diff --git a/open-sse/handlers/imageGeneration.ts b/open-sse/handlers/imageGeneration.ts
index 3b2da49eaa..1e63e105bd 100644
--- a/open-sse/handlers/imageGeneration.ts
+++ b/open-sse/handlers/imageGeneration.ts
@@ -44,6 +44,24 @@ import { fetchRemoteImage } from "@/shared/network/remoteImageFetch";
 import { FetchTimeoutError, fetchWithTimeout, getConfiguredTimeout } from "@/shared/utils/fetchTimeout";
 import { sanitizeErrorMessage, sanitizeUpstreamDetails } from "../utils/error.ts";
 
+// --- Per-provider handlers (extracted to co-located files in PR-#4582-batch) ---
+// Imported locally so internal callers (handleImageGeneration / handleImageEdit)
+// resolve to a real binding. extractMarkdownImageUrls + CHATGPT_WEB_IMAGE_ID_RE
+// are still used by handleImageEdit below, so they are imported (not re-defined).
+import { handleSDWebUIImageGeneration } from "./imageGeneration/providers/sdWebUI.ts";
+import { handleHyperbolicImageGeneration } from "./imageGeneration/providers/hyperbolic.ts";
+import { handleComfyUIImageGeneration } from "./imageGeneration/providers/comfyUI.ts";
+import { handleImagen3ImageGeneration } from "./imageGeneration/providers/imagen3.ts";
+import { handleIdeogramImageGeneration } from "./imageGeneration/providers/ideogram.ts";
+import { handleHaiperImageGeneration } from "./imageGeneration/providers/haiper.ts";
+import { handleLeonardoImageGeneration } from "./imageGeneration/providers/leonardo.ts";
+import {
+  handleChatGptWebImageGeneration,
+  extractMarkdownImageUrls,
+  CHATGPT_WEB_IMAGE_ID_RE,
+} from "./imageGeneration/providers/chatgptWeb.ts";
+
+
 interface KieImageOptions {
   model: string;
   provider: string;
@@ -1096,190 +1114,6 @@ export async function handleOpenAIImageEdit({
   return result;
 }
 
-const CHATGPT_WEB_IMAGE_MARKDOWN_RE = /!\[[^\]]*\]\(([^)\s]+)\)/g;
-const CHATGPT_WEB_IMAGE_ID_RE = /\/v1\/chatgpt-web\/image\/([a-f0-9]{16,64})(?=[?\s"'<>)]|$)/i;
-
-function extractMarkdownImageUrls(text: string): string[] {
-  const urls: string[] = [];
-  // String.prototype.matchAll consumes a fresh iterator and ignores the
-  // regex's lastIndex, so no manual reset is required.
-  for (const match of text.matchAll(CHATGPT_WEB_IMAGE_MARKDOWN_RE)) {
-    if (match[1]) urls.push(match[1]);
-  }
-  return urls;
-}
-
-function buildChatGptWebImagePrompt(body): string {
-  const prompt = String(body.prompt || "").trim();
-  const details: string[] = [`Create an image for this prompt: ${prompt}`];
-  if (typeof body.size === "string" && body.size.trim()) {
-    details.push(`Requested size: ${body.size.trim()}.`);
-  }
-  if (typeof body.quality === "string" && body.quality.trim()) {
-    details.push(`Requested quality: ${body.quality.trim()}.`);
-  }
-  if (typeof body.style === "string" && body.style.trim()) {
-    details.push(`Requested style: ${body.style.trim()}.`);
-  }
-  return details.join("\n");
-}
-
-async function handleChatGptWebImageGeneration({
-  model,
-  provider,
-  body,
-  credentials,
-  log,
-  signal,
-  clientHeaders,
-}) {
-  const startTime = Date.now();
-  const prompt = typeof body.prompt === "string" ? body.prompt.trim() : "";
-  if (!prompt) {
-    return saveImageErrorResult({
-      provider,
-      model,
-      status: 400,
-      startTime,
-      error: "Prompt is required for ChatGPT Web image generation",
-    });
-  }
-
-  if (!credentials?.apiKey) {
-    return saveImageErrorResult({
-      provider,
-      model,
-      status: 401,
-      startTime,
-      error: "ChatGPT Web credentials missing session cookie",
-    });
-  }
-
-  // Each image is one chatgpt.com chat turn (~30s). Cap at 4 (matches OpenAI's
-  // own limit for GPT Image models) so a stray n=1000 doesn't pin the
-  // executor for hours before the upstream HTTP timeout fires.
-  const CHATGPT_WEB_IMAGE_N_MAX = 4;
-  const rawCount = Number.isInteger(body.n) && (body.n as number) > 0 ? (body.n as number) : 1;
-  if (rawCount > CHATGPT_WEB_IMAGE_N_MAX) {
-    return saveImageErrorResult({
-      provider,
-      model,
-      status: 400,
-      startTime,
-      error: `ChatGPT Web image generation supports n=1..${CHATGPT_WEB_IMAGE_N_MAX} (got ${rawCount}); each n is a separate ~30s chat turn.`,
-    });
-  }
-  const requestedCount = rawCount;
-  if (log && requestedCount > 1) {
-    log.warn(
-      "IMAGE",
-      `ChatGPT Web returns one image per chat turn; requested n=${requestedCount} will run sequentially`
-    );
-  }
-
-  const wantsBase64 = body.response_format === "b64_json";
-  const images: Array<{ url?: string; b64_json?: string }> = [];
-  const requestBody = {
-    model,
-    prompt: prompt.slice(0, 500),
-    size: body.size || undefined,
-    quality: body.quality || undefined,
-  };
-
-  for (let i = 0; i < requestedCount; i++) {
-    const executor = new ChatGptWebExecutor();
-    const result = await executor.execute({
-      model,
-      body: {
-        messages: [{ role: "user", content: buildChatGptWebImagePrompt(body) }],
-      },
-      stream: false,
-      credentials,
-      signal,
-      log,
-      clientHeaders,
-    });
-
-    const responseText = await result.response.text();
-    if (result.response.status >= 400) {
-      return saveImageErrorResult({
-        provider,
-        model,
-        status: result.response.status,
-        startTime,
-        error: responseText,
-        requestBody,
-      });
-    }
-
-    let content = "";
-    try {
-      const json = JSON.parse(responseText);
-      content = String(json?.choices?.[0]?.message?.content || "");
-    } catch {
-      content = responseText;
-    }
-
-    const urls = extractMarkdownImageUrls(content);
-    if (urls.length === 0) {
-      return saveImageErrorResult({
-        provider,
-        model,
-        status: 502,
-        startTime,
-        error: `ChatGPT Web completed without returning image markdown: ${content.slice(0, 300)}`,
-        requestBody,
-      });
-    }
-
-    for (const url of urls) {
-      if (!wantsBase64) {
-        images.push({ url });
-        continue;
-      }
-      const id = url.match(CHATGPT_WEB_IMAGE_ID_RE)?.[1];
-      const cached = id ? getChatGptImage(id) : null;
-      if (!cached) {
-        return saveImageErrorResult({
-          provider,
-          model,
-          status: 502,
-          startTime,
-          error: "ChatGPT Web image bytes expired before b64_json conversion",
-          requestBody,
-        });
-      }
-      images.push({ b64_json: cached.bytes.toString("base64") });
-    }
-  }
-
-  return saveImageSuccessResult({
-    provider,
-    model,
-    startTime,
-    requestBody,
-    responseBody: { images_count: images.length },
-    images,
-  });
-}
-
-/**
- * Handle a multipart /v1/images/edits request for chatgpt-web. Open WebUI
- * uploads the prior image's bytes; we hash them and look up our cache.
