diff --git a/CHANGELOG.md b/CHANGELOG.md
index 6d8e0d5..f1e252b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,33 @@
 # Changelog
 
+## v0.2.0 — 2026-09-14
+
+### Added
+
+- **gpt-image-2.5** — `gpt-image-2.5-flare` (new default) and `gpt-image-2.5-sunburst`, with
+  custom `WxH` sizes, `transparent` background, and the new `xhigh` / `max` quality tiers.
+  gpt-image-2 falls back to `high` when an extended tier is selected.
+- **`mask` output on both nodes** — ComfyUI IMAGE is RGB, so a `transparent` background used to
+  be flattened onto black and lost. Alpha now comes out as a MASK (`1 - alpha`, matching
+  `LoadImage`); pair it with **Join Image with Alpha** to save a transparent PNG. Opaque output
+  yields an all-zero mask. **Both nodes gained a second output, so saved workflows will show the
+  node as changed.**
+
+### Fixed
+
+- **`custom_width` / `custom_height` minimum lowered from 1024 to 480** — the widget floor was
+  stricter than `validate_custom_dimensions()`, so legal sizes such as `1536x864` and `1440x480`
+  could not be entered and silently snapped up to 1024.
+
+### Removed
+
+- **gpt-image-1 and gpt-image-1.5** — OpenAI shuts them down on 2026-10-23 and 2026-12-01
+  respectively. **Saved workflows that select either model will need their `model` widget
+  re-picked.**
+- **`input_fidelity`** — it only ever applied to gpt-image-1.x; gpt-image-2 and 2.5 always use
+  high input fidelity and error if the parameter is sent. The widget is gone from the edit node
+  and the parameter is no longer part of `build.run_edit()`.
+
 ## v0.1.0 — 2026-06-08
 
 First public release.
diff --git a/README.md b/README.md
index fcf2b87..316ea57 100644
--- a/README.md
+++ b/README.md
@@ -20,7 +20,7 @@
 ## ✨ Features
 
 - 🖼️ **Two nodes** — **Imagent: OpenAI Image** (text-to-image) and **Imagent: OpenAI Image Edit** (edit, inpaint, multi-reference compose).
-- 🤖 **Current gpt-image models** — `gpt-image-2`, `gpt-image-1.5`, `gpt-image-1`.
+- 🤖 **Current gpt-image models** — `gpt-image-2.5-flare`, `gpt-image-2.5-sunburst`, `gpt-image-2`.
 - ✍️ **Text-to-image** with full control over size, quality, background, and output format.
 - 🎨 **Edit + inpaint (mask)** — supply a mask to repaint a specific region; white pixels mark the area to edit.
 - 🔗 **Multi-reference compositing** — feed up to 16 reference images to the edit node (auto-growing input).
@@ -63,11 +63,11 @@ Text-to-image generation via `images.generate`.
 | Parameter | Type | Values / Notes |
 |---|---|---|
 | `prompt` | STRING | Text description of the image to generate |
-| `model` | **DynamicCombo** | `gpt-image-2` (default), `gpt-image-1.5`, `gpt-image-1`. Switching the model swaps the options below. |
-| ↳ `size` | COMBO | **gpt-image-2:** `auto`, the three base sizes, five high-res presets, and `custom`. **gpt-image-1.x:** `auto` + the three base sizes only. |
-| ↳↳ `custom_width` / `custom_height` | INT | **Appear only when `size = custom`.** 1024–3840, step 16; both multiples of 16; aspect ≤ 3:1; total pixels 655,360–8,294,400. |
-| ↳ `background` | COMBO | **gpt-image-2:** `auto`, `opaque`. **gpt-image-1.x:** `auto`, `opaque`, `transparent` (needs `png`/`webp`). |
-| `quality` | COMBO | `auto`, `low`, `medium`, `high` |
+| `model` | **DynamicCombo** | `gpt-image-2.5-flare` (default), `gpt-image-2.5-sunburst`, `gpt-image-2`. Switching the model swaps the options below. |
+| ↳ `size` | COMBO | `auto`, the three base sizes, five high-res presets, and `custom`. |
+| ↳↳ `custom_width` / `custom_height` | INT | **Appear only when `size = custom`.** 480–3840, step 16; both multiples of 16; aspect ≤ 3:1; total pixels 655,360–8,294,400. |
+| ↳ `background` | COMBO | **gpt-image-2.5:** `auto`, `opaque`, `transparent` (needs `png`/`webp`). **gpt-image-2:** `auto`, `opaque`. |
+| `quality` | COMBO | `auto`, `low`, `medium`, `high`, plus `xhigh` / `max` on gpt-image-2.5 (other models fall back to `high`). |
 | `output_format` | COMBO | `png`, `jpeg`, `webp` |
 | `output_compression` | INT | 0–100. Applied only for `jpeg` and `webp`. |
 | `moderation` | COMBO | `auto` (default), `low`. Sent only when not `auto`. |
@@ -77,7 +77,14 @@ Rows marked ↳ live inside the dynamic `model` widget (appear only for models t
 
 > No `seed` widget: OpenAI's image API has no seed, so it can't make outputs reproducible. ComfyUI's normal input-based caching applies — re-queuing an unchanged graph returns the cached image; change the prompt (or any input) to regenerate.
 
-**Output:** `image` (IMAGE tensor, batch of n). Errors are logged to the ComfyUI console.
+**Outputs:** `image` (IMAGE tensor, batch of n) and `mask` (MASK tensor). Errors are logged to the ComfyUI console.
+
+ComfyUI's IMAGE type is RGB, so when `background = transparent` the alpha channel comes out on
+`mask` instead — following the `LoadImage` convention, `mask = 1 - alpha`, meaning a transparent
+region reads as selected (1.0). The `image` preview will look black in those regions; that is the
+alpha being discarded for display, not a failed generation. To get a transparent file, feed
+`image` and `mask` into **Join Image with Alpha** (it inverts the mask internally, so no
+`InvertMask` in between) and save the result. Opaque output gives an all-zero mask.
 
