diff --git a/studio/frontend/src/features/images/api.ts b/studio/frontend/src/features/images/api.ts
index e33da62113..26e9e25bed 100644
--- a/studio/frontend/src/features/images/api.ts
+++ b/studio/frontend/src/features/images/api.ts
@@ -254,3 +254,62 @@ export async function fetchGalleryObjectUrl(url: string): Promise<string> {
   if (!res.ok) throw new Error(await readFastApiError(res));
   return URL.createObjectURL(await res.blob());
 }
+
+// ── Diffusion (SDXL) LoRA training ────────────────────────────────────────────
+// Mirrors DiffusionTrainingStartRequest on the backend; only the paths are required.
+export interface DiffusionTrainingStartRequest {
+  base_model: string;
+  data_dir: string;
+  output_dir: string;
+  instance_prompt?: string | null;
+  resolution?: number;
+  train_steps?: number;
+  learning_rate?: number;
+  train_batch_size?: number;
+  gradient_accumulation_steps?: number;
+  lora_rank?: number;
+  lora_alpha?: number | null;
+  seed?: number;
+  mixed_precision?: "bf16" | "fp16" | "no";
+  gradient_checkpointing?: boolean;
+  lr_scheduler?: string;
+}
+
+// A snapshot of the current diffusion training job (GET /api/train/diffusion/status).
+export interface DiffusionTrainingStatus {
+  active: boolean;
+  job_id: string | null;
+  status: string;
+  message: string;
+  step: number;
+  total_steps: number;
+  loss: number | null;
+  avg_loss: number | null;
+  learning_rate: number | null;
+  num_images: number | null;
+  in_model_load: boolean;
+  output_dir: string | null;
+  lora_path: string | null;
+  started_at: number | null;
+  updated_at: number | null;
+}
+
+export async function startDiffusionTraining(
+  body: DiffusionTrainingStartRequest,
+): Promise<{ job_id: string; status: string }> {
+  return parseJson(
+    await authFetch("/api/train/diffusion/start", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify(body),
+    }),
+  );
+}
+
+export async function stopDiffusionTraining(): Promise<{ status: string }> {
+  return parseJson(await authFetch("/api/train/diffusion/stop", { method: "POST" }));
+}
+
+export async function getDiffusionTrainingStatus(): Promise<DiffusionTrainingStatus> {
+  return parseJson(await authFetch("/api/train/diffusion/status"));
+}
diff --git a/studio/frontend/src/features/images/diffusion-train-dialog.tsx b/studio/frontend/src/features/images/diffusion-train-dialog.tsx
new file mode 100644
index 0000000000..a365908dae
--- /dev/null
+++ b/studio/frontend/src/features/images/diffusion-train-dialog.tsx
@@ -0,0 +1,251 @@
+// SPDX-License-Identifier: AGPL-3.0-only
+// Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
+
+import { useCallback, useEffect, useState } from "react";
+
+import { Button } from "@/components/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/ui/dialog";
+import { Input } from "@/components/ui/input";
+import { Label } from "@/components/ui/label";
+import { toast } from "@/lib/toast";
+
+import {
+  type DiffusionTrainingStatus,
+  getDiffusionTrainingStatus,
+  startDiffusionTraining,
+  stopDiffusionTraining,
+} from "./api";
+
+// A self-contained "Train a LoRA" dialog for the diffusion (SDXL) trainer. It posts to
+// /api/train/diffusion/start and polls /status while open, so it never blocks the page and
+// works whether or not a model is loaded for generation. Only SDXL is trainable today.