- *
- * The hash match is reliable because Open WebUI's image-gen pipeline
- * downloads our /v1/chatgpt-web/image/<id> URL byte-for-byte and re-serves
- * those exact bytes through its own file store. When the user asks to edit
- * the image, OWUI uploads the same bytes back to us via multipart — same
- * hash, we find the conversation context, and drive the executor with a
- * synthetic chat thread that triggers continuation mode.
- *
- * No-match cases (cache evicted by TTL, or the user uploaded a foreign
- * image) get a clear 400. We can't actually edit an image we don't have a
- * conversation context for — chatgpt.com's image_gen tool needs the
- * original conversation node, and we don't have a path to upload bytes
- * directly.
- */
 export async function handleImageEdit({
   provider,
   model,
@@ -2538,7 +2372,7 @@ async function handleCodexImageGeneration({
   });
 }
 
-function saveImageSuccessResult({
+export function saveImageSuccessResult({
   provider,
   model,
   startTime,
@@ -2567,7 +2401,7 @@ function saveImageSuccessResult({
   };
 }
 
-function saveImageErrorResult({ provider, model, status, startTime, error, requestBody = null }) {
+export function saveImageErrorResult({ provider, model, status, startTime, error, requestBody = null }) {
   saveCallLog({
     method: "POST",
     path: "/v1/images/generations",
@@ -2658,104 +2492,6 @@ async function fetchImageEndpoint(url, headers, body, provider, log) {
  * Handle Hyperbolic image generation
  * Uses { model_name, prompt, height, width } and returns { images: [{ image: base64 }] }
  */
-async function handleHyperbolicImageGeneration({
-  model,
-  provider,
-  providerConfig,
-  body,
-  credentials,
-  log,
-}) {
-  const startTime = Date.now();
-  const token = credentials.apiKey || credentials.accessToken;
-
-  const [width, height] = (body.size || "1024x1024").split("x").map(Number);
-
-  const upstreamBody = {
-    model_name: model,
-    prompt: body.prompt,
-    height: height || 1024,
-    width: width || 1024,
-    backend: "auto",
-  };
-
-  if (log) {
-    const promptPreview = String(body.prompt ?? "").slice(0, 60);
-    log.info("IMAGE", `${provider}/${model} (hyperbolic) | prompt: "${promptPreview}..."`);
-  }
-
-  try {
-    const response = await fetch(providerConfig.baseUrl, {
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json",
-        Authorization: `Bearer ${token}`,
-      },
-      body: JSON.stringify(upstreamBody),
-    });
-
-    if (!response.ok) {
-      const errorText = await response.text();
-      if (log)
-        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
-
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: response.status,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: errorText.slice(0, 500),
-      }).catch(() => {});
-
-      return { success: false, status: response.status, error: errorText };
-    }
-
-    const data = await response.json();
-    // Transform { images: [{ image: base64 }] } → OpenAI format
-    const images = (data.images || []).map((img) => ({
-      b64_json: img.image,
-      revised_prompt: body.prompt,
-    }));
-
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 200,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      responseBody: { images_count: images.length },
-    }).catch(() => {});
-
-    return {
-      success: true,
-      data: { created: Math.floor(Date.now() / 1000), data: images },
-    };
-  } catch (err) {
-    if (log) log.error("IMAGE", `${provider} fetch error: ${err.message}`);
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: err.message,
-    }).catch(() => {});
-    return {
-      success: false,
-      status: 502,
-      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
-    };
-  }
-}
-
-/**
- * Handle NanoBanana image generation
- * NanoBanana is async (submit task -> poll status -> return final image URL/base64)
- */
 async function handleNanoBananaImageGeneration({
   model,
   provider,
@@ -3117,660 +2853,4 @@ function normalizePositiveNumber(value, fallback) {
  * Handle SD WebUI image generation (local, no auth)
  * POST {baseUrl} with { prompt, negative_prompt, width, height, steps }
  * Response: { images: ["base64..."] }
- */
-async function handleSDWebUIImageGeneration({ model, provider, providerConfig, body, log }) {
-  const startTime = Date.now();
-  const [width, height] = (body.size || "512x512").split("x").map(Number);
-
-  const upstreamBody = {
-    prompt: body.prompt,
-    negative_prompt: body.negative_prompt || "",
-    width: width || 512,
-    height: height || 512,
-    steps: body.steps || 20,
-    cfg_scale: body.cfg_scale || 7,
-    sampler_name: body.sampler || "Euler a",
-    batch_size: body.n || 1,
-    override_settings: {
-      sd_model_checkpoint: model,
-    },
-  };
-
-  if (log) {
-    const promptPreview = String(body.prompt ?? "").slice(0, 60);
-    log.info("IMAGE", `${provider}/${model} (sdwebui) | prompt: "${promptPreview}..."`);
-  }
-
-  try {
-    const response = await fetch(providerConfig.baseUrl, {
-      method: "POST",
-      headers: { "Content-Type": "application/json" },
-      body: JSON.stringify(upstreamBody),
-    });
-
-    if (!response.ok) {
-      const errorText = await response.text();
-      if (log)
-        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
-
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: response.status,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: errorText.slice(0, 500),
-      }).catch(() => {});
-
-      return { success: false, status: response.status, error: errorText };
-    }
-
-    const data = await response.json();
-    // SD WebUI returns { images: ["base64...", ...] }
-    const images = (data.images || []).map((b64) => ({
-      b64_json: b64,
-      revised_prompt: body.prompt,
-    }));
-
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 200,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      responseBody: { images_count: images.length },
-    }).catch(() => {});
-
-    return {
-      success: true,
-      data: { created: Math.floor(Date.now() / 1000), data: images },
-    };
-  } catch (err) {
-    if (log) log.error("IMAGE", `${provider} sdwebui error: ${err.message}`);
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: err.message,
-    }).catch(() => {});
-    return {
-      success: false,
-      status: 502,
-      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
-    };
-  }
-}
-
-/**
- * Handle ComfyUI image generation (local, no auth)
- * Submits a txt2img workflow, polls for completion, fetches output
- */
-async function handleComfyUIImageGeneration({ model, provider, providerConfig, body, log }) {
-  const startTime = Date.now();
-  const [width, height] = (body.size || "1024x1024").split("x").map(Number);
-
-  // Default txt2img workflow template for ComfyUI
-  const workflow = {
-    "3": {
-      class_type: "KSampler",
-      inputs: {
-        seed: parseInt(randomUUID().replace(/-/g, "").substring(0, 8), 16) % 2 ** 32,
-        steps: body.steps || 20,
-        cfg: body.cfg_scale || 7,
-        sampler_name: "euler",
-        scheduler: "normal",
-        denoise: 1,
-        model: ["4", 0],
-        positive: ["6", 0],
-        negative: ["7", 0],
-        latent_image: ["5", 0],
-      },
-    },
-    "4": {
-      class_type: "CheckpointLoaderSimple",
-      inputs: { ckpt_name: model },
-    },
-    "5": {
-      class_type: "EmptyLatentImage",
-      inputs: { width: width || 1024, height: height || 1024, batch_size: body.n || 1 },
-    },
-    "6": {
-      class_type: "CLIPTextEncode",
-      inputs: { text: body.prompt, clip: ["4", 1] },
-    },
-    "7": {
-      class_type: "CLIPTextEncode",
-      inputs: { text: body.negative_prompt || "", clip: ["4", 1] },
-    },
-    "8": {
-      class_type: "VAEDecode",