 ---
 
@@ -89,12 +96,11 @@ Image editing, inpainting, and multi-reference compositing via `images.edit`.
 |---|---|---|
 | `prompt` | STRING | Description of the desired edit |
 | `model` | **DynamicCombo** | Same three models; switching swaps the options below. |
-| ↳ `size` | COMBO | Same as the generate node (hi-res + `custom` on gpt-image-2; base sizes on gpt-image-1.x). |
-| ↳↳ `custom_width` / `custom_height` | INT | **Appear only when `size = custom`** (gpt-image-2). Same rules as the generate node. |
-| ↳ `background` | COMBO | gpt-image-2: `auto`/`opaque`; gpt-image-1.x: adds `transparent`. |
-| ↳ `input_fidelity` | COMBO | **gpt-image-1.x only.** `high` (default) or `low` — how closely to follow the reference image. |
+| ↳ `size` | COMBO | Same as the generate node. |
+| ↳↳ `custom_width` / `custom_height` | INT | **Appear only when `size = custom`.** Same rules as the generate node. |
+| ↳ `background` | COMBO | gpt-image-2.5: `auto`/`opaque`/`transparent`; gpt-image-2: `auto`/`opaque`. |
 | `images` | IMAGE (auto-grow) | Reference image(s) to edit — grows up to **16** slots; at least one required. |
-| `quality` | COMBO | `auto`, `low`, `medium`, `high` |
+| `quality` | COMBO | `auto`, `low`, `medium`, `high`, plus `xhigh` / `max` on gpt-image-2.5. |
 | `output_format` | COMBO | `png`, `jpeg`, `webp` |
 | `moderation` | COMBO | `auto` (default), `low` |
 | `n` | INT | 1–8 images per call |
@@ -102,7 +108,16 @@ Image editing, inpainting, and multi-reference compositing via `images.edit`.
 
 Rows marked ↳ live inside the dynamic `model` widget; ↳↳ rows appear only when their parent option is selected.
 
-**Output:** `image` (IMAGE tensor, batch of n). Errors are logged to the ComfyUI console.
+> No `input_fidelity` widget: every model shipped here always uses high input fidelity, and passing the parameter is an error. It only applied to the retired gpt-image-1.x models.
+
+**Outputs:** `image` (IMAGE tensor, batch of n) and `mask` (MASK tensor). Errors are logged to the ComfyUI console.
+
+ComfyUI's IMAGE type is RGB, so when `background = transparent` the alpha channel comes out on
+`mask` instead — following the `LoadImage` convention, `mask = 1 - alpha`, meaning a transparent
+region reads as selected (1.0). The `image` preview will look black in those regions; that is the
+alpha being discarded for display, not a failed generation. To get a transparent file, feed
+`image` and `mask` into **Join Image with Alpha** (it inverts the mask internally, so no
+`InvertMask` in between) and save the result. Opaque output gives an all-zero mask.
 
 **Quick-start recipes:**
 - **Edit:** connect one image to `images`, write a `prompt`, leave `mask` disconnected.
diff --git a/imagent/__init__.py b/imagent/__init__.py
index c27ddf0..c415e30 100644
--- a/imagent/__init__.py
+++ b/imagent/__init__.py
@@ -1,3 +1,3 @@
 """imagent package — OpenAI gpt-image generation and editing for ComfyUI."""
 
-__version__ = "0.1.0"
+__version__ = "0.2.0"
diff --git a/imagent/build.py b/imagent/build.py
index 856617d..d9d0e7e 100644
--- a/imagent/build.py
+++ b/imagent/build.py
@@ -35,19 +35,20 @@ def run_generate(*, prompt, model, size, quality, background, output_format, n,
                  output_compression=100):
     """Text-to-image via images.generate.
 
-    Returns (image_tensor, info_string). Never raises: a failed call yields an
-    empty image plus a friendly error so a bad call can't crash the queue.
+    Returns (image_tensor, mask_tensor, info_string); the mask carries the
+    alpha channel when background='transparent'. Never raises: a failed call
+    yields an empty image plus a friendly error so a bad call can't crash the queue.
     """
     oai = client_mod.get_client()
     if oai is None:
         log.warning("imagent: %s", _NO_KEY)
-        return (image_io.empty_image(), _NO_KEY)
+        return (image_io.empty_image(), image_io.empty_mask(), _NO_KEY)
     try:
-        resolved_size = params_mod.resolve_size(size, custom_width, custom_height, model)
+        resolved_size = params_mod.resolve_size(size, custom_width, custom_height)
         resolved_background = params_mod.resolve_background(background, model)
         kwargs = {
             "model": model, "prompt": prompt, "n": n,
-            "size": resolved_size, "quality": quality,
+            "size": resolved_size, "quality": params_mod.resolve_quality(quality, model),
             "background": resolved_background, "output_format": output_format,
         }
         if output_format in ("jpeg", "webp"):
@@ -56,44 +57,43 @@ def run_generate(*, prompt, model, size, quality, background, output_format, n,
             kwargs["moderation"] = moderation
         resp = oai.images.generate(**kwargs)
         if not resp.data:
-            return (image_io.empty_image(), _NO_IMAGES)
+            return (image_io.empty_image(), image_io.empty_mask(), _NO_IMAGES)
         info = getattr(resp.data[0], "revised_prompt", None) \
             or f"Generated {len(resp.data)} image(s) with {model}."
-        return (image_io.batch_from_response_data(resp.data), info)
+        return (*image_io.batch_from_response_data(resp.data), info)
     except Exception as exc:  # noqa: BLE001 - node must not crash the queue
         log.exception("imagent: image generation failed")
-        return (image_io.empty_image(), client_mod.friendly_error(exc))
+        return (image_io.empty_image(), image_io.empty_mask(), client_mod.friendly_error(exc))
 
 
 def run_edit(*, prompt, model, size, quality, background, output_format, n,
-             images, mask=None, input_fidelity="high", moderation="auto",
+             images, mask=None, moderation="auto",
              custom_width=1024, custom_height=1024):
     """Image edit / inpaint / multi-reference via images.edit.
 
     `images` is an iterable of IMAGE tensors (None entries are ignored).
-    Returns (image_tensor, info_string); never raises (see run_generate).
+    Returns (image_tensor, mask_tensor, info_string); never raises (see run_generate).
     """
     oai = client_mod.get_client()
     if oai is None:
         log.warning("imagent: %s", _NO_KEY)
-        return (image_io.empty_image(), _NO_KEY)
+        return (image_io.empty_image(), image_io.empty_mask(), _NO_KEY)
 
     refs = [t for t in (images or []) if t is not None]
     if not refs:
         msg = "Error: OpenAIImageEdit requires at least one reference image."
         log.warning("imagent: %s", msg)
-        return (image_io.empty_image(), msg)
+        return (image_io.empty_image(), image_io.empty_mask(), msg)
 
     if mask is not None and len(refs) > 1:
         msg = ("Error: mask inpainting requires a single reference image "
                "(connect only one image).")
         log.warning("imagent: %s", msg)
-        return (image_io.empty_image(), msg)
+        return (image_io.empty_image(), image_io.empty_mask(), msg)
 
