diff --git a/src/server/services/brandMatcher.test.ts b/src/server/services/brandMatcher.test.ts
new file mode 100644
index 0000000..4fe7e67
--- /dev/null
+++ b/src/server/services/brandMatcher.test.ts
@@ -0,0 +1,41 @@
+import { describe, expect, it } from 'vitest';
+import { getAllBrandNames, getBlockedBrandRules, isModelBlockedByBrand } from './brandMatcher.js';
+
+describe('brandMatcher', () => {
+  it('exposes newly supported provider and platform brands', () => {
+    const brands = getAllBrandNames();
+
+    expect(brands).toContain('OpenRouter');
+    expect(brands).toContain('Groq');
+    expect(brands).toContain('DeepInfra');
+    expect(brands).toContain('Fireworks');
+    expect(brands).toContain('Together AI');
+    expect(brands).toContain('AI21 Labs');
+    expect(brands).toContain('百川智能');
+    expect(brands).toContain('Amazon Nova');
+    expect(brands).toContain('百炼');
+    expect(brands).toContain('Arcee');
+    expect(brands).toContain('Xiaomi MiMo');
+    expect(brands).toContain('LongCat');
+  });
+
+  it('deduplicates blocked brands and ignores unknown entries', () => {
+    expect(getBlockedBrandRules(['OpenRouter', 'OpenRouter', 'Unknown Brand'])).toEqual(['OpenRouter']);
+  });
+
+  it('uses the shared frontend detection result for global brand blocking', () => {
+    const providerRules = getBlockedBrandRules(['OpenRouter', 'Groq', '百炼', 'LongCat']);
+    expect(isModelBlockedByBrand('openrouter/openrouter-auto', providerRules)).toBe(true);
+    expect(isModelBlockedByBrand('groq/compound-beta', providerRules)).toBe(true);
+    expect(isModelBlockedByBrand('dashscope/wanx2.1-t2i-turbo', providerRules)).toBe(true);
+    expect(isModelBlockedByBrand('LongCat-Flash-Lite', providerRules)).toBe(true);
+
+    const vendorRules = getBlockedBrandRules(['Anthropic', 'Meta', 'Google', 'OpenAI', 'Arcee', 'Xiaomi MiMo']);
+    expect(isModelBlockedByBrand('openrouter/anthropic/claude-3-7-sonnet', vendorRules)).toBe(true);
+    expect(isModelBlockedByBrand('deepinfra/meta-llama/llama-3.3-70b-instruct', vendorRules)).toBe(true);
+    expect(isModelBlockedByBrand('vertexai/google/gemini-2.5-pro', vendorRules)).toBe(true);
+    expect(isModelBlockedByBrand('azureai/gpt-4o', vendorRules)).toBe(true);
+    expect(isModelBlockedByBrand('arcee-ai/trinity-mini', vendorRules)).toBe(true);
+    expect(isModelBlockedByBrand('xiaomi/mimo-v2-pro', vendorRules)).toBe(true);
+  });
+});
diff --git a/src/server/services/brandMatcher.ts b/src/server/services/brandMatcher.ts
index f4a93ac..a5f67c4 100644
--- a/src/server/services/brandMatcher.ts
+++ b/src/server/services/brandMatcher.ts
@@ -1,273 +1,28 @@
-/**
- * Server-side brand matching for global brand filtering.
- *
- * Context-building logic is ported from the frontend BrandIcon.tsx
- * (collectBrandCandidates + buildMatchContext) to ensure identical
- * matching behavior between route display and rebuild filtering.
- */
+import { getAllBrandNames as getSharedBrandNames, getBrand } from '../shared/modelBrand.js';
 
-type MatchMode = 'includes' | 'startsWith' | 'segment' | 'boundary';
-type KeywordRule = { keyword: string; mode: MatchMode };
+export type BlockedBrandRule = string;
 
-const BRAND_RULES: Record<string, KeywordRule[]> = {
-  'OpenAI': [
-    { keyword: 'gpt', mode: 'startsWith' },
-    { keyword: 'chatgpt', mode: 'startsWith' },
-    { keyword: 'dall-e', mode: 'startsWith' },
-    { keyword: 'whisper', mode: 'startsWith' },
-    { keyword: 'text-embedding', mode: 'startsWith' },
-    { keyword: 'text-moderation', mode: 'startsWith' },
-    { keyword: 'davinci', mode: 'startsWith' },
-    { keyword: 'babbage', mode: 'startsWith' },
-    { keyword: 'codex-mini', mode: 'startsWith' },
-    { keyword: 'o1', mode: 'startsWith' },
-    { keyword: 'o3', mode: 'startsWith' },
-    { keyword: 'o4', mode: 'startsWith' },
-    { keyword: 'tts', mode: 'startsWith' },
-  ],
-  'Anthropic': [
-    { keyword: 'claude', mode: 'includes' },
-  ],
-  'Google': [
-    { keyword: 'gemini', mode: 'includes' },
-    { keyword: 'gemma', mode: 'includes' },
-    { keyword: 'google/', mode: 'includes' },
-    { keyword: 'palm', mode: 'includes' },
-    { keyword: 'paligemma', mode: 'includes' },
-    { keyword: 'shieldgemma', mode: 'includes' },
-    { keyword: 'recurrentgemma', mode: 'includes' },
-    { keyword: 'deplot', mode: 'includes' },
-    { keyword: 'codegemma', mode: 'includes' },
-    { keyword: 'imagen', mode: 'includes' },
-    { keyword: 'learnlm', mode: 'includes' },