-      inputs: { samples: ["3", 0], vae: ["4", 2] },
-    },
-    "9": {
-      class_type: "SaveImage",
-      inputs: { filename_prefix: "omniroute", images: ["8", 0] },
-    },
-  };
-
-  if (log) {
-    const promptPreview = String(body.prompt ?? "").slice(0, 60);
-    log.info("IMAGE", `${provider}/${model} (comfyui) | prompt: "${promptPreview}..."`);
-  }
-
-  try {
-    const promptId = await submitComfyWorkflow(providerConfig.baseUrl, workflow);
-    const historyEntry = await pollComfyResult(providerConfig.baseUrl, promptId);
-    const outputFiles = extractComfyOutputFiles(historyEntry);
-
-    const images = [];
-    for (const file of outputFiles) {
-      const buffer = await fetchComfyOutput(
-        providerConfig.baseUrl,
-        file.filename,
-        file.subfolder,
-        file.type
-      );
-      const base64 = Buffer.from(buffer).toString("base64");
-      images.push({ b64_json: base64, revised_prompt: body.prompt });
-    }
-
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 200,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      responseBody: { images_count: images.length },
-    }).catch(() => {});
-
-    return {
-      success: true,
-      data: { created: Math.floor(Date.now() / 1000), data: images },
-    };
-  } catch (err) {
-    if (log) log.error("IMAGE", `${provider} comfyui error: ${err.message}`);
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: err.message,
-    }).catch(() => {});
-    return {
-      success: false,
-      status: 502,
-      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
-    };
-  }
-}
-
-async function handleHaiperImageGeneration({
-  model,
-  provider,
-  providerConfig,
-  body,
-  credentials,
-  log,
-}) {
-  const startTime = Date.now();
-  const token = credentials?.apiKey || "";
-  const prompt = typeof body.prompt === "string" ? body.prompt : String(body.prompt ?? "");
-  if (log) {
-    log.info("IMAGE", `${provider}/${model} (haiper) | prompt: "${prompt.slice(0, 60)}..."`);
-  }
-  try {
-    const res = await fetch(providerConfig.baseUrl, {
-      method: "POST",
-      headers: { "Content-Type": "application/json", HAIPER_KEY: token },
-      body: JSON.stringify({ prompt, aspect_ratio: body.aspect_ratio || "16:9" }),
-    });
-    if (!res.ok) {
-      const errorText = await res.text();
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: res.status,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: errorText.slice(0, 500),
-      }).catch(() => {});
-      return { success: false, status: res.status, error: errorText };
-    }
-    const { job_id } = await res.json();
-    const deadline = Date.now() + 300000;
-    while (Date.now() < deadline) {
-      await sleep(5000);
-      const statusRes = await fetch(`${providerConfig.statusUrl}/${job_id}`, {
-        headers: { HAIPER_KEY: token },
-      });
-      const status = await statusRes.json();
-      if (status.status === "completed" || status.status === "succeeded") {
-        const imgUrl = status.creation_url || status.output?.image_url;
-        if (imgUrl) {
-          const imgRes = await fetch(imgUrl);
-          if (!imgRes.ok) {
-            return {
-              success: false,
-              status: imgRes.status,
-              error: `Failed to download image: ${imgRes.status}`,
-            };
-          }
-          const buf = await imgRes.arrayBuffer();
-          saveCallLog({
-            method: "POST",
-            path: "/v1/images/generations",
-            status: 200,
-            model: `${provider}/${model}`,
-            provider,
-            duration: Date.now() - startTime,
-          }).catch(() => {});
-          return {
-            success: true,
-            data: {
-              created: Math.floor(Date.now() / 1000),
-              data: [{ b64_json: Buffer.from(buf).toString("base64") }],
-            },
-          };
-        }
-      }
-      if (status.status === "failed") {
-        saveCallLog({
-          method: "POST",
-          path: "/v1/images/generations",
-          status: 502,
-          model: `${provider}/${model}`,
-          provider,
-          duration: Date.now() - startTime,
-          error: "Haiper image generation failed",
-        }).catch(() => {});
-        return { success: false, status: 502, error: "Haiper image generation failed" };
-      }
-    }
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 504,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: "Haiper image generation timed out",
-    }).catch(() => {});
-    return { success: false, status: 504, error: "Haiper image generation timed out" };
-  } catch (err) {
-    if (log) log.error("IMAGE", `${provider} haiper error: ${err.message}`);
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: err.message,
-    }).catch(() => {});
-    return {
-      success: false,
-      status: 502,
-      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
-    };
-  }
-}
-
-async function handleLeonardoImageGeneration({
-  model,
-  provider,
-  providerConfig,
-  body,
-  credentials,
-  log,
-}) {
-  const startTime = Date.now();
-  const token = credentials?.apiKey || "";
-  const prompt = typeof body.prompt === "string" ? body.prompt : String(body.prompt ?? "");
-  if (log) {
-    log.info("IMAGE", `${provider}/${model} (leonardo) | prompt: "${prompt.slice(0, 60)}..."`);
-  }
-  try {
-    const res = await fetch(providerConfig.baseUrl, {
-      method: "POST",
-      headers: { "Content-Type": "application/json", Authorization: `Bearer ${token}` },
-      body: JSON.stringify({
-        modelId: model || "phoenix",
-        prompt,
-        width: body.width || 1024,
-        height: body.height || 1024,
-        num_images: 1,
-      }),
-    });
-    if (!res.ok) {
-      const errorText = await res.text();
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: res.status,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: errorText.slice(0, 500),
-      }).catch(() => {});
-      return { success: false, status: res.status, error: errorText };
-    }
-    const { sdGenerationJob } = await res.json();
-    const genId = sdGenerationJob?.generationId;
-    if (!genId) {
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: 502,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: "No generation ID returned",
-      }).catch(() => {});
-      return { success: false, status: 502, error: "No generation ID returned" };
-    }
-    const deadline = Date.now() + 300000;
-    while (Date.now() < deadline) {
-      await sleep(5000);
-      const statusRes = await fetch(`${providerConfig.baseUrl}/${genId}`, {
-        headers: { Authorization: `Bearer ${token}` },
-      });
-      const status = await statusRes.json();
-      const gen = status.generations_by_pk || status;
-      if (gen.status === "COMPLETE") {
-        const imgUrl = gen.generated_images?.[0]?.url;
-        if (imgUrl) {
-          const imgRes = await fetch(imgUrl);
-          if (!imgRes.ok) {
-            return {
-              success: false,
-              status: imgRes.status,
-              error: `Failed to download image: ${imgRes.status}`,
-            };
-          }
-          const buf = await imgRes.arrayBuffer();
-          saveCallLog({
-            method: "POST",
-            path: "/v1/images/generations",
-            status: 200,
-            model: `${provider}/${model}`,
-            provider,
-            duration: Date.now() - startTime,
-          }).catch(() => {});
-          return {
-            success: true,
-            data: {
-              created: Math.floor(Date.now() / 1000),
-              data: [{ b64_json: Buffer.from(buf).toString("base64") }],
-            },
-          };
-        }
-      }
-      if (gen.status === "FAILED") {
-        saveCallLog({
-          method: "POST",