     try:
-        resolved_size = params_mod.resolve_size(size, custom_width, custom_height, model)
+        resolved_size = params_mod.resolve_size(size, custom_width, custom_height)
         resolved_background = params_mod.resolve_background(background, model)
-        caps = params_mod.capabilities_for(model)
         # Downscale oversized references to fit the API's input pixel budget.
         ref_pils = [image_io.downscale_pil_to_pixel_limit(image_io.tensor_to_pil(t)[0])
                     for t in refs]
@@ -101,21 +101,20 @@ def run_edit(*, prompt, model, size, quality, background, output_format, n,
         kwargs = {
             "model": model, "prompt": prompt,
             "image": [_named_png(p, f"ref_{i}.png") for i, p in enumerate(ref_pils)],
-            "n": n, "size": resolved_size, "quality": quality,
+            "n": n, "size": resolved_size,
+            "quality": params_mod.resolve_quality(quality, model),
             "background": resolved_background, "output_format": output_format,
         }
         if mask is not None:
             kwargs["mask"] = image_io.mask_to_named_png(ref_pils[0], mask, "mask.png")
-        if caps["input_fidelity"]:
-            kwargs["input_fidelity"] = input_fidelity
         if moderation != "auto":
             kwargs["moderation"] = moderation
         resp = oai.images.edit(**kwargs)
         if not resp.data:
-            return (image_io.empty_image(), _NO_IMAGES)
+            return (image_io.empty_image(), image_io.empty_mask(), _NO_IMAGES)
         info = getattr(resp.data[0], "revised_prompt", None) \
             or f"Edited image with {model}."
-        return (image_io.batch_from_response_data(resp.data), info)
+        return (*image_io.batch_from_response_data(resp.data), info)
     except Exception as exc:  # noqa: BLE001 - node must not crash the queue
         log.exception("imagent: image edit failed")
-        return (image_io.empty_image(), client_mod.friendly_error(exc))
+        return (image_io.empty_image(), image_io.empty_mask(), client_mod.friendly_error(exc))
diff --git a/imagent/client.py b/imagent/client.py
index 6ce6797..5506901 100644
--- a/imagent/client.py
+++ b/imagent/client.py
@@ -19,15 +19,14 @@ log = logging.getLogger("imagent")
 # config.json lives at the repo root, next to this package directory.
 _CONFIG_PATH = Path(__file__).resolve().parent.parent / "config.json"
 
-# Current OpenAI image models, verified 2026-06-07. Curated to the three current
-# GPT image generations (1, 1.5, 2); dated snapshots and -mini are intentionally
-# omitted. DALL-E excluded (shut down 2026-05-12).
+# Current OpenAI image models, verified 2026-09-13. Dated snapshots, -mini and
+# models with an announced shutdown date are intentionally omitted.
 MODELS = [
+    "gpt-image-2.5-flare",
+    "gpt-image-2.5-sunburst",
     "gpt-image-2",
-    "gpt-image-1.5",
-    "gpt-image-1",
 ]
-DEFAULT_MODEL = "gpt-image-2"
+DEFAULT_MODEL = "gpt-image-2.5-flare"
 
 _PLACEHOLDERS = {"", "sk-...", "your_openai_api_key_here"}
 
diff --git a/imagent/image_io.py b/imagent/image_io.py
index 2426674..08c3f53 100644
--- a/imagent/image_io.py
+++ b/imagent/image_io.py
@@ -1,9 +1,8 @@
 """Conversions between ComfyUI tensors, PIL images, masks, and base64 payloads.
 
-Public helpers: pil_to_tensor, tensor_to_pil, b64_to_tensor, empty_image,
-pil_to_png_bytes, mask_to_alpha_png_bytes, mask_to_named_png,
-downscale_pil_to_pixel_limit, url_to_tensor, response_item_to_tensor,
-batch_from_response_data.
+Public helpers: pil_to_tensor, pil_to_image_and_mask, tensor_to_pil, empty_image,
+empty_mask, pil_to_png_bytes, mask_to_alpha_png_bytes, mask_to_named_png,
+downscale_pil_to_pixel_limit, response_item_to_pil, batch_from_response_data.
 """
 from __future__ import annotations
 
@@ -33,11 +32,19 @@ def tensor_to_pil(image_tensor: torch.Tensor) -> list[Image.Image]:
     return out
 
 
-def b64_to_tensor(b64_str: str) -> torch.Tensor:
-    """Base64 PNG/JPEG/WebP -> [1, H, W, 3] float32 tensor."""
-    data = base64.b64decode(b64_str)
-    pil = Image.open(io.BytesIO(data))
-    return pil_to_tensor(pil)
+def pil_to_image_and_mask(pil_image: Image.Image) -> tuple[torch.Tensor, torch.Tensor]:
+    """PIL image -> (IMAGE [1, H, W, 3], MASK [1, H, W]).
+
+    Alpha is carried out as a MASK because ComfyUI IMAGE is RGB-only: following
+    the LoadImage convention, mask = 1 - alpha, so a transparent region reads as
+    selected (1.0). Images without an alpha channel yield an all-zero mask.
+    """
+    if "A" in pil_image.getbands():
+        alpha = np.array(pil_image.getchannel("A")).astype(np.float32) / 255.0
+        mask = 1.0 - torch.from_numpy(alpha)[None, ]
+    else:
+        mask = empty_mask(pil_image.height, pil_image.width)
+    return pil_to_tensor(pil_image), mask
 
 
 def empty_image(height: int = 512, width: int = 512) -> torch.Tensor:
@@ -45,6 +52,11 @@ def empty_image(height: int = 512, width: int = 512) -> torch.Tensor:
     return torch.zeros((1, height, width, 3), dtype=torch.float32)
 
 
+def empty_mask(height: int = 512, width: int = 512) -> torch.Tensor:
+    """All-zero (fully opaque) MASK tensor."""
+    return torch.zeros((1, height, width), dtype=torch.float32)
+
+
 def pil_to_png_bytes(pil_image: Image.Image) -> bytes:
     """PIL image -> PNG bytes."""
     buf = io.BytesIO()
@@ -96,27 +108,23 @@ def downscale_pil_to_pixel_limit(pil_image: Image.Image,
     return pil_image.resize((max(1, int(w * scale)), max(1, int(h * scale))))
 
 
-def url_to_tensor(url: str) -> torch.Tensor:
-    """Download an image URL and convert it to a [1, H, W, 3] tensor."""
-    import urllib.request
-    with urllib.request.urlopen(url, timeout=30) as resp:  # noqa: S310 - caller owns URL provenance
-        data = resp.read()
-    return pil_to_tensor(Image.open(io.BytesIO(data)))
-
-
-def response_item_to_tensor(item) -> torch.Tensor:
-    """Convert an OpenAI image response item (b64_json or url) to a tensor."""
+def response_item_to_pil(item) -> Image.Image:
+    """Decode an OpenAI image response item (b64_json or url) to a PIL image."""
     b64 = getattr(item, "b64_json", None)
     if b64:
-        return b64_to_tensor(b64)
+        return Image.open(io.BytesIO(base64.b64decode(b64)))
     url = getattr(item, "url", None)
     if url:
-        return url_to_tensor(url)
+        import urllib.request
+        with urllib.request.urlopen(url, timeout=30) as resp:  # noqa: S310 - caller owns URL provenance
+            return Image.open(io.BytesIO(resp.read()))
     raise ValueError("response item has neither b64_json nor url")
 