-    { keyword: 'aqa', mode: 'includes' },
-    { keyword: 'veo', mode: 'startsWith' },
-  ],
-  'DeepSeek': [
-    { keyword: 'deepseek', mode: 'includes' },
-    { keyword: 'ds-chat', mode: 'segment' },
-  ],
-  '通义千问': [
-    { keyword: 'qwen', mode: 'includes' },
-    { keyword: 'qwq', mode: 'includes' },
-    { keyword: 'tongyi', mode: 'includes' },
-  ],
-  '智谱 AI': [
-    { keyword: 'glm', mode: 'includes' },
-    { keyword: 'chatglm', mode: 'includes' },
-    { keyword: 'codegeex', mode: 'includes' },
-    { keyword: 'cogview', mode: 'includes' },
-    { keyword: 'cogvideo', mode: 'includes' },
-  ],
-  'Meta': [
-    { keyword: 'llama', mode: 'includes' },
-    { keyword: 'code-llama', mode: 'includes' },
-    { keyword: 'codellama', mode: 'includes' },
-  ],
-  'Mistral': [
-    { keyword: 'mistral', mode: 'includes' },
-    { keyword: 'mixtral', mode: 'includes' },
-    { keyword: 'codestral', mode: 'includes' },
-    { keyword: 'pixtral', mode: 'includes' },
-    { keyword: 'ministral', mode: 'includes' },
-    { keyword: 'voxtral', mode: 'includes' },
-    { keyword: 'magistral', mode: 'includes' },
-  ],
-  'Moonshot': [
-    { keyword: 'moonshot', mode: 'includes' },
-    { keyword: 'kimi', mode: 'includes' },
-  ],
-  '零一万物': [
-    { keyword: 'yi-', mode: 'startsWith' },
-    { keyword: 'yi', mode: 'boundary' },
-  ],
-  '文心一言': [
-    { keyword: 'ernie', mode: 'includes' },
-    { keyword: 'eb-', mode: 'includes' },
-  ],
-  '讯飞星火': [
-    { keyword: 'spark', mode: 'includes' },
-    { keyword: 'generalv', mode: 'includes' },
-  ],
-  '腾讯混元': [
-    { keyword: 'hunyuan', mode: 'includes' },
-    { keyword: 'tencent-hunyuan', mode: 'includes' },
-  ],
-  '豆包': [
-    { keyword: 'doubao', mode: 'includes' },
-  ],
-  'MiniMax': [
-    { keyword: 'minimax', mode: 'includes' },
-    { keyword: 'abab', mode: 'includes' },
-    { keyword: 'mini2.1', mode: 'segment' },
-  ],
-  'Cohere': [
-    { keyword: 'command', mode: 'includes' },
-    { keyword: 'c4ai-', mode: 'includes' },
-    { keyword: 'embed-', mode: 'startsWith' },
-  ],
-  'Microsoft': [
-    { keyword: 'microsoft/', mode: 'includes' },
-    { keyword: 'phi-', mode: 'includes' },
-    { keyword: 'kosmos', mode: 'includes' },
-    { keyword: 'phi4', mode: 'segment' },
-  ],
-  'xAI': [
-    { keyword: 'grok', mode: 'includes' },
-  ],
-  '阶跃星辰': [
-    { keyword: 'stepfun', mode: 'includes' },
-    { keyword: 'step-', mode: 'startsWith' },
-    { keyword: 'step3', mode: 'startsWith' },
-  ],
-  'Stability': [
-    { keyword: 'flux', mode: 'includes' },
-    { keyword: 'stablediffusion', mode: 'includes' },
-    { keyword: 'stable-diffusion', mode: 'includes' },
-    { keyword: 'sdxl', mode: 'includes' },
-    { keyword: 'sd3', mode: 'startsWith' },
-  ],
-  'NVIDIA': [
-    { keyword: 'nvidia/', mode: 'includes' },
-    { keyword: 'nvclip', mode: 'includes' },
-    { keyword: 'nemotron', mode: 'includes' },
-    { keyword: 'nemoretriever', mode: 'includes' },
-    { keyword: 'neva', mode: 'includes' },
-    { keyword: 'riva-translate', mode: 'includes' },
-    { keyword: 'cosmos', mode: 'includes' },
-    { keyword: 'nv-', mode: 'startsWith' },
-  ],
-  'IBM': [
-    { keyword: 'ibm/', mode: 'includes' },
-    { keyword: 'granite', mode: 'includes' },
-  ],
-  'BAAI': [
-    { keyword: 'baai/', mode: 'includes' },
-    { keyword: 'bge-', mode: 'includes' },
-  ],
-  'ByteDance': [
-    { keyword: 'bytedance', mode: 'includes' },
-    { keyword: 'seed-oss', mode: 'includes' },
-    { keyword: 'kolors', mode: 'includes' },
-    { keyword: 'kwai', mode: 'includes' },
-    { keyword: 'kwaipilot', mode: 'includes' },
-    { keyword: 'wan-', mode: 'startsWith' },
-    { keyword: 'kat-', mode: 'startsWith' },
-  ],
-  'InternLM': [
-    { keyword: 'internlm', mode: 'includes' },
-  ],
-  'Midjourney': [
-    { keyword: 'midjourney', mode: 'includes' },
-    { keyword: 'mj_', mode: 'startsWith' },
-  ],
-  'DeepL': [
-    { keyword: 'deepl/', mode: 'includes' },
-    { keyword: 'deepl-', mode: 'startsWith' },
-  ],
-  'Jina AI': [
-    { keyword: 'jina', mode: 'includes' },
-  ],
-};
-
-// ── Context building (ported from frontend BrandIcon.tsx) ──
-
-function stripCommonWrappers(value: string): string {
-  return value
-    .replace(/^(?:\[[^\]]+\]|【[^】]+】)\s*/g, '')
-    .replace(/^re:\s*/g, '')
-    .replace(/^\^+/, '')
-    .replace(/\$+$/, '')
-    .trim();
-}
-
-/**
- * Recursively split model name on `/`, `:`, `,` to build all candidate strings.