-          path: "/v1/images/generations",
-          status: 502,
-          model: `${provider}/${model}`,
-          provider,
-          duration: Date.now() - startTime,
-          error: "Leonardo image generation failed",
-        }).catch(() => {});
-        return { success: false, status: 502, error: "Leonardo image generation failed" };
-      }
-    }
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 504,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: "Leonardo image generation timed out",
-    }).catch(() => {});
-    return { success: false, status: 504, error: "Leonardo image generation timed out" };
-  } catch (err) {
-    if (log) log.error("IMAGE", `${provider} leonardo error: ${err.message}`);
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: err.message,
-    }).catch(() => {});
-    return {
-      success: false,
-      status: 502,
-      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
-    };
-  }
-}
-
-async function handleIdeogramImageGeneration({
-  model,
-  provider,
-  providerConfig,
-  body,
-  credentials,
-  log,
-}) {
-  const startTime = Date.now();
-  const token = credentials?.apiKey || "";
-  const prompt = typeof body.prompt === "string" ? body.prompt : String(body.prompt ?? "");
-  if (log) {
-    log.info("IMAGE", `${provider}/${model} (ideogram) | prompt: "${prompt.slice(0, 60)}..."`);
-  }
-  try {
-    const res = await fetch(providerConfig.baseUrl, {
-      method: "POST",
-      headers: { "Content-Type": "application/json", "Api-Key": token },
-      body: JSON.stringify({ prompt, aspect_ratio: "ASPECT_16_9", model: model || "V_3" }),
-    });
-    if (!res.ok) {
-      const errorText = await res.text();
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: res.status,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: errorText.slice(0, 500),
-      }).catch(() => {});
-      return { success: false, status: res.status, error: errorText };
-    }
-    const data = await res.json();
-    if (data.data && data.data.length > 0) {
-      const imgUrl = data.data[0].url;
-      const imgRes = await fetch(imgUrl);
-      if (!imgRes.ok) {
-        return {
-          success: false,
-          status: imgRes.status,
-          error: `Failed to download image: ${imgRes.status}`,
-        };
-      }
-      const buf = await imgRes.arrayBuffer();
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: 200,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-      }).catch(() => {});
-      return {
-        success: true,
-        data: {
-          created: Math.floor(Date.now() / 1000),
-          data: [{ b64_json: Buffer.from(buf).toString("base64") }],
-        },
-      };
-    }
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: "No images returned from Ideogram",
-    }).catch(() => {});
-    return { success: false, status: 502, error: "No images returned from Ideogram" };
-  } catch (err) {
-    if (log) log.error("IMAGE", `${provider} ideogram error: ${err.message}`);
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: err.message,
-    }).catch(() => {});
-    return {
-      success: false,
-      status: 502,
-      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
-    };
-  }
-}
-
-type Imagen3ImageGenArgs = {
-  model: string;
-  provider: string;
-  providerConfig: { baseUrl: string };
-  body: { prompt?: string; size?: string; n?: number };
-  credentials: { apiKey?: string; accessToken?: string };
-  log?: {
-    info?: (tag: string, msg: string) => void;
-    error?: (tag: string, msg: string) => void;
-  } | null;
-};
-
-type Imagen3NormalizedImage = {
-  b64_json?: unknown;
-  url?: unknown;
-  revised_prompt?: string;
-};
-
-/**
- * Handle Imagen 3 image generation
- */
-async function handleImagen3ImageGeneration({
-  model,
-  provider,
-  providerConfig,
-  body,
-  credentials,
-  log,
-}: Imagen3ImageGenArgs) {
-  const startTime = Date.now();
-  const token = credentials.apiKey || credentials.accessToken;
-  const aspectRatio = mapImageSize(body.size);
-
-  const upstreamBody = {
-    prompt: body.prompt,
-    aspect_ratio: aspectRatio,
-    number_of_images: body.n ?? 1,
-  };
-
-  if (log) {
-    const promptPreview = String(body.prompt ?? "").slice(0, 60);
-    log.info(
-      "IMAGE",
-      `${provider}/${model} (imagen3) | prompt: "${promptPreview}..." | aspect_ratio: ${aspectRatio}`
-    );
-  }
-
-  try {
-    const response = await fetch(providerConfig.baseUrl, {
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json",
-        Authorization: `Bearer ${token}`,
-      },
-      body: JSON.stringify(upstreamBody),
-    });
-
-    if (!response.ok) {
-      const errorText = await response.text();
-      if (log)
-        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
-
-      saveCallLog({
-        method: "POST",
-        path: "/v1/images/generations",
-        status: response.status,
-        model: `${provider}/${model}`,
-        provider,
-        duration: Date.now() - startTime,
-        error: errorText.slice(0, 500),
-        requestBody: upstreamBody,
-      }).catch(() => {});
-
-      return { success: false, status: response.status, error: errorText };
-    }
-
-    const data = await response.json();
-
-    // Normalize response to OpenAI format
-    const images: Imagen3NormalizedImage[] = [];
-    if (Array.isArray(data.images)) {
-      images.push(
-        ...data.images.map((img: Record<string, unknown>) => ({
-          b64_json: img.image ?? img.b64_json ?? img.url ?? img,
-          revised_prompt: body.prompt,
-        }))
-      );
-    } else if (Array.isArray(data.data)) {
-      images.push(...data.data);
-    } else if (data.url || data.b64_json || data.image) {
-      images.push({
-        b64_json: data.image || data.b64_json || data.url,
-        url: data.url,
-        revised_prompt: body.prompt,
-      });
-    }
-
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 200,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      responseBody: { images_count: images.length },
-    }).catch(() => {});
-
-    return {
-      success: true,
-      data: { created: data.created || Math.floor(Date.now() / 1000), data: images },
-    };
-  } catch (err: unknown) {
-    const errMsg = err instanceof Error ? err.message : String(err);
-    if (log) log.error("IMAGE", `${provider} fetch error: ${errMsg}`);
-
-    saveCallLog({
-      method: "POST",
-      path: "/v1/images/generations",
-      status: 502,
-      model: `${provider}/${model}`,
-      provider,
-      duration: Date.now() - startTime,
-      error: errMsg,
-    }).catch(() => {});
-
-    return { success: false, status: 502, error: `Image provider error: ${errMsg}` };
-  }
-}
+ */
\ No newline at end of file
diff --git a/open-sse/handlers/imageGeneration/providers/chatgptWeb.ts b/open-sse/handlers/imageGeneration/providers/chatgptWeb.ts
new file mode 100644
index 0000000000..7faa531f5c
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/chatgptWeb.ts
@@ -0,0 +1,175 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: chatgpt-web | Module: chatgptWeb | Lines: 1102-1282 (181 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { ChatGptWebExecutor } from "../../../executors/chatgpt-web.ts";
+import { getChatGptImage } from "../../../services/chatgptImageCache.ts";
+import { saveImageErrorResult, saveImageSuccessResult } from "../../imageGeneration.ts";
+
+export const CHATGPT_WEB_IMAGE_MARKDOWN_RE = /!\[[^\]]*\]\(([^)\s]+)\)/g;
+export const CHATGPT_WEB_IMAGE_ID_RE =
+  /\/v1\/chatgpt-web\/image\/([a-f0-9]{16,64})(?=[?\s"'<>)]|$)/i;
+
+export function extractMarkdownImageUrls(text: string): string[] {
+  const urls: string[] = [];
+  // String.prototype.matchAll consumes a fresh iterator and ignores the
+  // regex's lastIndex, so no manual reset is required.