 
-def batch_from_response_data(data: list) -> torch.Tensor:
-    """OpenAI response `.data` list -> [B, H, W, 3] batch tensor (b64 or url items)."""
+def batch_from_response_data(data: list) -> tuple[torch.Tensor, torch.Tensor]:
+    """OpenAI response `.data` list -> ([B, H, W, 3] IMAGE, [B, H, W] MASK) batches."""
     if not data:
         raise ValueError("data must contain at least one response item")
-    return torch.cat([response_item_to_tensor(d) for d in data], dim=0)
+    pairs = [pil_to_image_and_mask(response_item_to_pil(d)) for d in data]
+    return (torch.cat([img for img, _ in pairs], dim=0),
+            torch.cat([mask for _, mask in pairs], dim=0))
diff --git a/imagent/node_edit.py b/imagent/node_edit.py
index 517f849..926f9ad 100644
--- a/imagent/node_edit.py
+++ b/imagent/node_edit.py
@@ -9,24 +9,11 @@ from comfy_api.latest import IO
 
 from . import build
 from . import params as params_mod
-from .node_generate import _gpt_image_2_inputs, unpack_size
+from .node_generate import _gpt_image_2_inputs, _gpt_image_25_inputs, unpack_size
 
 _MAX_REFS = 16
 
 
-def _legacy_edit_inputs():
-    """gpt-image-1 / gpt-image-1.5: base sizes, transparent allowed, input_fidelity."""
-    return [
-        IO.Combo.Input("size", options=params_mod.SIZES_BASE, default="auto",
-                       tooltip="Output size (base sizes supported by gpt-image-1.x)."),
-        IO.Combo.Input("background", options=params_mod.BACKGROUNDS, default="auto",
-                       tooltip="Background handling. 'transparent' needs png or webp output."),
-        IO.Combo.Input("input_fidelity", options=params_mod.INPUT_FIDELITIES, default="high",
-                       tooltip="How closely to preserve the reference image: 'high' "
-                       "(default) or 'low'."),
-    ]
-
-
 class OpenAIImageEdit(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -44,9 +31,9 @@ class OpenAIImageEdit(IO.ComfyNode):
                     "model",
                     tooltip="OpenAI gpt-image model. Switching this changes the options below.",
                     options=[
+                        IO.DynamicCombo.Option("gpt-image-2.5-flare", _gpt_image_25_inputs()),
+                        IO.DynamicCombo.Option("gpt-image-2.5-sunburst", _gpt_image_25_inputs()),
                         IO.DynamicCombo.Option("gpt-image-2", _gpt_image_2_inputs()),
-                        IO.DynamicCombo.Option("gpt-image-1.5", _legacy_edit_inputs()),
-                        IO.DynamicCombo.Option("gpt-image-1", _legacy_edit_inputs()),
                     ],
                 ),
                 IO.Autogrow.Input(
@@ -59,7 +46,8 @@ class OpenAIImageEdit(IO.ComfyNode):
                     "(if used) applies to the first image and requires exactly one image."),
                 IO.Combo.Input("quality", options=params_mod.QUALITIES, default="auto",
                                tooltip="Rendering quality. 'auto' lets the model decide; "
-                               "higher quality costs more."),
+                               "higher quality costs more. 'xhigh' and 'max' need "
+                               "gpt-image-2.5 and fall back to 'high' elsewhere."),
                 IO.Combo.Input("output_format", options=params_mod.FORMATS, default="png",
                                tooltip="Image file format returned by the API."),
                 IO.Combo.Input("moderation", options=params_mod.MODERATIONS, default="auto",
@@ -71,7 +59,8 @@ class OpenAIImageEdit(IO.ComfyNode):
                               tooltip="Inpaint mask: white marks the region to edit. Requires a "
                               "single reference image."),
             ],
-            outputs=[IO.Image.Output(display_name="image")],
+            outputs=[IO.Image.Output(display_name="image"),
+                     IO.Mask.Output(display_name="mask")],
         )
 
     @classmethod
@@ -79,10 +68,9 @@ class OpenAIImageEdit(IO.ComfyNode):
                 mask=None) -> IO.NodeOutput:
         size, custom_width, custom_height = unpack_size(model)
         ref_tensors = [t for t in (images or {}).values() if t is not None]
-        img, _info = build.run_edit(
+        img, out_mask, _info = build.run_edit(
             prompt=prompt, model=model["model"], size=size, quality=quality,
             background=model["background"], output_format=output_format, n=n,
-            images=ref_tensors, mask=mask,
-            input_fidelity=model.get("input_fidelity", "high"), moderation=moderation,
+            images=ref_tensors, mask=mask, moderation=moderation,
             custom_width=custom_width, custom_height=custom_height)
-        return IO.NodeOutput(img)
+        return IO.NodeOutput(img, out_mask)
diff --git a/imagent/node_generate.py b/imagent/node_generate.py
index 2d1d396..68d994d 100644
--- a/imagent/node_generate.py
+++ b/imagent/node_generate.py
@@ -40,11 +40,10 @@ def _gpt_image_2_inputs():
     ]
 
 
-def _legacy_inputs():
-    """Per-model widgets for gpt-image-1 / gpt-image-1.5: base sizes, transparent allowed."""
+def _gpt_image_25_inputs():
+    """Per-model widgets for gpt-image-2.5: hi-res/custom sizes, transparent allowed."""
     return [
-        IO.Combo.Input("size", options=params_mod.SIZES_BASE, default="auto",
-                       tooltip="Output size (base sizes supported by gpt-image-1.x)."),
+        _size_combo_gpt2(),
         IO.Combo.Input("background", options=params_mod.BACKGROUNDS, default="auto",
                        tooltip="Background handling. 'transparent' needs png or webp output."),
     ]
@@ -53,13 +52,10 @@ def _legacy_inputs():
 def unpack_size(model: dict):
     """Pull (size, custom_width, custom_height) from a model dict.
 
-    For gpt-image-2 `size` is a nested DynamicCombo (dict); for gpt-image-1.x it's
-    a plain combo (string).
+    `size` is itself a nested DynamicCombo, so it arrives as a dict.
     """
     sz = model["size"]
-    if isinstance(sz, dict):
-        return sz["size"], sz.get("custom_width", 1024), sz.get("custom_height", 1024)
-    return sz, 1024, 1024
+    return sz["size"], sz.get("custom_width", 1024), sz.get("custom_height", 1024)
 