- * Mirrors the frontend collectBrandCandidates exactly.
- */
-function collectCandidates(modelName: string): string[] {
-  const queue: string[] = [];
-  const seen = new Set<string>();
-  const push = (value: string) => {
-    const normalized = value.trim().toLowerCase();
-    if (!normalized || seen.has(normalized)) return;
-    seen.add(normalized);
-    queue.push(normalized);
-  };
-
-  push(modelName);
-
-  for (let i = 0; i < queue.length; i++) {
-    const candidate = queue[i]!;
-    const cleaned = stripCommonWrappers(candidate);
-    push(cleaned);
-    if (cleaned.includes('/')) for (const part of cleaned.split('/')) push(part);
-    if (cleaned.includes(':')) for (const part of cleaned.split(':')) push(part);
-    if (cleaned.includes(',')) for (const part of cleaned.split(',')) push(part);
-  }
-
-  return queue;
-}
-
-type MatchContext = {
-  raw: string;       // first candidate (normalized full name)
-  candidates: string[];  // all candidates from recursive splitting
-  segments: string[];    // candidates split on /,:,\s (NOT on - or _)
-};
-
-function buildMatchContext(modelName: string): MatchContext {
-  const candidates = collectCandidates(modelName);
-  const raw = candidates[0] || modelName.trim().toLowerCase();
-  // Segments split on /,:,whitespace only — NOT on - or _ (matches frontend)
-  const segments = Array.from(new Set(
-    candidates
-      .flatMap((c) => c.split(/[/:,\s]+/g))
-      .map((s) => s.trim())
-      .filter(Boolean),
-  ));
-  return { raw, candidates, segments };
-}
-
-// ── Matching functions (mirror frontend includesAny / startsWithAny / hasExactSegment / matchesBoundary) ──
-
-function matchesRule(ctx: MatchContext, rule: KeywordRule): boolean {
-  switch (rule.mode) {
-    case 'includes':
-      return ctx.raw.includes(rule.keyword)
-        || ctx.candidates.some((c) => c.includes(rule.keyword));
-    case 'startsWith':
-      return ctx.raw.startsWith(rule.keyword)
-        || ctx.segments.some((s) => s.startsWith(rule.keyword))
-        || ctx.candidates.some((c) => c.startsWith(rule.keyword));
-    case 'segment':
-      return ctx.segments.includes(rule.keyword);
-    case 'boundary': {
-      const pattern = new RegExp(`(^|[/:_\\-\\s])${rule.keyword}(?=$|[/:_\\-\\s])`);
-      return pattern.test(ctx.raw) || ctx.candidates.some((c) => pattern.test(c));
-    }
-    default:
-      return false;
-  }
-}
-
-// ── Public API ──
+const KNOWN_BRANDS = new Set(getSharedBrandNames());
+const KNOWN_BRAND_LIST = Array.from(KNOWN_BRANDS);
 
 export function getAllBrandNames(): string[] {
-  return Object.keys(BRAND_RULES);
+  return KNOWN_BRAND_LIST;
 }
 
-export function getBlockedBrandRules(blockedBrands: string[]): KeywordRule[] {
-  const rules: KeywordRule[] = [];
+export function getBlockedBrandRules(blockedBrands: string[]): BlockedBrandRule[] {
+  const seen = new Set<string>();
+  const rules: string[] = [];
   for (const brand of blockedBrands) {
-    const brandRules = BRAND_RULES[brand];
-    if (brandRules) rules.push(...brandRules);
+    const normalized = String(brand || '').trim();
+    if (!normalized || seen.has(normalized) || !KNOWN_BRANDS.has(normalized)) continue;
+    seen.add(normalized);
+    rules.push(normalized);
   }
   return rules;
 }
 
-export function isModelBlockedByBrand(modelName: string, rules: KeywordRule[]): boolean {
+export function isModelBlockedByBrand(modelName: string, rules: BlockedBrandRule[]): boolean {
   if (!modelName || rules.length === 0) return false;
-  const ctx = buildMatchContext(modelName);
-  if (!ctx.raw) return false;
-  return rules.some((rule) => matchesRule(ctx, rule));
+  const brand = getBrand(modelName);
+  return !!brand && rules.includes(brand.name);
 }
diff --git a/src/server/shared/modelBrand.ts b/src/server/shared/modelBrand.ts
new file mode 100644
index 0000000..de93d1a
--- /dev/null
+++ b/src/server/shared/modelBrand.ts
@@ -0,0 +1,806 @@
+export interface BrandMatchContext {
+  raw: string;
+  cleaned: string;
+  segments: string[];
+  candidates: string[];
+}
+
+export interface BrandInfo {
+  name: string;
+  icon: string;
+  color: string;
+}
+
+export type BrandMatchMode = 'includes' | 'startsWith' | 'segment' | 'boundary';
+
+type BrandRule = {
+  keyword: string;
+  mode: BrandMatchMode;
+};
+
+type BrandDefinition = BrandInfo & {
+  rules: BrandRule[];
+};
+
+const BRAND_DEFINITIONS: BrandDefinition[] = [
+  {
+    name: 'OpenAI',
+    icon: 'openai',
+    color: 'linear-gradient(135deg, #10a37f, #1a7f5a)',
+    rules: [
+      { keyword: 'gpt', mode: 'startsWith' },
+      { keyword: 'chatgpt', mode: 'startsWith' },
+      { keyword: 'dall-e', mode: 'startsWith' },
+      { keyword: 'whisper', mode: 'startsWith' },
+      { keyword: 'text-embedding', mode: 'startsWith' },
+      { keyword: 'text-moderation', mode: 'startsWith' },