+  for (const match of text.matchAll(CHATGPT_WEB_IMAGE_MARKDOWN_RE)) {
+    if (match[1]) urls.push(match[1]);
+  }
+  return urls;
+}
+
+export function buildChatGptWebImagePrompt(body): string {
+  const prompt = String(body.prompt || "").trim();
+  const details: string[] = [`Create an image for this prompt: ${prompt}`];
+  if (typeof body.size === "string" && body.size.trim()) {
+    details.push(`Requested size: ${body.size.trim()}.`);
+  }
+  if (typeof body.quality === "string" && body.quality.trim()) {
+    details.push(`Requested quality: ${body.quality.trim()}.`);
+  }
+  if (typeof body.style === "string" && body.style.trim()) {
+    details.push(`Requested style: ${body.style.trim()}.`);
+  }
+  return details.join("\n");
+}
+
+export async function handleChatGptWebImageGeneration({
+  model,
+  provider,
+  body,
+  credentials,
+  log,
+  signal,
+  clientHeaders,
+}) {
+  const startTime = Date.now();
+  const prompt = typeof body.prompt === "string" ? body.prompt.trim() : "";
+  if (!prompt) {
+    return saveImageErrorResult({
+      provider,
+      model,
+      status: 400,
+      startTime,
+      error: "Prompt is required for ChatGPT Web image generation",
+    });
+  }
+
+  if (!credentials?.apiKey) {
+    return saveImageErrorResult({
+      provider,
+      model,
+      status: 401,
+      startTime,
+      error: "ChatGPT Web credentials missing session cookie",
+    });
+  }
+
+  // Each image is one chatgpt.com chat turn (~30s). Cap at 4 (matches OpenAI's
+  // own limit for GPT Image models) so a stray n=1000 doesn't pin the
+  // executor for hours before the upstream HTTP timeout fires.
+  const CHATGPT_WEB_IMAGE_N_MAX = 4;
+  const rawCount = Number.isInteger(body.n) && (body.n as number) > 0 ? (body.n as number) : 1;
+  if (rawCount > CHATGPT_WEB_IMAGE_N_MAX) {
+    return saveImageErrorResult({
+      provider,
+      model,
+      status: 400,
+      startTime,
+      error: `ChatGPT Web image generation supports n=1..${CHATGPT_WEB_IMAGE_N_MAX} (got ${rawCount}); each n is a separate ~30s chat turn.`,
+    });
+  }
+  const requestedCount = rawCount;
+  if (log && requestedCount > 1) {
+    log.warn(
+      "IMAGE",
+      `ChatGPT Web returns one image per chat turn; requested n=${requestedCount} will run sequentially`
+    );
+  }
+
+  const wantsBase64 = body.response_format === "b64_json";
+  const images: Array<{ url?: string; b64_json?: string }> = [];
+  const requestBody = {
+    model,
+    prompt: prompt.slice(0, 500),
+    size: body.size || undefined,
+    quality: body.quality || undefined,
+  };
+
+  for (let i = 0; i < requestedCount; i++) {
+    const executor = new ChatGptWebExecutor();
+    const result = await executor.execute({
+      model,
+      body: {
+        messages: [{ role: "user", content: buildChatGptWebImagePrompt(body) }],
+      },
+      stream: false,
+      credentials,
+      signal,
+      log,
+      clientHeaders,
+    });
+
+    const responseText = await result.response.text();
+    if (result.response.status >= 400) {
+      return saveImageErrorResult({
+        provider,
+        model,
+        status: result.response.status,
+        startTime,
+        error: responseText,
+        requestBody,
+      });
+    }
+
+    let content = "";
+    try {
+      const json = JSON.parse(responseText);
+      content = String(json?.choices?.[0]?.message?.content || "");
+    } catch {
+      content = responseText;
+    }
+
+    const urls = extractMarkdownImageUrls(content);
+    if (urls.length === 0) {
+      return saveImageErrorResult({
+        provider,
+        model,
+        status: 502,
+        startTime,
+        error: `ChatGPT Web completed without returning image markdown: ${content.slice(0, 300)}`,
+        requestBody,
+      });
+    }
+
+    for (const url of urls) {
+      if (!wantsBase64) {
+        images.push({ url });
+        continue;
+      }
+      const id = url.match(CHATGPT_WEB_IMAGE_ID_RE)?.[1];
+      const cached = id ? getChatGptImage(id) : null;
+      if (!cached) {
+        return saveImageErrorResult({
+          provider,
+          model,
+          status: 502,
+          startTime,
+          error: "ChatGPT Web image bytes expired before b64_json conversion",
+          requestBody,
+        });
+      }
+      images.push({ b64_json: cached.bytes.toString("base64") });
+    }
+  }
+
+  return saveImageSuccessResult({
+    provider,
+    model,
+    startTime,
+    requestBody,
+    responseBody: { images_count: images.length },
+    images,
+  });
+}
diff --git a/open-sse/handlers/imageGeneration/providers/comfyUI.ts b/open-sse/handlers/imageGeneration/providers/comfyUI.ts
new file mode 100644
index 0000000000..4540c52a0c
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/comfyUI.ts
@@ -0,0 +1,116 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: comfyui | Module: comfyUI | Lines: 3213-3314 (102 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { randomUUID } from "crypto";
+import { saveCallLog } from "@/lib/usageDb";
+import { sanitizeErrorMessage } from "../../../utils/error.ts";
+import {
+  submitComfyWorkflow,
+  pollComfyResult,
+  fetchComfyOutput,
+  extractComfyOutputFiles,
+} from "../../../utils/comfyuiClient.ts";
+
+export async function handleComfyUIImageGeneration({ model, provider, providerConfig, body, log }) {
+  const startTime = Date.now();
+  const [width, height] = (body.size || "1024x1024").split("x").map(Number);
+
+  // Default txt2img workflow template for ComfyUI
+  const workflow = {
+    "3": {
+      class_type: "KSampler",
+      inputs: {
+        seed: parseInt(randomUUID().replace(/-/g, "").substring(0, 8), 16) % 2 ** 32,
+        steps: body.steps || 20,
+        cfg: body.cfg_scale || 7,
+        sampler_name: "euler",
+        scheduler: "normal",
+        denoise: 1,
+        model: ["4", 0],
+        positive: ["6", 0],
+        negative: ["7", 0],
+        latent_image: ["5", 0],
+      },
+    },
+    "4": {
+      class_type: "CheckpointLoaderSimple",
+      inputs: { ckpt_name: model },
+    },
+    "5": {
+      class_type: "EmptyLatentImage",
+      inputs: { width: width || 1024, height: height || 1024, batch_size: body.n || 1 },
+    },
+    "6": {
+      class_type: "CLIPTextEncode",
+      inputs: { text: body.prompt, clip: ["4", 1] },
+    },
+    "7": {
+      class_type: "CLIPTextEncode",
+      inputs: { text: body.negative_prompt || "", clip: ["4", 1] },
+    },
+    "8": {
+      class_type: "VAEDecode",
+      inputs: { samples: ["3", 0], vae: ["4", 2] },
+    },
+    "9": {
+      class_type: "SaveImage",
+      inputs: { filename_prefix: "omniroute", images: ["8", 0] },
+    },
+  };
+
+  if (log) {
+    const promptPreview = String(body.prompt ?? "").slice(0, 60);
+    log.info("IMAGE", `${provider}/${model} (comfyui) | prompt: "${promptPreview}..."`);
+  }
+
+  try {
+    const promptId = await submitComfyWorkflow(providerConfig.baseUrl, workflow);
+    const historyEntry = await pollComfyResult(providerConfig.baseUrl, promptId);
+    const outputFiles = extractComfyOutputFiles(historyEntry);
+
+    const images = [];
