info,
+            model_3d_info,
+            width,
+            height,
+            ui=UI.PreviewUI3DAdvanced(filename, camera_info, model_3d_info),
+        )
+
+
+class PreviewPointCloud(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="PreviewPointCloud",
+            display_name="Preview Point Cloud",
+            category="3d",
+            is_experimental=True,
+            is_output_node=True,
+            search_aliases=[
+                "view point cloud",
+                "view pointcloud",
+                "preview point cloud",
+                "preview pointcloud",
+                "preview ply",
+            ],
+            inputs=[
+                IO.MultiType.Input(
+                    "model_3d",
+                    types=[
+                        IO.File3DPointCloudAny,
+                        IO.File3DPLY,
+                    ],
+                    tooltip="Point cloud file (.ply)",
+                ),
+                IO.Load3D.Input("viewport_state"),
+                IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
+                IO.Load3DModelInfo.Input("model_3d_info", optional=True, advanced=True),
+                IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
+                IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
+            ],
+            outputs=[
+                IO.File3DPointCloudAny.Output(display_name="model_3d"),
+                IO.Load3DCamera.Output(display_name="camera_info"),
+                IO.Load3DModelInfo.Output(display_name="model_3d_info"),
+                IO.Int.Output(display_name="width"),
+                IO.Int.Output(display_name="height"),
+            ],
+        )
+
+    @classmethod
+    def execute(cls, model_3d: Types.File3D, viewport_state, width: int, height: int, **kwargs) -> IO.NodeOutput:
+        filename = f"preview_pointcloud_{uuid.uuid4().hex}.{model_3d.format}"
+        model_3d.save_to(os.path.join(folder_paths.get_temp_directory(), filename))
+
+        camera_info_input = kwargs.get("camera_info", None)
+        camera_info = camera_info_input if camera_info_input is not None else viewport_state['camera_info']
+        model_3d_info_input = kwargs.get("model_3d_info", None)
+        model_3d_info = model_3d_info_input if model_3d_info_input is not None else viewport_state.get('model_3d_info', [])
+        return IO.NodeOutput(
+            model_3d,
             camera_info,
             model_3d_info,
             width,
@@ -189,6 +324,8 @@ class Load3DExtension(ComfyExtension):
             Load3D,
             Preview3D,
             Preview3DAdvanced,
+            PreviewGaussianSplat,
+            PreviewPointCloud,
         ]
 
 

comfy_extras/nodes_save_3d.py

@@ -337,6 +337,12 @@ class SaveGLB(IO.ComfyNode):
                         IO.File3DFBX,
                         IO.File3DSTL,
                         IO.File3DUSDZ,
+                        IO.File3DPLY,
+                        IO.File3DSPLAT,
+                        IO.File3DSPZ,
+                        IO.File3DKSPLAT,
+                        IO.File3DSplatAny,
+                        IO.File3DPointCloudAny,
                         IO.File3DAny,
                     ],
                     tooltip="Mesh or 3D file to save",

openapi.yaml

@@ -3,6 +3,11 @@ components:
         Asset:
             description: Represents a user-owned asset (image, video, or other generated output).
             properties:
+                asset_hash:
+                    deprecated: true
+                    description: 'Deprecated: use hash instead. Blake3 hash of the asset content.'
+                    pattern: ^blake3:[a-f0-9]{64}$
+                    type: string
                 created_at:
                     description: Timestamp when the asset was created
                     format: date-time
@@ -12,7 +17,7 @@ components:
                     nullable: true
                     type: string
                 hash:
-                    description: Blake3 hash of the asset content.
+                    description: Blake3 hash of the asset content. Preferred over asset_hash.
                     pattern: ^blake3:[a-f0-9]{64}$
                     type: string
                 id:
@@ -134,12 +139,17 @@ components:
         AssetUpdated:
             description: Response returned when an existing asset is successfully updated.
             properties:
+                asset_hash:
+                    deprecated: true
+                    description: 'Deprecated: use hash instead. Blake3 hash of the asset content.'
+                    pattern: ^blake3:[a-f0-9]{64}$
+                    type: string
                 display_name:
                     description: Display name of the asset. Mirrors name for backwards compatibility.
                     nullable: true
                     type: string
                 hash:
-                    description: Blake3 hash of the asset content.
+                    description: Blake3 hash of the asset content. Preferred over asset_hash.
                     pattern: ^blake3:[a-f0-9]{64}$
                     type: string
                 id:
@@ -1508,11 +1518,17 @@ paths:
                   schema:
                     default: true
                     type: boolean
-                - description: Filter assets by exact content hash.
+                - description: Filter assets by exact content hash. Preferred over asset_hash.
                   in: query
                   name: hash
                   schema:
                     type: string
+                - deprecated: true
+                  description: 'Deprecated: use hash instead. Filter assets by exact content hash.'
+                  in: query
+                  name: asset_hash
+                  schema:
+                    type: string
                 - description: |
                     Opaque cursor for keyset pagination. Pass the `next_cursor` value
                     from the previous response to fetch the next page. When provided,
@@ -1555,12 +1571,42 @@ paths:
                 - file
         post:
             description: |
-                Creates a new asset from a direct file upload (multipart/form-data) with associated metadata.
+                Uploads a new asset to the system with associated metadata.
+                Supports two upload methods:
+                1. Direct file upload (multipart/form-data)
+                2. URL-based upload (application/json with source: "url")
 