 
 class OpenAIImageGenerate(IO.ComfyNode):
@@ -78,14 +74,15 @@ class OpenAIImageGenerate(IO.ComfyNode):
                     "model",
                     tooltip="OpenAI gpt-image model. Switching this changes the options below.",
                     options=[
+                        IO.DynamicCombo.Option("gpt-image-2.5-flare", _gpt_image_25_inputs()),
+                        IO.DynamicCombo.Option("gpt-image-2.5-sunburst", _gpt_image_25_inputs()),
                         IO.DynamicCombo.Option("gpt-image-2", _gpt_image_2_inputs()),
-                        IO.DynamicCombo.Option("gpt-image-1.5", _legacy_inputs()),
-                        IO.DynamicCombo.Option("gpt-image-1", _legacy_inputs()),
                     ],
                 ),
                 IO.Combo.Input("quality", options=params_mod.QUALITIES, default="auto",
                                tooltip="Rendering quality. 'auto' lets the model decide; "
-                               "higher quality costs more."),
+                               "higher quality costs more. 'xhigh' and 'max' need "
+                               "gpt-image-2.5 and fall back to 'high' elsewhere."),
                 IO.Combo.Input("output_format", options=params_mod.FORMATS, default="png",
                                tooltip="Image file format returned by the API."),
                 IO.Int.Input("output_compression", default=100, min=0, max=100,
@@ -96,16 +93,17 @@ class OpenAIImageGenerate(IO.ComfyNode):
                 IO.Int.Input("n", default=1, min=params_mod.N_MIN, max=params_mod.N_MAX, step=1,
                              tooltip="How many images to generate (1-8)."),
             ],
-            outputs=[IO.Image.Output(display_name="image")],
+            outputs=[IO.Image.Output(display_name="image"),
+                     IO.Mask.Output(display_name="mask")],
         )
 
     @classmethod
     def execute(cls, prompt, model, quality, output_format, output_compression,
                 moderation, n) -> IO.NodeOutput:
         size, custom_width, custom_height = unpack_size(model)
-        img, _info = build.run_generate(
+        img, mask, _info = build.run_generate(
             prompt=prompt, model=model["model"], size=size, quality=quality,
             background=model["background"], output_format=output_format, n=n,
             moderation=moderation, custom_width=custom_width, custom_height=custom_height,
             output_compression=output_compression)
-        return IO.NodeOutput(img)
+        return IO.NodeOutput(img, mask)
diff --git a/imagent/params.py b/imagent/params.py
index ab566e0..a0e3419 100644
--- a/imagent/params.py
+++ b/imagent/params.py
@@ -1,8 +1,8 @@
 """Parameter constants, per-model capabilities, and size validation.
 
 Public entry points: capabilities_for(), validate_custom_dimensions(), resolve_size(),
-resolve_background(); plus the SIZE_PRESETS / QUALITIES / BACKGROUNDS / FORMATS /
-INPUT_FIDELITIES / MODERATIONS lists and the CUSTOM_DIM_* widget bounds.
+resolve_quality(), resolve_background(); plus the SIZE_PRESETS / QUALITIES /
+BACKGROUNDS / FORMATS / MODERATIONS lists and the CUSTOM_DIM_* widget bounds.
 """
 from __future__ import annotations
 
@@ -10,47 +10,44 @@ import logging
 
 log = logging.getLogger("imagent")
 
-# Size presets. The base sizes work on every gpt-image model; the high-res presets
-# and 'custom' are gpt-image-2 only (gated in resolve_size to stay cross-model safe).
+# Size presets, all supported by every model in the catalog.
 _BASE_SIZES = ["auto", "1024x1024", "1024x1536", "1536x1024"]
 _GPT2_SIZES = ["2048x2048", "2048x1152", "1152x2048", "3840x2160", "2160x3840"]
-_GPT2_ONLY_SIZES = set(_GPT2_SIZES)
 SIZE_PRESETS = [*_BASE_SIZES, *_GPT2_SIZES, "custom"]
 
-# Per-model size option lists for the IO DynamicCombo (what each model can pick).
-SIZES_BASE = list(_BASE_SIZES)                              # gpt-image-1 / 1.5
-SIZES_GPT2 = [*_BASE_SIZES, *_GPT2_SIZES, "custom"]         # gpt-image-2
+# Size option list for the IO DynamicCombo (what each model can pick).
+SIZES_GPT2 = [*_BASE_SIZES, *_GPT2_SIZES, "custom"]         # gpt-image-2 / 2.5
 
-# custom_width / custom_height INT-widget bounds (mirror the official node).
-CUSTOM_DIM_MIN, CUSTOM_DIM_MAX, CUSTOM_DIM_STEP = 1024, 3840, 16
+# custom_width / custom_height INT-widget bounds. The floor is the smallest edge
+# validate_custom_dimensions() can accept (480x1440 at the 3:1 aspect limit); a
+# higher floor would block sizes the validator considers legal.
+CUSTOM_DIM_MIN, CUSTOM_DIM_MAX, CUSTOM_DIM_STEP = 480, 3840, 16
 
 # Per-model background option lists (gpt-image-2 cannot do transparent).
 BACKGROUNDS = ["auto", "opaque", "transparent"]
 BACKGROUNDS_GPT2 = ["auto", "opaque"]
 
-QUALITIES = ["auto", "low", "medium", "high"]
+# 'xhigh' and 'max' exist only on gpt-image-2.5 (gated in resolve_quality).
+_EXTENDED_QUALITIES = {"xhigh", "max"}
+QUALITIES = ["auto", "low", "medium", "high", "xhigh", "max"]
 FORMATS = ["png", "jpeg", "webp"]
-INPUT_FIDELITIES = ["high", "low"]
 MODERATIONS = ["auto", "low"]
 
 # Widget bounds shared by both nodes' IO schemas.
 N_MIN, N_MAX = 1, 8
 
 # Per-model capability flags. Keys (all default False for unknown models):
-#   custom_size            - arbitrary WxH sizes (gpt-image-2 only)
-#   input_fidelity         - edit input_fidelity param (gpt-image-1.x)
 #   transparent_background - background="transparent" (NOT gpt-image-2, which errors)
-_DEFAULT_CAPS = {
-    "custom_size": False, "input_fidelity": False, "transparent_background": False,
-}
+#   extended_quality       - quality="xhigh" / "max" (gpt-image-2.5 only)
+_DEFAULT_CAPS = {"transparent_background": False, "extended_quality": False}
 
 CAPABILITIES: dict[str, dict[str, bool]] = {
-    "gpt-image-2":   {"custom_size": True,  "input_fidelity": False, "transparent_background": False},
-    "gpt-image-1.5": {"custom_size": False, "input_fidelity": True,  "transparent_background": True},
-    "gpt-image-1":   {"custom_size": False, "input_fidelity": True,  "transparent_background": True},
+    "gpt-image-2.5-sunburst": {"transparent_background": True,  "extended_quality": True},
+    "gpt-image-2.5-flare":    {"transparent_background": True,  "extended_quality": True},
+    "gpt-image-2":            {"transparent_background": False, "extended_quality": False},
 }
 
-# gpt-image-2 custom-resolution constraints (mirror the official node, 2026-06-08).
+# Custom-resolution constraints, shared by gpt-image-2 and gpt-image-2.5.
 _MAX_EDGE = 3840
 _MIN_TOTAL_PX = 655_360
 _MAX_TOTAL_PX = 8_294_400
@@ -86,29 +83,30 @@ def validate_custom_dimensions(width: int, height: int) -> str:
     return f"{w}x{h}"
 