+      { keyword: 'davinci', mode: 'startsWith' },
+      { keyword: 'babbage', mode: 'startsWith' },
+      { keyword: 'codex-mini', mode: 'startsWith' },
+      { keyword: 'o1', mode: 'startsWith' },
+      { keyword: 'o3', mode: 'startsWith' },
+      { keyword: 'o4', mode: 'startsWith' },
+      { keyword: 'tts', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'Anthropic',
+    icon: 'claude-color',
+    color: 'linear-gradient(135deg, #d4a574, #c4956a)',
+    rules: [
+      { keyword: 'claude', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Google',
+    icon: 'gemini-color',
+    color: 'linear-gradient(135deg, #4285f4, #34a853)',
+    rules: [
+      { keyword: 'gemini', mode: 'includes' },
+      { keyword: 'gemma', mode: 'includes' },
+      { keyword: 'google/', mode: 'includes' },
+      { keyword: 'palm', mode: 'includes' },
+      { keyword: 'paligemma', mode: 'includes' },
+      { keyword: 'shieldgemma', mode: 'includes' },
+      { keyword: 'recurrentgemma', mode: 'includes' },
+      { keyword: 'deplot', mode: 'includes' },
+      { keyword: 'codegemma', mode: 'includes' },
+      { keyword: 'imagen', mode: 'includes' },
+      { keyword: 'learnlm', mode: 'includes' },
+      { keyword: 'aqa', mode: 'includes' },
+      { keyword: 'veo', mode: 'startsWith' },
+      { keyword: 'google/', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'DeepSeek',
+    icon: 'deepseek-color',
+    color: 'linear-gradient(135deg, #4d6bfe, #44a3ec)',
+    rules: [
+      { keyword: 'deepseek', mode: 'includes' },
+      { keyword: 'ds-chat', mode: 'segment' },
+    ],
+  },
+  {
+    name: '通义千问',
+    icon: 'qwen-color',
+    color: 'linear-gradient(135deg, #615cf7, #9b8afb)',
+    rules: [
+      { keyword: 'qwen', mode: 'includes' },
+      { keyword: 'qwq', mode: 'includes' },
+      { keyword: 'tongyi', mode: 'includes' },
+    ],
+  },
+  {
+    name: '智谱 AI',
+    icon: 'zhipu-color',
+    color: 'linear-gradient(135deg, #3b6cf5, #6366f1)',
+    rules: [
+      { keyword: 'glm', mode: 'includes' },
+      { keyword: 'chatglm', mode: 'includes' },
+      { keyword: 'codegeex', mode: 'includes' },
+      { keyword: 'cogview', mode: 'includes' },
+      { keyword: 'cogvideo', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Meta',
+    icon: 'meta-color',
+    color: 'linear-gradient(135deg, #0668E1, #1877f2)',
+    rules: [
+      { keyword: 'llama', mode: 'includes' },
+      { keyword: 'code-llama', mode: 'includes' },
+      { keyword: 'codellama', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Mistral',
+    icon: 'mistral-color',
+    color: 'linear-gradient(135deg, #f7d046, #f2a900)',
+    rules: [
+      { keyword: 'mistral', mode: 'includes' },
+      { keyword: 'mixtral', mode: 'includes' },
+      { keyword: 'codestral', mode: 'includes' },
+      { keyword: 'pixtral', mode: 'includes' },
+      { keyword: 'ministral', mode: 'includes' },
+      { keyword: 'voxtral', mode: 'includes' },
+      { keyword: 'magistral', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Moonshot',
+    icon: 'moonshot',
+    color: 'linear-gradient(135deg, #000000, #333333)',
+    rules: [
+      { keyword: 'moonshot', mode: 'includes' },
+      { keyword: 'kimi', mode: 'includes' },
+    ],
+  },
+  {
+    name: '零一万物',
+    icon: 'yi-color',
+    color: 'linear-gradient(135deg, #1d4ed8, #3b82f6)',
+    rules: [
+      { keyword: 'yi-', mode: 'startsWith' },
+      { keyword: 'yi', mode: 'boundary' },
+    ],
+  },
+  {
+    name: '文心一言',
+    icon: 'wenxin-color',
+    color: 'linear-gradient(135deg, #2932e1, #4468f2)',
+    rules: [
+      { keyword: 'ernie', mode: 'includes' },
+      { keyword: 'eb-', mode: 'includes' },
+    ],
+  },
+  {
+    name: '讯飞星火',
+    icon: 'spark-color',
+    color: 'linear-gradient(135deg, #0070f3, #00d4ff)',
+    rules: [
+      { keyword: 'spark', mode: 'includes' },
+      { keyword: 'generalv', mode: 'includes' },
+    ],
+  },
+  {
+    name: '腾讯混元',
+    icon: 'hunyuan-color',
+    color: 'linear-gradient(135deg, #00b7ff, #0052d9)',
+    rules: [
+      { keyword: 'hunyuan', mode: 'includes' },
+      { keyword: 'tencent-hunyuan', mode: 'includes' },
+    ],
+  },
+  {
+    name: '豆包',
+    icon: 'doubao-color',
+    color: 'linear-gradient(135deg, #3b5bdb, #7048e8)',
+    rules: [
+      { keyword: 'doubao', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'MiniMax',
+    icon: 'minimax-color',
+    color: 'linear-gradient(135deg, #6366f1, #818cf8)',
+    rules: [
+      { keyword: 'minimax', mode: 'includes' },
+      { keyword: 'abab', mode: 'includes' },
+      { keyword: 'mini2.1', mode: 'segment' },
+    ],
+  },
+  {
+    name: 'Cohere',
+    icon: 'cohere-color',
+    color: 'linear-gradient(135deg, #39594d, #5ba77f)',
+    rules: [