+export function DiffusionTrainDialog({
+  open,
+  onOpenChange,
+  defaultBaseModel,
+}: {
+  open: boolean;
+  onOpenChange: (open: boolean) => void;
+  defaultBaseModel?: string;
+}) {
+  const [baseModel, setBaseModel] = useState(defaultBaseModel || "stabilityai/stable-diffusion-xl-base-1.0");
+  const [dataDir, setDataDir] = useState("");
+  const [outputDir, setOutputDir] = useState("");
+  const [instancePrompt, setInstancePrompt] = useState("");
+  const [steps, setSteps] = useState(500);
+  const [learningRate, setLearningRate] = useState(0.0001);
+  const [rank, setRank] = useState(16);
+  const [resolution, setResolution] = useState(1024);
+  const [batchSize, setBatchSize] = useState(1);
+  const [starting, setStarting] = useState(false);
+  const [status, setStatus] = useState<DiffusionTrainingStatus | null>(null);
+
+  const poll = useCallback(async () => {
+    try {
+      setStatus(await getDiffusionTrainingStatus());
+    } catch {
+      // Best-effort; a failed poll should not surface an error while the dialog is open.
+    }
+  }, []);
+
+  // Poll status only while the dialog is open.
+  useEffect(() => {
+    if (!open) return;
+    void poll();
+    const id = window.setInterval(() => void poll(), 1500);
+    return () => window.clearInterval(id);
+  }, [open, poll]);
+
+  const active = Boolean(status?.active) || status?.status === "running";
+  const pct =
+    status && status.total_steps > 0
+      ? Math.min(100, Math.round((status.step / status.total_steps) * 100))
+      : 0;
+
+  const onStart = useCallback(async () => {
+    if (!baseModel.trim() || !dataDir.trim() || !outputDir.trim()) {
+      toast.error("Base model, dataset folder, and output folder are required.");
+      return;
+    }
+    setStarting(true);
+    try {
+      await startDiffusionTraining({
+        base_model: baseModel.trim(),
+        data_dir: dataDir.trim(),
+        output_dir: outputDir.trim(),
+        instance_prompt: instancePrompt.trim() || undefined,
+        resolution,
+        train_steps: steps,
+        learning_rate: learningRate,
+        train_batch_size: batchSize,
+        lora_rank: rank,
+      });
+      toast.success("Training started");
+      void poll();
+    } catch (e) {
+      toast.error(e instanceof Error ? e.message : "Failed to start training");
+    } finally {
+      setStarting(false);
+    }
+  }, [baseModel, dataDir, outputDir, instancePrompt, resolution, steps, learningRate, batchSize, rank, poll]);
+
+  const onStop = useCallback(async () => {
+    try {
+      await stopDiffusionTraining();
+      toast.success("Stop requested; finishing the current step.");
+      void poll();
+    } catch (e) {
+      toast.error(e instanceof Error ? e.message : "Failed to stop training");
+    }
+  }, [poll]);
+
+  return (
+    <Dialog open={open} onOpenChange={onOpenChange}>
+      <DialogContent className="max-w-lg">
+        <DialogHeader>
+          <DialogTitle>Train a LoRA (SDXL)</DialogTitle>
+          <DialogDescription>
+            Fine-tune an SDXL LoRA on a folder of images. Captions come from a metadata.jsonl,
+            per-image .txt sidecars, or the instance prompt below. The adapter is written to the
+            output folder and can be loaded from the LoRAs picker.