+    for (const file of outputFiles) {
+      const buffer = await fetchComfyOutput(
+        providerConfig.baseUrl,
+        file.filename,
+        file.subfolder,
+        file.type
+      );
+      const base64 = Buffer.from(buffer).toString("base64");
+      images.push({ b64_json: base64, revised_prompt: body.prompt });
+    }
+
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 200,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      responseBody: { images_count: images.length },
+    }).catch(() => {});
+
+    return {
+      success: true,
+      data: { created: Math.floor(Date.now() / 1000), data: images },
+    };
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} comfyui error: ${err.message}`);
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: err.message,
+    }).catch(() => {});
+    return {
+      success: false,
+      status: 502,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    };
+  }
+}
+
diff --git a/open-sse/handlers/imageGeneration/providers/haiper.ts b/open-sse/handlers/imageGeneration/providers/haiper.ts
new file mode 100644
index 0000000000..f22ad35cd8
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/haiper.ts
@@ -0,0 +1,120 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: haiper | Module: haiper | Lines: 3315-3426 (112 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { saveCallLog } from "@/lib/usageDb";
+import { sleep } from "../../../utils/sleep.ts";
+import { sanitizeErrorMessage } from "../../../utils/error.ts";
+
+export async function handleHaiperImageGeneration({
+  model,
+  provider,
+  providerConfig,
+  body,
+  credentials,
+  log,
+}) {
+  const startTime = Date.now();
+  const token = credentials?.apiKey || "";
+  const prompt = typeof body.prompt === "string" ? body.prompt : String(body.prompt ?? "");
+  if (log) {
+    log.info("IMAGE", `${provider}/${model} (haiper) | prompt: "${prompt.slice(0, 60)}..."`);
+  }
+  try {
+    const res = await fetch(providerConfig.baseUrl, {
+      method: "POST",
+      headers: { "Content-Type": "application/json", HAIPER_KEY: token },
+      body: JSON.stringify({ prompt, aspect_ratio: body.aspect_ratio || "16:9" }),
+    });
+    if (!res.ok) {
+      const errorText = await res.text();
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: res.status,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: errorText.slice(0, 500),
+      }).catch(() => {});
+      return { success: false, status: res.status, error: errorText };
+    }
+    const { job_id } = await res.json();
+    const deadline = Date.now() + 300000;
+    while (Date.now() < deadline) {
+      await sleep(5000);
+      const statusRes = await fetch(`${providerConfig.statusUrl}/${job_id}`, {
+        headers: { HAIPER_KEY: token },
+      });
+      const status = await statusRes.json();
+      if (status.status === "completed" || status.status === "succeeded") {
+        const imgUrl = status.creation_url || status.output?.image_url;
+        if (imgUrl) {
+          const imgRes = await fetch(imgUrl);
+          if (!imgRes.ok) {
+            return {
+              success: false,
+              status: imgRes.status,
+              error: `Failed to download image: ${imgRes.status}`,
+            };
+          }
+          const buf = await imgRes.arrayBuffer();
+          saveCallLog({
+            method: "POST",
+            path: "/v1/images/generations",
+            status: 200,
+            model: `${provider}/${model}`,
+            provider,
+            duration: Date.now() - startTime,
+          }).catch(() => {});
+          return {
+            success: true,
+            data: {
+              created: Math.floor(Date.now() / 1000),
+              data: [{ b64_json: Buffer.from(buf).toString("base64") }],
+            },
+          };
+        }
+      }
+      if (status.status === "failed") {
+        saveCallLog({
+          method: "POST",
+          path: "/v1/images/generations",
+          status: 502,
+          model: `${provider}/${model}`,
+          provider,
+          duration: Date.now() - startTime,
+          error: "Haiper image generation failed",
+        }).catch(() => {});
+        return { success: false, status: 502, error: "Haiper image generation failed" };
+      }
+    }
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 504,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: "Haiper image generation timed out",
+    }).catch(() => {});
+    return { success: false, status: 504, error: "Haiper image generation timed out" };
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} haiper error: ${err.message}`);
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: err.message,
+    }).catch(() => {});
+    return {
+      success: false,
+      status: 502,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    };
+  }
+}
+
diff --git a/open-sse/handlers/imageGeneration/providers/hyperbolic.ts b/open-sse/handlers/imageGeneration/providers/hyperbolic.ts
new file mode 100644
index 0000000000..528695c30d
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/hyperbolic.ts
@@ -0,0 +1,100 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: hyperbolic | Module: hyperbolic | Lines: 2661-2758 (98 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { saveCallLog } from "@/lib/usageDb";
+import { sanitizeErrorMessage } from "../../../utils/error.ts";
+
+export async function handleHyperbolicImageGeneration({
+  model,
+  provider,
+  providerConfig,
+  body,
+  credentials,
+  log,
+}) {
+  const startTime = Date.now();
+  const token = credentials.apiKey || credentials.accessToken;
+
+  const [width, height] = (body.size || "1024x1024").split("x").map(Number);
+
+  const upstreamBody = {
+    model_name: model,
+    prompt: body.prompt,
+    height: height || 1024,
+    width: width || 1024,
+    backend: "auto",
+  };
+
+  if (log) {
+    const promptPreview = String(body.prompt ?? "").slice(0, 60);
+    log.info("IMAGE", `${provider}/${model} (hyperbolic) | prompt: "${promptPreview}..."`);
+  }
+
+  try {
+    const response = await fetch(providerConfig.baseUrl, {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Authorization: `Bearer ${token}`,
+      },
+      body: JSON.stringify(upstreamBody),
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      if (log)
+        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
+
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: response.status,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: errorText.slice(0, 500),
+      }).catch(() => {});
+
+      return { success: false, status: response.status, error: errorText };
+    }
+
+    const data = await response.json();
+    // Transform { images: [{ image: base64 }] } → OpenAI format
+    const images = (data.images || []).map((img) => ({
+      b64_json: img.image,
+      revised_prompt: body.prompt,
+    }));
+
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 200,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      responseBody: { images_count: images.length },
+    }).catch(() => {});
+
+    return {
+      success: true,