                 If an asset with the same hash already exists, returns the existing asset.
-            operationId: createAsset
+            operationId: uploadAsset
             requestBody:
                 content:
+                    application/json:
+                        schema:
+                            properties:
+                                name:
+                                    description: Display name for the asset (used to determine file extension)
+                                    type: string
+                                preview_id:
+                                    description: Optional preview asset ID
+                                    format: uuid
+                                    type: string
+                                tags:
+                                    description: Freeform tags for the asset. Common types include "models", "input", "output", and "temp", but any tag can be used in any order.
+                                    items:
+                                        type: string
+                                    type: array
+                                url:
+                                    description: HTTP/HTTPS URL to download the asset from
+                                    format: uri
+                                    type: string
+                                user_metadata:
+                                    additionalProperties: true
+                                    description: Custom metadata to store with the asset
+                                    type: object
+                            required:
+                                - url
+                                - name
+                            type: object
                     multipart/form-data:
                         schema:
                             properties:
@@ -1568,10 +1614,6 @@ paths:
                                     description: The asset file to upload
                                     format: binary
                                     type: string
-                                hash:
-                                    description: Content hash of the file.
-                                    pattern: ^(blake3|sha256):[a-f0-9]{64}$
-                                    type: string
                                 id:
                                     description: Optional asset ID for idempotent creation. If provided and asset exists, returns existing asset.
                                     format: uuid
@@ -1587,8 +1629,10 @@ paths:
                                     format: uuid
                                     type: string
                                 tags:
-                                    description: JSON-encoded array of freeform tag strings, e.g. '["models","checkpoint"]'. Common types include "models", "input", "output", and "temp", but any tag can be used in any order.
-                                    type: string
+                                    description: Freeform tags for the asset. Common types include "models", "input", "output", and "temp", but any tag can be used in any order.
+                                    items:
+                                        type: string
+                                    type: array
                                 user_metadata:
                                     description: Custom JSON metadata as a string
                                     type: string
@@ -1608,13 +1652,25 @@ paths:
                         application/json:
                             schema:
                                 $ref: '#/components/schemas/ErrorResponse'
-                    description: Invalid request (bad file, invalid content type, etc.)
+                    description: Invalid request (bad file, invalid URL, invalid content type, etc.)
                 "401":
                     content:
                         application/json:
                             schema:
                                 $ref: '#/components/schemas/ErrorResponse'
                     description: Unauthorized
+                "403":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Source URL requires authentication or access denied
+                "404":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Source URL not found
                 "413":
                     content:
                         application/json:
@@ -1627,13 +1683,19 @@ paths:
                             schema:
                                 $ref: '#/components/schemas/ErrorResponse'
                     description: Unsupported media type
+                "422":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Download failed due to network error or timeout
                 "500":
                     content:
                         application/json:
                             schema:
                                 $ref: '#/components/schemas/ErrorResponse'
                     description: Internal server error
-            summary: Create a new asset
+            summary: Upload a new asset
             tags:
                 - file
     /api/assets/{id}:
@@ -1721,7 +1783,7 @@ paths:
             description: |
                 Updates an asset's metadata. At least one field must be provided.
                 Only name, mime_type, preview_id, and user_metadata can be updated.
-                For tag management, use POST (add) and DELETE (remove) /api/assets/{id}/tags.
+                For tag management, use the dedicated PUT /api/assets/{id}/tags endpoint.
             operationId: updateAsset
             parameters:
                 - description: Asset ID
@@ -1920,6 +1982,76 @@ paths:
             summary: Add tags to asset
             tags:
                 - file
+        put:
+            description: Adds and removes tags from an asset in a single operation
+            operationId: updateAssetTags
+            parameters:
+                - description: Asset ID
+                  in: path
+                  name: id
+                  required: true
+                  schema:
+                    format: uuid
+                    type: string
+            requestBody:
+                content:
+                    application/json:
+                        schema:
+                            description: At least one of add or remove must contain items. Empty arrays are allowed when the other array has items.
+                            minProperties: 1
+                            properties:
+                                add:
+                                    description: Tags to add to the asset. Can be empty if remove has items.
+                                    items:
+                                        type: string
+                                    type: array
+                                remove:
+                                    description: Tags to remove from the asset. Can be empty if add has items.
+                                    items:
+                                        type: string
+                                    type: array
+                            type: object
+                required: true
+            responses:
+                "200":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/TagsModificationResponse'
+                    description: Tags updated successfully
+                "400":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Invalid request
+                "401":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Unauthorized
+                "404":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Asset not found
+                "422":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Reserved tag validation error
+                "500":
+                    content:
+                        application/json:
+                            schema:
+                                $ref: '#/components/schemas/ErrorResponse'
+                    description: Internal server error
+            summary: Update asset tags
+            tags:
+                - file
     /api/assets/from-hash:
         post:
             description: |

requirements.txt

@@ -23,7 +23,7 @@ SQLAlchemy>=2.0.0
 filelock
 av>=16.0.0
 comfy-kitchen==0.2.10
-comfy-aimdo==0.4.8
+comfy-aimdo==0.4.9
 requests
 simpleeval>=1.0.0
 blake3