+          </DialogDescription>
+        </DialogHeader>
+
+        <div className="grid gap-3 py-2">
+          <div className="grid gap-1.5">
+            <Label className="text-xs">Base model (SDXL repo or local path)</Label>
+            <Input
+              value={baseModel}
+              spellCheck={false}
+              onChange={(e) => setBaseModel(e.target.value)}
+              className="h-8 text-xs"
+            />
+          </div>
+          <div className="grid gap-1.5">
+            <Label className="text-xs">Dataset folder</Label>
+            <Input
+              value={dataDir}
+              placeholder="/path/to/images"
+              spellCheck={false}
+              onChange={(e) => setDataDir(e.target.value)}
+              className="h-8 text-xs"
+            />
+          </div>
+          <div className="grid gap-1.5">
+            <Label className="text-xs">Output folder (LoRA .safetensors)</Label>
+            <Input
+              value={outputDir}
+              placeholder="/path/to/output-lora"
+              spellCheck={false}
+              onChange={(e) => setOutputDir(e.target.value)}
+              className="h-8 text-xs"
+            />
+          </div>
+          <div className="grid gap-1.5">
+            <Label className="text-xs">Instance prompt (optional; used for uncaptioned images)</Label>
+            <Input
+              value={instancePrompt}
+              placeholder="a photo of sks style"
+              onChange={(e) => setInstancePrompt(e.target.value)}
+              className="h-8 text-xs"
+            />
+          </div>
+          <div className="grid grid-cols-2 gap-3 sm:grid-cols-4">
+            <div className="grid gap-1.5">
+              <Label className="text-xs">Steps</Label>
+              <Input
+                type="number"
+                min={1}
+                value={steps}
+                onChange={(e) => setSteps(Number(e.target.value) || 1)}
+                className="h-8 text-xs"
+              />
+            </div>
+            <div className="grid gap-1.5">
+              <Label className="text-xs">LoRA rank</Label>
+              <Input
+                type="number"
+                min={1}
+                value={rank}
+                onChange={(e) => setRank(Number(e.target.value) || 1)}
+                className="h-8 text-xs"
+              />
+            </div>
+            <div className="grid gap-1.5">
+              <Label className="text-xs">Resolution</Label>
+              <Input
+                type="number"
+                min={64}
+                step={64}
+                value={resolution}
+                onChange={(e) => setResolution(Number(e.target.value) || 1024)}
+                className="h-8 text-xs"
+              />
+            </div>
+            <div className="grid gap-1.5">
+              <Label className="text-xs">Batch</Label>
+              <Input
+                type="number"
+                min={1}
+                value={batchSize}
+                onChange={(e) => setBatchSize(Number(e.target.value) || 1)}
+                className="h-8 text-xs"
+              />
+            </div>
+          </div>
+          <div className="grid gap-1.5">
+            <Label className="text-xs">Learning rate</Label>
+            <Input
+              type="number"
+              step={0.00001}
+              min={0}
+              value={learningRate}
+              onChange={(e) => setLearningRate(Number(e.target.value) || 0.0001)}
+              className="h-8 text-xs"
+            />
+          </div>
+
+          {status && status.status !== "idle" && (
+            <div className="rounded-lg border border-border bg-muted/30 p-3 text-xs">
+              <div className="mb-1 flex items-center justify-between">
+                <span className="font-medium capitalize">{status.status}</span>
+                <span className="text-muted-foreground">
+                  {status.total_steps > 0 ? `${status.step}/${status.total_steps}` : ""}
+                </span>
+              </div>
+              <div className="mb-2 h-1.5 w-full overflow-hidden rounded-full bg-border">
+                <div className="h-full bg-primary transition-all" style={{ width: `${pct}%` }} />
+              </div>
+              <div className="text-muted-foreground">
+                {status.message}
+                {status.loss != null && <> · loss {status.loss.toFixed(4)}</>}
+                {status.lora_path && (
+                  <div className="mt-1 break-all text-[11px]">Saved: {status.lora_path}</div>
+                )}
+              </div>
+            </div>
+          )}
+        </div>
+
+        <DialogFooter>
+          {active ? (
+            <Button type="button" variant="destructive" onClick={onStop}>
+              Stop
+            </Button>
+          ) : (
+            <Button type="button" onClick={onStart} disabled={starting}>
+              {starting ? "Starting..." : "Start training"}
+            </Button>
+          )}
+        </DialogFooter>
+      </DialogContent>
+    </Dialog>
+  );
+}
diff --git a/studio/frontend/src/features/images/images-page.tsx b/studio/frontend/src/features/images/images-page.tsx
index eacfea5c15..4df7aef66d 100644
--- a/studio/frontend/src/features/images/images-page.tsx
+++ b/studio/frontend/src/features/images/images-page.tsx
@@ -66,6 +66,7 @@ import {
   loadDiffusionModel,
   unloadDiffusionModel,
 } from "./api";
+import { DiffusionTrainDialog } from "./diffusion-train-dialog";
 
 // Curated diffusion GGUFs the picker recommends. The backend resolves each one's
 // pipeline + base diffusers repo from its repo id, so the rail just lists them;
@@ -907,6 +908,8 @@ export function ImagesPage({ active = true }: { active?: boolean }) {
   // offers. Applied at generate time; available adapters are refreshed per loaded family.