+      data: { created: Math.floor(Date.now() / 1000), data: images },
+    };
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} fetch error: ${err.message}`);
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: err.message,
+    }).catch(() => {});
+    return {
+      success: false,
+      status: 502,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    };
+  }
+}
diff --git a/open-sse/handlers/imageGeneration/providers/ideogram.ts b/open-sse/handlers/imageGeneration/providers/ideogram.ts
new file mode 100644
index 0000000000..824ca45385
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/ideogram.ts
@@ -0,0 +1,96 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: ideogram | Module: ideogram | Lines: 3559-3669 (111 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { saveCallLog } from "@/lib/usageDb";
+import { sanitizeErrorMessage } from "../../../utils/error.ts";
+
+export async function handleIdeogramImageGeneration({
+  model,
+  provider,
+  providerConfig,
+  body,
+  credentials,
+  log,
+}) {
+  const startTime = Date.now();
+  const token = credentials?.apiKey || "";
+  const prompt = typeof body.prompt === "string" ? body.prompt : String(body.prompt ?? "");
+  if (log) {
+    log.info("IMAGE", `${provider}/${model} (ideogram) | prompt: "${prompt.slice(0, 60)}..."`);
+  }
+  try {
+    const res = await fetch(providerConfig.baseUrl, {
+      method: "POST",
+      headers: { "Content-Type": "application/json", "Api-Key": token },
+      body: JSON.stringify({ prompt, aspect_ratio: "ASPECT_16_9", model: model || "V_3" }),
+    });
+    if (!res.ok) {
+      const errorText = await res.text();
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: res.status,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: errorText.slice(0, 500),
+      }).catch(() => {});
+      return { success: false, status: res.status, error: errorText };
+    }
+    const data = await res.json();
+    if (data.data && data.data.length > 0) {
+      const imgUrl = data.data[0].url;
+      const imgRes = await fetch(imgUrl);
+      if (!imgRes.ok) {
+        return {
+          success: false,
+          status: imgRes.status,
+          error: `Failed to download image: ${imgRes.status}`,
+        };
+      }
+      const buf = await imgRes.arrayBuffer();
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: 200,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+      }).catch(() => {});
+      return {
+        success: true,
+        data: {
+          created: Math.floor(Date.now() / 1000),
+          data: [{ b64_json: Buffer.from(buf).toString("base64") }],
+        },
+      };
+    }
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: "No images returned from Ideogram",
+    }).catch(() => {});
+    return { success: false, status: 502, error: "No images returned from Ideogram" };
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} ideogram error: ${err.message}`);
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: err.message,
+    }).catch(() => {});
+    return {
+      success: false,
+      status: 502,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    };
+  }
+}
diff --git a/open-sse/handlers/imageGeneration/providers/imagen3.ts b/open-sse/handlers/imageGeneration/providers/imagen3.ts
new file mode 100644
index 0000000000..c53a0016c2
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/imagen3.ts
@@ -0,0 +1,136 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: imagen3 | Module: imagen3 | Lines: 3670-3777 (108 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { saveCallLog } from "@/lib/usageDb";
+import { mapImageSize } from "../../../translator/image/sizeMapper.ts";
+
+type Imagen3ImageGenArgs = {
+  model: string;
+  provider: string;
+  providerConfig: { baseUrl: string };
+  body: { prompt?: string; size?: string; n?: number };
+  credentials: { apiKey?: string; accessToken?: string };
+  log?: {
+    info?: (tag: string, msg: string) => void;
+    error?: (tag: string, msg: string) => void;
+  } | null;
+};
+
+type Imagen3NormalizedImage = {
+  b64_json?: unknown;
+  url?: unknown;
+  revised_prompt?: string;
+};
+
+/**
+ * Handle Imagen 3 image generation
+ */
+export async function handleImagen3ImageGeneration({
+  model,
+  provider,
+  providerConfig,
+  body,
+  credentials,
+  log,
+}: Imagen3ImageGenArgs) {
+  const startTime = Date.now();
+  const token = credentials.apiKey || credentials.accessToken;
+  const aspectRatio = mapImageSize(body.size);
+
+  const upstreamBody = {
+    prompt: body.prompt,
+    aspect_ratio: aspectRatio,
+    number_of_images: body.n ?? 1,
+  };
+
+  if (log) {
+    const promptPreview = String(body.prompt ?? "").slice(0, 60);
+    log.info(
+      "IMAGE",
+      `${provider}/${model} (imagen3) | prompt: "${promptPreview}..." | aspect_ratio: ${aspectRatio}`
+    );
+  }
+
+  try {
+    const response = await fetch(providerConfig.baseUrl, {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Authorization: `Bearer ${token}`,
+      },
+      body: JSON.stringify(upstreamBody),
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      if (log)
+        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
+
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: response.status,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: errorText.slice(0, 500),
+        requestBody: upstreamBody,
+      }).catch(() => {});
+
+      return { success: false, status: response.status, error: errorText };
+    }
+
+    const data = await response.json();
+
+    // Normalize response to OpenAI format
+    const images: Imagen3NormalizedImage[] = [];
+    if (Array.isArray(data.images)) {
+      images.push(
+        ...data.images.map((img: Record<string, unknown>) => ({
+          b64_json: img.image ?? img.b64_json ?? img.url ?? img,
+          revised_prompt: body.prompt,
+        }))
+      );
+    } else if (Array.isArray(data.data)) {
+      images.push(...data.data);
+    } else if (data.url || data.b64_json || data.image) {
+      images.push({
+        b64_json: data.image || data.b64_json || data.url,
+        url: data.url,
+        revised_prompt: body.prompt,
+      });
+    }
+
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 200,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      responseBody: { images_count: images.length },
+    }).catch(() => {});
+
+    return {
+      success: true,
+      data: { created: data.created || Math.floor(Date.now() / 1000), data: images },
+    };
+  } catch (err: unknown) {
+    const errMsg = err instanceof Error ? err.message : String(err);
+    if (log) log.error("IMAGE", `${provider} fetch error: ${errMsg}`);
+
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: errMsg,
+    }).catch(() => {});
+
+    return { success: false, status: 502, error: `Image provider error: ${errMsg}` };
+  }
+}
+
diff --git a/open-sse/handlers/imageGeneration/providers/leonardo.ts b/open-sse/handlers/imageGeneration/providers/leonardo.ts
new file mode 100644
index 0000000000..c407693f46
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/leonardo.ts