 
-def resolve_size(size: str, custom_width: int, custom_height: int, model: str) -> str:
-    """Resolve the size parameter to a value the selected model accepts.
-
-    'custom' and the high-res presets are gpt-image-2 only; for other models they
-    fall back to 'auto' so switching models never sends an unsupported size.
-    """
-    caps = capabilities_for(model)
+def resolve_size(size: str, custom_width: int, custom_height: int) -> str:
+    """Resolve the size parameter, validating 'custom' against the WxH rules."""
     if size == "custom":
-        if not caps["custom_size"]:
-            log.info("imagent: %s does not support custom sizes; using 'auto'.", model)
-            return "auto"
         return validate_custom_dimensions(custom_width, custom_height)
-    if size in _GPT2_ONLY_SIZES and not caps["custom_size"]:
-        log.info("imagent: size %s is gpt-image-2 only; using 'auto' for %s.", size, model)
-        return "auto"
     return size
 
 
+def resolve_quality(quality: str, model: str) -> str:
+    """Drop an unsupported extended quality tier to 'high'.
+
+    'xhigh' and 'max' are gpt-image-2.5 only; older models error on them, so they
+    fall back to 'high' when the model is switched.
+    """
+    if quality in _EXTENDED_QUALITIES and not capabilities_for(model)["extended_quality"]:
+        log.info("imagent: %s does not support quality '%s'; using 'high'.", model, quality)
+        return "high"
+    return quality
+
+
 def resolve_background(background: str, model: str) -> str:
     """Drop an unsupported transparent background to 'auto'.
 
-    gpt-image-2 errors on background='transparent'; only gpt-image-1.x supports
-    it. Falling back to 'auto' keeps the node compatible across model switches.
+    gpt-image-2 errors on background='transparent'; gpt-image-2.5 supports it.
+    Falling back to 'auto' keeps the node compatible across model switches.
     """
     if background == "transparent" and not capabilities_for(model)["transparent_background"]:
         log.info("imagent: %s does not support a transparent background; using 'auto'.", model)
diff --git a/tests/test_client.py b/tests/test_client.py
index 417a644..2ca4c6f 100644
--- a/tests/test_client.py
+++ b/tests/test_client.py
@@ -32,10 +32,15 @@ def test_placeholder_key_is_ignored(monkeypatch, tmp_path):
 
 
 def test_model_catalog_defaults():
-    assert client.DEFAULT_MODEL == "gpt-image-2"
-    assert set(client.MODELS) == {"gpt-image-1", "gpt-image-1.5", "gpt-image-2"}
+    assert client.DEFAULT_MODEL == "gpt-image-2.5-flare"
+    assert set(client.MODELS) == {"gpt-image-2", "gpt-image-2.5-flare",
+                                  "gpt-image-2.5-sunburst"}
     assert "gpt-image-1-mini" not in client.MODELS
     assert "gpt-image-2-2026-04-21" not in client.MODELS
+    assert "gpt-image-2.5-flare-2026-09-08" not in client.MODELS
+    # Retired: both shut down before this release's models do.
+    assert "gpt-image-1" not in client.MODELS
+    assert "gpt-image-1.5" not in client.MODELS
     assert all("dall-e" not in m for m in client.MODELS)
 
 
diff --git a/tests/test_image_io.py b/tests/test_image_io.py
index 021e37b..ef8cdb0 100644
--- a/tests/test_image_io.py
+++ b/tests/test_image_io.py
@@ -24,9 +24,26 @@ def test_pil_to_tensor_shape_and_range():
     assert abs(float(t[0, 0, 0, 0]) - 1.0) < 1e-6   # red channel
 
 
-def test_b64_to_tensor_roundtrip():
-    t = image_io.b64_to_tensor(_png_b64(size=(32, 48)))
-    assert t.shape == (1, 48, 32, 3)
+def test_response_item_to_pil_roundtrip():
+    item = types.SimpleNamespace(b64_json=_png_b64(size=(32, 48)), url=None)
+    assert image_io.response_item_to_pil(item).size == (32, 48)
+
+
+def test_rgba_alpha_becomes_mask():
+    rgba = Image.new("RGBA", (4, 4), (255, 0, 0, 255))
+    rgba.putalpha(Image.fromarray(
+        np.array([[0, 0, 255, 255]] * 4, dtype=np.uint8), "L"))
+    img, mask = image_io.pil_to_image_and_mask(rgba)
+    assert img.shape == (1, 4, 4, 3)
+    assert mask.shape == (1, 4, 4)
+    assert float(mask[0, 0, 0]) == 1.0      # transparent -> selected
+    assert float(mask[0, 0, 3]) == 0.0      # opaque -> unselected
+
+
+def test_rgb_without_alpha_yields_zero_mask():
+    _img, mask = image_io.pil_to_image_and_mask(Image.new("RGB", (8, 4), (1, 2, 3)))
+    assert mask.shape == (1, 4, 8)
+    assert float(mask.abs().sum()) == 0.0
 
 
 def test_empty_image_is_black_rgb():
@@ -69,13 +86,12 @@ def test_downscale_pil_to_pixel_limit_keeps_small_image():
     assert out.size == (64, 48)               # unchanged
 
 
-def test_response_item_to_tensor_handles_b64():
+def test_response_item_to_pil_handles_b64():
     item = types.SimpleNamespace(b64_json=_png_b64(size=(20, 10)), url=None)
-    t = image_io.response_item_to_tensor(item)
-    assert t.shape == (1, 10, 20, 3)
+    assert image_io.response_item_to_pil(item).size == (20, 10)
 
 
-def test_response_item_to_tensor_handles_url(monkeypatch):
+def test_response_item_to_pil_handles_url(monkeypatch):
     png = base64.b64decode(_png_b64(size=(12, 6)))
 
     class _FakeResp:
@@ -90,21 +106,21 @@ def test_response_item_to_tensor_handles_url(monkeypatch):
 
     monkeypatch.setattr("urllib.request.urlopen", lambda url, **kw: _FakeResp())
     item = types.SimpleNamespace(b64_json=None, url="http://example/x.png")
-    t = image_io.response_item_to_tensor(item)
-    assert t.shape == (1, 6, 12, 3)
+    assert image_io.response_item_to_pil(item).size == (12, 6)
 
 
 def test_batch_from_response_data_concatenates_b64_items():
     data = [types.SimpleNamespace(b64_json=_png_b64(), url=None) for _ in range(3)]
-    batch = image_io.batch_from_response_data(data)
+    batch, masks = image_io.batch_from_response_data(data)
     assert batch.shape[0] == 3
+    assert masks.shape[0] == 3
 