+      { keyword: 'command', mode: 'includes' },
+      { keyword: 'c4ai-', mode: 'includes' },
+      { keyword: 'aya', mode: 'includes' },
+      { keyword: 'embed-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'Microsoft',
+    icon: 'microsoft-color',
+    color: 'linear-gradient(135deg, #00bcf2, #0078d4)',
+    rules: [
+      { keyword: 'microsoft/', mode: 'includes' },
+      { keyword: 'phi-', mode: 'includes' },
+      { keyword: 'kosmos', mode: 'includes' },
+      { keyword: 'phi4', mode: 'segment' },
+    ],
+  },
+  {
+    name: 'xAI',
+    icon: 'xai',
+    color: 'linear-gradient(135deg, #111, #444)',
+    rules: [
+      { keyword: 'grok', mode: 'includes' },
+    ],
+  },
+  {
+    name: '阶跃星辰',
+    icon: 'stepfun-color',
+    color: 'linear-gradient(135deg, #0066ff, #3399ff)',
+    rules: [
+      { keyword: 'stepfun', mode: 'includes' },
+      { keyword: 'step-', mode: 'startsWith' },
+      { keyword: 'step3', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: '百川智能',
+    icon: 'baichuan-color',
+    color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
+    rules: [
+      { keyword: 'baichuan', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'AI21 Labs',
+    icon: 'ai21-brand-color',
+    color: 'linear-gradient(135deg, #7c3aed, #a855f7)',
+    rules: [
+      { keyword: 'ai21', mode: 'includes' },
+      { keyword: 'jamba', mode: 'startsWith' },
+      { keyword: 'jamba', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'AI2',
+    icon: 'ai2-color',
+    color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
+    rules: [
+      { keyword: 'allenai', mode: 'includes' },
+      { keyword: 'olmo', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Amazon Nova',
+    icon: 'nova',
+    color: 'linear-gradient(135deg, #f59e0b, #f97316)',
+    rules: [
+      { keyword: 'amazon/nova', mode: 'startsWith' },
+      { keyword: 'amazon.nova', mode: 'includes' },
+      { keyword: 'us.amazon.nova', mode: 'includes' },
+      { keyword: 'nova-', mode: 'startsWith' },
+      { keyword: 'nova-lite', mode: 'startsWith' },
+      { keyword: 'nova-pro', mode: 'startsWith' },
+      { keyword: 'nova-micro', mode: 'startsWith' },
+      { keyword: 'nova-canvas', mode: 'startsWith' },
+      { keyword: 'nova-reel', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'Stability',
+    icon: 'stability-color',
+    color: 'linear-gradient(135deg, #8b5cf6, #a855f7)',
+    rules: [
+      { keyword: 'flux', mode: 'includes' },
+      { keyword: 'stablediffusion', mode: 'includes' },
+      { keyword: 'stable-diffusion', mode: 'includes' },
+      { keyword: 'sdxl', mode: 'includes' },
+      { keyword: 'sd3', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'NVIDIA',
+    icon: 'nvidia-color',
+    color: 'linear-gradient(135deg, #76b900, #4a8c0b)',
+    rules: [
+      { keyword: 'nvidia/', mode: 'includes' },
+      { keyword: 'nvclip', mode: 'includes' },
+      { keyword: 'nemotron', mode: 'includes' },
+      { keyword: 'nemoretriever', mode: 'includes' },
+      { keyword: 'neva', mode: 'includes' },
+      { keyword: 'riva-translate', mode: 'includes' },
+      { keyword: 'cosmos', mode: 'includes' },
+      { keyword: 'nv-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'IBM',
+    icon: 'ibm',
+    color: 'linear-gradient(135deg, #0f62fe, #4589ff)',
+    rules: [
+      { keyword: 'ibm/', mode: 'includes' },
+      { keyword: 'granite', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'BAAI',
+    icon: 'baai',
+    color: 'linear-gradient(135deg, #111827, #374151)',
+    rules: [
+      { keyword: 'baai/', mode: 'includes' },
+      { keyword: 'bge-', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'ByteDance',
+    icon: 'bytedance-color',
+    color: 'linear-gradient(135deg, #325ab4, #0f66ff)',
+    rules: [
+      { keyword: 'bytedance', mode: 'includes' },
+      { keyword: 'seed-oss', mode: 'includes' },
+      { keyword: 'kolors', mode: 'includes' },
+      { keyword: 'kwai', mode: 'includes' },
+      { keyword: 'kwaipilot', mode: 'includes' },
+      { keyword: 'wan-', mode: 'startsWith' },
+      { keyword: 'kat-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'InternLM',
+    icon: 'internlm-color',
+    color: 'linear-gradient(135deg, #1b3882, #4063c5)',
+    rules: [
+      { keyword: 'internlm', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Midjourney',
+    icon: 'midjourney',
+    color: 'linear-gradient(135deg, #4c6ef5, #748ffc)',
+    rules: [
+      { keyword: 'midjourney', mode: 'includes' },
+      { keyword: 'mj_', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'DeepL',
+    icon: 'deepl-color',
+    color: 'linear-gradient(135deg, #0f2b46, #21476f)',
+    rules: [
+      { keyword: 'deepl-', mode: 'startsWith' },
+      { keyword: 'deepl/', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Jina AI',