@@ -0,0 +1,140 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: leonardo | Module: leonardo | Lines: 3427-3558 (132 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { saveCallLog } from "@/lib/usageDb";
+import { sleep } from "../../../utils/sleep.ts";
+import { sanitizeErrorMessage } from "../../../utils/error.ts";
+
+export async function handleLeonardoImageGeneration({
+  model,
+  provider,
+  providerConfig,
+  body,
+  credentials,
+  log,
+}) {
+  const startTime = Date.now();
+  const token = credentials?.apiKey || "";
+  const prompt = typeof body.prompt === "string" ? body.prompt : String(body.prompt ?? "");
+  if (log) {
+    log.info("IMAGE", `${provider}/${model} (leonardo) | prompt: "${prompt.slice(0, 60)}..."`);
+  }
+  try {
+    const res = await fetch(providerConfig.baseUrl, {
+      method: "POST",
+      headers: { "Content-Type": "application/json", Authorization: `Bearer ${token}` },
+      body: JSON.stringify({
+        modelId: model || "phoenix",
+        prompt,
+        width: body.width || 1024,
+        height: body.height || 1024,
+        num_images: 1,
+      }),
+    });
+    if (!res.ok) {
+      const errorText = await res.text();
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: res.status,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: errorText.slice(0, 500),
+      }).catch(() => {});
+      return { success: false, status: res.status, error: errorText };
+    }
+    const { sdGenerationJob } = await res.json();
+    const genId = sdGenerationJob?.generationId;
+    if (!genId) {
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: 502,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: "No generation ID returned",
+      }).catch(() => {});
+      return { success: false, status: 502, error: "No generation ID returned" };
+    }
+    const deadline = Date.now() + 300000;
+    while (Date.now() < deadline) {
+      await sleep(5000);
+      const statusRes = await fetch(`${providerConfig.baseUrl}/${genId}`, {
+        headers: { Authorization: `Bearer ${token}` },
+      });
+      const status = await statusRes.json();
+      const gen = status.generations_by_pk || status;
+      if (gen.status === "COMPLETE") {
+        const imgUrl = gen.generated_images?.[0]?.url;
+        if (imgUrl) {
+          const imgRes = await fetch(imgUrl);
+          if (!imgRes.ok) {
+            return {
+              success: false,
+              status: imgRes.status,
+              error: `Failed to download image: ${imgRes.status}`,
+            };
+          }
+          const buf = await imgRes.arrayBuffer();
+          saveCallLog({
+            method: "POST",
+            path: "/v1/images/generations",
+            status: 200,
+            model: `${provider}/${model}`,
+            provider,
+            duration: Date.now() - startTime,
+          }).catch(() => {});
+          return {
+            success: true,
+            data: {
+              created: Math.floor(Date.now() / 1000),
+              data: [{ b64_json: Buffer.from(buf).toString("base64") }],
+            },
+          };
+        }
+      }
+      if (gen.status === "FAILED") {
+        saveCallLog({
+          method: "POST",
+          path: "/v1/images/generations",
+          status: 502,
+          model: `${provider}/${model}`,
+          provider,
+          duration: Date.now() - startTime,
+          error: "Leonardo image generation failed",
+        }).catch(() => {});
+        return { success: false, status: 502, error: "Leonardo image generation failed" };
+      }
+    }
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 504,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: "Leonardo image generation timed out",
+    }).catch(() => {});
+    return { success: false, status: 504, error: "Leonardo image generation timed out" };
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} leonardo error: ${err.message}`);
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: err.message,
+    }).catch(() => {});
+    return {
+      success: false,
+      status: 502,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    };
+  }
+}
+
diff --git a/open-sse/handlers/imageGeneration/providers/sdWebUI.ts b/open-sse/handlers/imageGeneration/providers/sdWebUI.ts
new file mode 100644
index 0000000000..aa4576ef22
--- /dev/null
+++ b/open-sse/handlers/imageGeneration/providers/sdWebUI.ts
@@ -0,0 +1,94 @@
+// Auto-extracted from open-sse/handlers/imageGeneration.ts in PR-#4582-batch
+// Family: sd-webui | Module: sdWebUI | Lines: 3121-3212 (92 LOC)
+// Ref: see open-sse/handlers/imageGeneration.ts top-of-file comment for split rationale
+
+import { saveCallLog } from "@/lib/usageDb";
+import { sanitizeErrorMessage } from "../../../utils/error.ts";
+
+export async function handleSDWebUIImageGeneration({ model, provider, providerConfig, body, log }) {
+  const startTime = Date.now();
+  const [width, height] = (body.size || "512x512").split("x").map(Number);
+
+  const upstreamBody = {
+    prompt: body.prompt,
+    negative_prompt: body.negative_prompt || "",
+    width: width || 512,
+    height: height || 512,
+    steps: body.steps || 20,
+    cfg_scale: body.cfg_scale || 7,
+    sampler_name: body.sampler || "Euler a",
+    batch_size: body.n || 1,
+    override_settings: {
+      sd_model_checkpoint: model,
+    },
+  };
+
+  if (log) {
+    const promptPreview = String(body.prompt ?? "").slice(0, 60);
+    log.info("IMAGE", `${provider}/${model} (sdwebui) | prompt: "${promptPreview}..."`);
+  }
+
+  try {
+    const response = await fetch(providerConfig.baseUrl, {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify(upstreamBody),
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      if (log)
+        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
+
+      saveCallLog({
+        method: "POST",
+        path: "/v1/images/generations",
+        status: response.status,
+        model: `${provider}/${model}`,
+        provider,
+        duration: Date.now() - startTime,
+        error: errorText.slice(0, 500),
+      }).catch(() => {});
+
+      return { success: false, status: response.status, error: errorText };
+    }
+
+    const data = await response.json();
+    // SD WebUI returns { images: ["base64...", ...] }
+    const images = (data.images || []).map((b64) => ({
+      b64_json: b64,
+      revised_prompt: body.prompt,
+    }));
+
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 200,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      responseBody: { images_count: images.length },
+    }).catch(() => {});
+
+    return {
+      success: true,
+      data: { created: Math.floor(Date.now() / 1000), data: images },
+    };
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} sdwebui error: ${err.message}`);
+    saveCallLog({
+      method: "POST",
+      path: "/v1/images/generations",
+      status: 502,
+      model: `${provider}/${model}`,
+      provider,
+      duration: Date.now() - startTime,
+      error: err.message,
+    }).catch(() => {});
+    return {
+      success: false,
+      status: 502,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    };
+  }
+}