 
-def test_response_item_to_tensor_raises_without_payload():
+def test_response_item_to_pil_raises_without_payload():
     import pytest
     item = types.SimpleNamespace(b64_json=None, url=None)
     with pytest.raises(ValueError):
-        image_io.response_item_to_tensor(item)
+        image_io.response_item_to_pil(item)
 
 
 def test_mask_3d_shape_is_handled():
diff --git a/tests/test_nodes.py b/tests/test_nodes.py
index 4b725c7..503ebf4 100644
--- a/tests/test_nodes.py
+++ b/tests/test_nodes.py
@@ -37,7 +37,7 @@ class FakeClient:
 
 def test_generate_missing_key_returns_empty(monkeypatch):
     monkeypatch.setattr(client, "get_client", lambda: None)
-    img, info = run_generate(
+    img, _mask, info = run_generate(
         prompt="x", model="gpt-image-2", size="auto", quality="auto",
         background="auto", output_format="png", n=1)
     assert img.shape == (1, 512, 512, 3)
@@ -47,7 +47,7 @@ def test_generate_missing_key_returns_empty(monkeypatch):
 def test_generate_sends_expected_params_and_decodes(monkeypatch):
     rec = {}
     monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
-    img, info = run_generate(
+    img, _mask, info = run_generate(
         prompt="a cat", model="gpt-image-2", size="1024x1024", quality="high",
         background="opaque", output_format="png", n=2)
     sent = rec["generate"]
@@ -70,11 +70,25 @@ def test_generate_drops_transparent_background_for_gpt_image_2(monkeypatch):
     assert rec["generate"]["background"] == "auto"   # gpt-image-2 can't do transparent
 
 
-def test_generate_keeps_transparent_background_for_gpt_image_1(monkeypatch):
+def test_generate_extended_quality_gated_to_gpt_image_25(monkeypatch):
     rec = {}
     monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
     run_generate(
-        prompt="x", model="gpt-image-1", size="auto", quality="auto",
+        prompt="x", model="gpt-image-2.5-sunburst", size="auto", quality="max",
+        background="auto", output_format="png", n=1)
+    assert rec["generate"]["quality"] == "max"
+    rec.clear()
+    run_generate(
+        prompt="x", model="gpt-image-2", size="auto", quality="max",
+        background="auto", output_format="png", n=1)
+    assert rec["generate"]["quality"] == "high"
+
+
+def test_generate_keeps_transparent_background_for_gpt_image_25(monkeypatch):
+    rec = {}
+    monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
+    run_generate(
+        prompt="x", model="gpt-image-2.5-flare", size="auto", quality="auto",
         background="transparent", output_format="png", n=1)
     assert rec["generate"]["background"] == "transparent"
 
@@ -117,7 +131,7 @@ def test_generate_api_error_returns_empty(monkeypatch):
     monkeypatch.setattr(
         FakeImages, "generate",
         lambda self, **kw: (_ for _ in ()).throw(RuntimeError("network error")))
-    img, info = run_generate(
+    img, _mask, info = run_generate(
         prompt="x", model="gpt-image-2", size="auto", quality="auto",
         background="auto", output_format="png", n=1)
     assert img.shape == (1, 512, 512, 3)
@@ -126,7 +140,7 @@ def test_generate_api_error_returns_empty(monkeypatch):
 
 def test_generate_invalid_custom_size_returns_error(monkeypatch):
     monkeypatch.setattr(client, "get_client", lambda: FakeClient({}))
-    img, info = run_generate(
+    img, _mask, info = run_generate(
         prompt="x", model="gpt-image-2", size="custom", quality="auto",
         background="auto", output_format="png", n=1,
         custom_width=1000, custom_height=1000)   # 1000 is not a multiple of 16
@@ -144,20 +158,6 @@ def test_generate_custom_dimensions_for_gpt_image_2(monkeypatch):
     assert rec["generate"]["size"] == "2048x1152"
 
 
-def test_generate_hires_preset_gated_to_gpt_image_2(monkeypatch):
-    rec = {}
-    monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
-    run_generate(
-        prompt="x", model="gpt-image-1", size="2048x2048", quality="auto",
-        background="auto", output_format="png", n=1)
-    assert rec["generate"]["size"] == "auto"          # gpt-image-1 can't do hi-res
-    rec.clear()
-    run_generate(
-        prompt="x", model="gpt-image-2", size="2048x2048", quality="auto",
-        background="auto", output_format="png", n=1)
-    assert rec["generate"]["size"] == "2048x2048"
-
-
 # ---------------------------------------------------------------------------
 # OpenAIImageEdit tests
 # ---------------------------------------------------------------------------
@@ -171,7 +171,7 @@ def _img_tensor(h=16, w=16):
 def test_edit_sends_image_list_and_decodes(monkeypatch):
     rec = {}
     monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
-    img, info = run_edit(
+    img, _mask, info = run_edit(
         prompt="make it snowy", model="gpt-image-2", size="auto", quality="auto",
         background="auto", output_format="png", n=1,
         images=[_img_tensor(), _img_tensor()])
@@ -194,22 +194,6 @@ def test_edit_includes_mask_when_provided(monkeypatch):
     assert "mask" in rec["edit"]
 
 
-def test_edit_input_fidelity_only_for_1x(monkeypatch):
-    rec = {}
-    monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
-    run_edit(
-        prompt="x", model="gpt-image-1", size="auto", quality="auto",
-        background="auto", output_format="png", n=1,
-        images=[_img_tensor()], input_fidelity="high")
-    assert rec["edit"]["input_fidelity"] == "high"
-    rec.clear()
-    run_edit(
-        prompt="x", model="gpt-image-2", size="auto", quality="auto",
-        background="auto", output_format="png", n=1,
-        images=[_img_tensor()], input_fidelity="high")
-    assert "input_fidelity" not in rec["edit"]
-
-
 def test_edit_moderation_only_when_not_auto(monkeypatch):
     rec = {}
     monkeypatch.setattr(client, "get_client", lambda: FakeClient(rec))
@@ -241,7 +225,7 @@ def test_edit_downscales_large_reference(monkeypatch):
 
 def test_edit_missing_image_returns_error(monkeypatch):
     monkeypatch.setattr(client, "get_client", lambda: FakeClient({}))
-    img, info = run_edit(
+    img, _mask, info = run_edit(
         prompt="x", model="gpt-image-2", size="auto", quality="auto",
         background="auto", output_format="png", n=1, images=[])
     assert info.startswith("Error")
@@ -253,7 +237,7 @@ def test_edit_api_error_returns_empty(monkeypatch):
     monkeypatch.setattr(
         FakeImages, "edit",
         lambda self, **kw: (_ for _ in ()).throw(RuntimeError("network error")))
-    img, info = run_edit(
+    img, _mask, info = run_edit(
         prompt="x", model="gpt-image-2", size="auto", quality="auto",
         background="auto", output_format="png", n=1, images=[_img_tensor()])
     assert img.shape == (1, 512, 512, 3)
@@ -263,7 +247,7 @@ def test_edit_api_error_returns_empty(monkeypatch):
 def test_edit_mask_with_multiple_refs_returns_error(monkeypatch):
     monkeypatch.setattr(client, "get_client", lambda: FakeClient({}))
     mask = torch.zeros((16, 16), dtype=torch.float32)
-    img, info = run_edit(
+    img, _mask, info = run_edit(
         prompt="x", model="gpt-image-2", size="auto", quality="auto",
         background="auto", output_format="png", n=1,
         images=[_img_tensor(), _img_tensor()], mask=mask)
@@ -271,6 +255,20 @@ def test_edit_mask_with_multiple_refs_returns_error(monkeypatch):
     assert info.startswith("Error")
 