+    icon: 'jina',
+    color: 'linear-gradient(135deg, #111827, #4b5563)',
+    rules: [
+      { keyword: 'jina', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Relace',
+    icon: 'relace',
+    color: 'linear-gradient(135deg, #7c3aed, #6366f1)',
+    rules: [
+      { keyword: 'relace', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Arcee',
+    icon: 'arcee-color',
+    color: 'linear-gradient(135deg, #2563eb, #60a5fa)',
+    rules: [
+      { keyword: 'arcee-ai', mode: 'includes' },
+      { keyword: 'arcee', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'AionLabs',
+    icon: 'aionlabs-color',
+    color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
+    rules: [
+      { keyword: 'aion-labs', mode: 'includes' },
+      { keyword: 'aionlabs', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'DeepCogito',
+    icon: 'deepcogito-color',
+    color: 'linear-gradient(135deg, #2563eb, #7c3aed)',
+    rules: [
+      { keyword: 'deepcogito', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Essential AI',
+    icon: 'essentialai-color',
+    color: 'linear-gradient(135deg, #0f172a, #334155)',
+    rules: [
+      { keyword: 'essentialai', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Inception',
+    icon: 'inception',
+    color: 'linear-gradient(135deg, #7c3aed, #ec4899)',
+    rules: [
+      { keyword: 'inception', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Inflection',
+    icon: 'inflection',
+    color: 'linear-gradient(135deg, #1d4ed8, #2563eb)',
+    rules: [
+      { keyword: 'inflection', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Liquid AI',
+    icon: 'liquid',
+    color: 'linear-gradient(135deg, #0f172a, #475569)',
+    rules: [
+      { keyword: 'liquid', mode: 'includes' },
+      { keyword: 'lfm-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'LongCat',
+    icon: 'longcat-color',
+    color: 'linear-gradient(135deg, #f97316, #fb7185)',
+    rules: [
+      { keyword: 'longcat', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Morph',
+    icon: 'morph-color',
+    color: 'linear-gradient(135deg, #4f46e5, #8b5cf6)',
+    rules: [
+      { keyword: 'morph/', mode: 'includes' },
+      { keyword: 'morph-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'Nous Research',
+    icon: 'nousresearch',
+    color: 'linear-gradient(135deg, #111827, #4b5563)',
+    rules: [
+      { keyword: 'nousresearch', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Upstage',
+    icon: 'upstage-color',
+    color: 'linear-gradient(135deg, #2563eb, #14b8a6)',
+    rules: [
+      { keyword: 'upstage', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Xiaomi MiMo',
+    icon: 'xiaomimimo',
+    color: 'linear-gradient(135deg, #f97316, #fb923c)',
+    rules: [
+      { keyword: 'xiaomi/mimo', mode: 'includes' },
+      { keyword: 'xiaomimimo', mode: 'includes' },
+      { keyword: 'mimo-v', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'Z.ai',
+    icon: 'zai',
+    color: 'linear-gradient(135deg, #0f172a, #2563eb)',
+    rules: [
+      { keyword: '2zai', mode: 'startsWith' },
+      { keyword: 'z-ai', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'SenseNova',
+    icon: 'sensenova-brand-color',
+    color: 'linear-gradient(135deg, #f59e0b, #f97316)',
+    rules: [
+      { keyword: 'sensenova', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Perplexity',
+    icon: 'perplexity-color',
+    color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
+    rules: [
+      { keyword: 'perplexity', mode: 'includes' },
+      { keyword: 'pplx-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'OpenRouter',
+    icon: 'openrouter',
+    color: 'linear-gradient(135deg, #7c3aed, #2563eb)',
+    rules: [
+      { keyword: 'openrouter', mode: 'includes' },
+      { keyword: 'openrouter-', mode: 'startsWith' },
+    ],
+  },
+  {
+    name: 'Groq',
+    icon: 'groq',
+    color: 'linear-gradient(135deg, #111827, #374151)',
+    rules: [
+      { keyword: 'groq', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Fireworks',
+    icon: 'fireworks-color',
+    color: 'linear-gradient(135deg, #fb7185, #f97316)',
+    rules: [
+      { keyword: 'fireworks-ai', mode: 'includes' },
+      { keyword: 'fireworks', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'DeepInfra',
+    icon: 'deepinfra-color',
+    color: 'linear-gradient(135deg, #4f46e5, #7c3aed)',
+    rules: [
+      { keyword: 'deepinfra', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Together AI',
+    icon: 'together-brand-color',
+    color: 'linear-gradient(135deg, #7c3aed, #ec4899)',
+    rules: [
+      { keyword: 'together.ai', mode: 'includes' },
+      { keyword: 'together', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Replicate',
+    icon: 'replicate-brand',