   const [loras, setLoras] = useState<LoraSpecInput[]>([]);
   const [availableLoras, setAvailableLoras] = useState<DiffusionLoraInfo[]>([]);
+  // "Train a LoRA" dialog (SDXL). Independent of the loaded generation model.
+  const [trainOpen, setTrainOpen] = useState(false);
   // ControlNet for the next generation: the chosen model id, a control image (data URL),
   // how to derive the control map, and the conditioning strength. Available models refresh
   // per loaded family; applied at generate time only when a model + control image are set.
@@ -1732,24 +1735,43 @@ export function ImagesPage({ active = true }: { active?: boolean }) {
           open={active && selectorOpen}
           onOpenChange={(o) => setSelectorOpen(active && o)}
         />
-        {/* Single fixed toggle for the right-docked Advanced panel (mirrors Chat's settings
-            toggle, same icon in both states so it never moves). Highlighted when open. */}
-        <button
-          type="button"
-          onClick={() => setAdvancedOpen((o) => !o)}
-          aria-label={advancedOpen ? "Hide advanced options" : "Show advanced options"}
-          aria-pressed={advancedOpen}
-          title="Advanced options"
-          className={cn(
-            "flex h-[34px] w-[34px] items-center justify-center rounded-full transition-colors focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring",
-            advancedOpen
-              ? "bg-muted text-foreground"
-              : "text-muted-foreground hover:bg-muted hover:text-foreground",
-          )}
-        >
-          <HugeiconsIcon icon={LayoutAlignRightIcon} className="size-4" />
-        </button>
+        <div className="flex items-center gap-2">
+          {/* Train a LoRA (SDXL): opens a self-contained dialog; available regardless of
+              whether a generation model is loaded. */}
+          <Button
+            type="button"
+            variant="ghost"
+            size="sm"
+            className="h-[34px]"
+            onClick={() => setTrainOpen(true)}
+            title="Train a LoRA adapter (SDXL)"
+          >
+            Train LoRA
+          </Button>
+          {/* Single fixed toggle for the right-docked Advanced panel (mirrors Chat's settings
+              toggle, same icon in both states so it never moves). Highlighted when open. */}
+          <button
+            type="button"
+            onClick={() => setAdvancedOpen((o) => !o)}
+            aria-label={advancedOpen ? "Hide advanced options" : "Show advanced options"}
+            aria-pressed={advancedOpen}
+            title="Advanced options"
+            className={cn(
+              "flex h-[34px] w-[34px] items-center justify-center rounded-full transition-colors focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring",
+              advancedOpen
+                ? "bg-muted text-foreground"
+                : "text-muted-foreground hover:bg-muted hover:text-foreground",
+            )}
+          >
+            <HugeiconsIcon icon={LayoutAlignRightIcon} className="size-4" />
+          </button>
+        </div>
       </div>
+      <DiffusionTrainDialog
+        open={trainOpen}
+        onOpenChange={setTrainOpen}
+        defaultBaseModel={status?.family === "sdxl" ? status?.repo_id ?? undefined : undefined}
+      />
 
       {/* ── Controls rail + preview canvas. Padding mirrors the other tabs
           (Export, Data Recipes): px-5 / sm:px-9, with a roomy bottom. ── */}