 
+def test_model_widget_matches_catalog_and_gpt_image_25_options():
+    import pytest
+    pytest.importorskip("comfy_api")
+    from imagent.node_edit import OpenAIImageEdit
+    from imagent.node_generate import OpenAIImageGenerate
+    for node in (OpenAIImageGenerate, OpenAIImageEdit):
+        model_input = next(i for i in node.define_schema().inputs if i.id == "model")
+        assert [o.key for o in model_input.options] == client.MODELS
+        for key in ("gpt-image-2.5-flare", "gpt-image-2.5-sunburst"):
+            subs = {i.id: i for i in next(o for o in model_input.options if o.key == key).inputs}
+            assert "transparent" in subs["background"].options
+            assert "custom" in [o.key for o in subs["size"].options]
+
+
 def test_extension_registers_both_nodes():
     # Registration uses the comfy_api V3 entrypoint, so this needs ComfyUI present.
     import pytest
diff --git a/tests/test_params.py b/tests/test_params.py
index 7d586d0..e969a42 100644
--- a/tests/test_params.py
+++ b/tests/test_params.py
@@ -10,23 +10,35 @@ def test_constants():
         assert base in params.SIZE_PRESETS
     for hires in ("2048x2048", "3840x2160", "2160x3840"):
         assert hires in params.SIZE_PRESETS
-    assert (params.CUSTOM_DIM_MIN, params.CUSTOM_DIM_MAX, params.CUSTOM_DIM_STEP) == (1024, 3840, 16)
-    assert params.QUALITIES == ["auto", "low", "medium", "high"]
+    assert (params.CUSTOM_DIM_MIN, params.CUSTOM_DIM_MAX, params.CUSTOM_DIM_STEP) == (480, 3840, 16)
+    # The widget floor must not reject a size the validator accepts (the 3:1 edge case).
+    assert params.validate_custom_dimensions(1440, params.CUSTOM_DIM_MIN) == "1440x480"
+    assert params.QUALITIES == ["auto", "low", "medium", "high", "xhigh", "max"]
     assert params.BACKGROUNDS == ["auto", "opaque", "transparent"]
     assert params.FORMATS == ["png", "jpeg", "webp"]
     assert params.MODERATIONS == ["auto", "low"]
 
 
 def test_capabilities_for_known_and_unknown():
-    assert params.capabilities_for("gpt-image-2")["custom_size"] is True
-    assert params.capabilities_for("gpt-image-2")["input_fidelity"] is False
-    assert params.capabilities_for("gpt-image-2")["transparent_background"] is False
-    assert params.capabilities_for("gpt-image-1")["input_fidelity"] is True
-    assert params.capabilities_for("gpt-image-1")["custom_size"] is False
-    assert params.capabilities_for("gpt-image-1")["transparent_background"] is True
-    assert params.capabilities_for("gpt-image-1.5")["transparent_background"] is True
+    assert params.capabilities_for("gpt-image-2") == {
+        "transparent_background": False, "extended_quality": False}
     assert params.capabilities_for("mystery") == {
-        "custom_size": False, "input_fidelity": False, "transparent_background": False}
+        "transparent_background": False, "extended_quality": False}
+
+
+@pytest.mark.parametrize("model", ["gpt-image-2.5-flare", "gpt-image-2.5-sunburst"])
+def test_gpt_image_25_capabilities(model):
+    assert params.capabilities_for(model) == {
+        "transparent_background": True, "extended_quality": True}
+
+
+def test_resolve_quality_gates_extended_tiers():
+    assert params.resolve_quality("max", "gpt-image-2.5-sunburst") == "max"
+    assert params.resolve_quality("xhigh", "gpt-image-2.5-flare") == "xhigh"
+    assert params.resolve_quality("xhigh", "gpt-image-2") == "high"
+    assert params.resolve_quality("max", "mystery") == "high"
+    assert params.resolve_quality("high", "gpt-image-2") == "high"
+    assert params.resolve_quality("auto", "gpt-image-2") == "auto"
 
 
 def test_resolve_background_drops_transparent_for_gpt_image_2():
@@ -35,11 +47,6 @@ def test_resolve_background_drops_transparent_for_gpt_image_2():
     assert params.resolve_background("auto", "gpt-image-2") == "auto"
 
 
-def test_resolve_background_keeps_transparent_for_gpt_image_1x():
-    assert params.resolve_background("transparent", "gpt-image-1") == "transparent"
-    assert params.resolve_background("transparent", "gpt-image-1.5") == "transparent"
-
-
 def test_validate_custom_dimensions_ok():
     assert params.validate_custom_dimensions(1536, 864) == "1536x864"
     assert params.validate_custom_dimensions(2048, 1152) == "2048x1152"
@@ -60,18 +67,10 @@ def test_validate_custom_dimensions_rejects(w, h):
         params.validate_custom_dimensions(w, h)
 
 
-def test_resolve_size_passthrough_for_base_presets():
-    assert params.resolve_size("1024x1024", 1024, 1024, "gpt-image-2") == "1024x1024"
-    assert params.resolve_size("auto", 1024, 1024, "gpt-image-1") == "auto"
-
-
-def test_resolve_size_custom_requires_capability():
-    assert params.resolve_size("custom", 1536, 864, "gpt-image-2") == "1536x864"
-    assert params.resolve_size("custom", 1536, 864, "gpt-image-1") == "auto"
-
-
-def test_resolve_size_hires_presets_gated_to_gpt_image_2():
-    assert params.resolve_size("2048x2048", 1024, 1024, "gpt-image-2") == "2048x2048"
-    assert params.resolve_size("3840x2160", 1024, 1024, "gpt-image-2") == "3840x2160"
-    assert params.resolve_size("2048x2048", 1024, 1024, "gpt-image-1") == "auto"
-    assert params.resolve_size("3840x2160", 1024, 1024, "gpt-image-1.5") == "auto"
+def test_resolve_size_passes_presets_through_and_validates_custom():
+    assert params.resolve_size("auto", 1024, 1024) == "auto"
+    assert params.resolve_size("1024x1024", 1024, 1024) == "1024x1024"
+    assert params.resolve_size("3840x2160", 1024, 1024) == "3840x2160"
+    assert params.resolve_size("custom", 1536, 864) == "1536x864"
+    with pytest.raises(ValueError):
+        params.resolve_size("custom", 1000, 1000)