+    color: 'linear-gradient(135deg, #111827, #6366f1)',
+    rules: [
+      { keyword: 'replicate', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'SambaNova',
+    icon: 'sambanova-color',
+    color: 'linear-gradient(135deg, #2563eb, #06b6d4)',
+    rules: [
+      { keyword: 'sambanova', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Cerebras',
+    icon: 'cerebras-brand-color',
+    color: 'linear-gradient(135deg, #0f766e, #65a30d)',
+    rules: [
+      { keyword: 'cerebras', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Ollama',
+    icon: 'ollama',
+    color: 'linear-gradient(135deg, #1f2937, #4b5563)',
+    rules: [
+      { keyword: 'ollama', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'ModelScope',
+    icon: 'modelscope-color',
+    color: 'linear-gradient(135deg, #2563eb, #60a5fa)',
+    rules: [
+      { keyword: 'modelscope', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'SiliconCloud',
+    icon: 'siliconcloud-color',
+    color: 'linear-gradient(135deg, #0ea5e9, #22d3ee)',
+    rules: [
+      { keyword: 'siliconcloud', mode: 'includes' },
+      { keyword: 'siliconflow', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Azure AI',
+    icon: 'azureai-color',
+    color: 'linear-gradient(135deg, #0284c7, #2563eb)',
+    rules: [
+      { keyword: 'azureai', mode: 'includes' },
+      { keyword: 'azure-openai', mode: 'includes' },
+      { keyword: 'azure/openai', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'AWS Bedrock',
+    icon: 'bedrock-color',
+    color: 'linear-gradient(135deg, #f59e0b, #f97316)',
+    rules: [
+      { keyword: 'bedrock', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Vertex AI',
+    icon: 'vertexai-color',
+    color: 'linear-gradient(135deg, #2563eb, #6366f1)',
+    rules: [
+      { keyword: 'vertexai', mode: 'includes' },
+    ],
+  },
+  {
+    name: 'Google Cloud',
+    icon: 'googlecloud-brand-color',
+    color: 'linear-gradient(135deg, #4285f4, #34a853)',
+    rules: [
+      { keyword: 'googlecloud', mode: 'includes' },
+      { keyword: 'google-cloud', mode: 'includes' },
+    ],
+  },
+  {
+    name: '百度智能云',
+    icon: 'baiducloud-color',
+    color: 'linear-gradient(135deg, #2563eb, #38bdf8)',
+    rules: [
+      { keyword: 'baiducloud', mode: 'includes' },
+      { keyword: 'qianfan', mode: 'includes' },
+    ],
+  },
+  {
+    name: '百炼',
+    icon: 'bailian-color',
+    color: 'linear-gradient(135deg, #7c3aed, #2563eb)',
+    rules: [
+      { keyword: 'bailian', mode: 'includes' },
+      { keyword: 'dashscope', mode: 'includes' },
+    ],
+  },
+  {
+    name: '阿里云',
+    icon: 'alibabacloud-color',
+    color: 'linear-gradient(135deg, #f97316, #fb923c)',
+    rules: [
+      { keyword: 'alibabacloud', mode: 'includes' },
+    ],
+  },
+  {
+    name: '火山引擎',
+    icon: 'volcengine-color',
+    color: 'linear-gradient(135deg, #325ab4, #0f66ff)',
+    rules: [
+      { keyword: 'volcengine', mode: 'includes' },
+    ],
+  },
+  {
+    name: '七牛云',
+    icon: 'qiniu-color',
+    color: 'linear-gradient(135deg, #06b6d4, #0891b2)',
+    rules: [
+      { keyword: 'qiniu', mode: 'includes' },
+    ],
+  },
+];
+
+function normalizeInput(value: string): string {
+  return String(value || '').trim().toLowerCase();
+}
+
+export function stripCommonWrappers(value: string): string {
+  return value
+    .replace(/^(?:\[[^\]]+\]|【[^】]+】)\s*/g, '')
+    .replace(/^re:\s*/g, '')
+    .replace(/^\^+/, '')
+    .replace(/\$+$/, '')
+    .trim();
+}
+
+export function collectBrandCandidates(modelName: string): string[] {
+  const queue: string[] = [];
+  const seen = new Set<string>();
+  const push = (value: string) => {
+    const normalized = normalizeInput(value);
+    if (!normalized || seen.has(normalized)) return;
+    seen.add(normalized);
+    queue.push(normalized);
+  };
+
+  push(modelName);
+
+  for (let index = 0; index < queue.length; index += 1) {
+    const candidate = queue[index]!;
+    const cleaned = stripCommonWrappers(candidate);
+    push(cleaned);
+
+    if (cleaned.includes('/')) {
+      for (const part of cleaned.split('/')) push(part);
+    }
+    if (cleaned.includes(':')) {
+      for (const part of cleaned.split(':')) push(part);
+    }
+    if (cleaned.includes(',')) {
+      for (const part of cleaned.split(',')) push(part);
+    }
+  }
+
+  return queue;
+}
+
+function buildMatchContext(modelName: string): BrandMatchContext {
+  const candidates = collectBrandCandidates(modelName);
+  const raw = candidates[0] || normalizeInput(modelName);
+  const cleaned = stripCommonWrappers(raw);
+  const segments = Array.from(new Set(
+    candidates
+      .flatMap((candidate) => candidate.split(/[/:,\s]+/g))
+      .map((segment) => segment.trim())
+      .filter(Boolean),
+  ));
+
+  return {
+    raw,
+    cleaned,
+    segments,
+    candidates,
+  };
+}
+
+function matchesRule(context: BrandMatchContext, rule: BrandRule): boolean {
+  switch (rule.mode) {
+    case 'includes':
+      return context.raw.includes(rule.keyword)
+        || context.cleaned.includes(rule.keyword)
+        || context.candidates.some((candidate) => candidate.includes(rule.keyword));
+    case 'startsWith':
+      return context.raw.startsWith(rule.keyword)
+        || context.cleaned.startsWith(rule.keyword)
+        || context.segments.some((segment) => segment.startsWith(rule.keyword))
+        || context.candidates.some((candidate) => candidate.startsWith(rule.keyword));
+    case 'segment':
+      return context.segments.includes(rule.keyword);
+    case 'boundary': {
+      const pattern = new RegExp(`(^|[/:_\\-\\s])${escapeRegExp(rule.keyword)}(?=$|[/:_\\-\\s])`);
+      return pattern.test(context.raw)
+        || pattern.test(context.cleaned)
+        || context.candidates.some((candidate) => pattern.test(candidate));
+    }
+    default:
+      return false;
+  }
+}
+
+function escapeRegExp(value: string): string {
+  return value.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
+}
+
+const BRAND_FALLBACK_BOUNDARY_RULES = BRAND_DEFINITIONS.map((brand) => ({
+  brand,
+  boundaryRegex: new RegExp(`(^|[^a-z0-9])${escapeRegExp(brand.name.toLowerCase())}(?=$|[^a-z0-9])`),
+}));
+
+export function getAllBrands(): BrandInfo[] {
+  return BRAND_DEFINITIONS.map(({ name, icon, color }) => ({ name, icon, color }));
+}
+
+export function getAllBrandNames(): string[] {
+  return BRAND_DEFINITIONS.map((brand) => brand.name);
+}
+
+export function getBrand(modelName: string): BrandInfo | null {
+  const context = buildMatchContext(modelName);
+
+  for (const definition of BRAND_DEFINITIONS) {
+    if (definition.rules.some((rule) => matchesRule(context, rule))) {
+      return {
+        name: definition.name,
+        icon: definition.icon,
+        color: definition.color,
+      };
+    }
+  }
+
+  for (const candidate of context.candidates) {
+    for (const rule of BRAND_FALLBACK_BOUNDARY_RULES) {
+      if (rule.boundaryRegex.test(candidate)) {
+        return {
+          name: rule.brand.name,
+          icon: rule.brand.icon,
+          color: rule.brand.color,
+        };
+      }
+    }
+  }
+
+  return null;
+}
diff --git a/src/web/components/BrandIcon.test.ts b/src/web/components/BrandIcon.test.ts
index 1081dd2..66ba08f 100644
--- a/src/web/components/BrandIcon.test.ts
+++ b/src/web/components/BrandIcon.test.ts
@@ -47,6 +47,47 @@ describe('getBrand', () => {
     expect(getBrand('jina-embeddings-v3')).toMatchObject({ name: 'Jina AI', icon: expect.any(String) });
   });
 
+  it('detects new provider and platform brands with lobe-hub icons', () => {
+    expect(getBrand('openrouter/openrouter-auto')).toMatchObject({ name: 'OpenRouter', icon: expect.any(String) });
+    expect(getBrand('groq/compound-beta')).toMatchObject({ name: 'Groq', icon: expect.any(String) });
+    expect(getBrand('deepinfra/deepinfra-chat')).toMatchObject({ name: 'DeepInfra', icon: expect.any(String) });
+    expect(getBrand('fireworks-ai/firefunction-v2')).toMatchObject({ name: 'Fireworks', icon: expect.any(String) });
+    expect(getBrand('together/together-chat')).toMatchObject({ name: 'Together AI', icon: expect.any(String) });
+    expect(getBrand('replicate/recraft-v3')).toMatchObject({ name: 'Replicate', icon: expect.any(String) });
+    expect(getBrand('cerebras/cerebras-chat')).toMatchObject({ name: 'Cerebras', icon: expect.any(String) });
+    expect(getBrand('jamba-1.5-mini')).toMatchObject({ name: 'AI21 Labs', icon: expect.any(String) });
+    expect(getBrand('baichuan-m1-14b-instruct')).toMatchObject({ name: '百川智能', icon: expect.any(String) });
+    expect(getBrand('sensenova/sensenova-v6')).toMatchObject({ name: 'SenseNova', icon: expect.any(String) });
+    expect(getBrand('bedrock/us.amazon.nova-pro-v1:0')).toMatchObject({ name: 'Amazon Nova', icon: expect.any(String) });
+    expect(getBrand('amazon/nova-premier-v1')).toMatchObject({ name: 'Amazon Nova', icon: expect.any(String) });
+    expect(getBrand('dashscope/wanx2.1-t2i-turbo')).toMatchObject({ name: '百炼', icon: expect.any(String) });
+  });
+
+  it('recognizes user-reported uncategorized brands when current lobe-hub icons exist', () => {
+    expect(getBrand('relace/relace-search')).toMatchObject({ name: 'Relace', icon: expect.any(String) });
+    expect(getBrand('xiaomi/mimo-v2-pro')).toMatchObject({ name: 'Xiaomi MiMo', icon: expect.any(String) });
+    expect(getBrand('arcee-ai/trinity-mini')).toMatchObject({ name: 'Arcee', icon: expect.any(String) });
+    expect(getBrand('aion-labs/aion-2.0')).toMatchObject({ name: 'AionLabs', icon: expect.any(String) });
+    expect(getBrand('allenai/olmo-3-32b-think')).toMatchObject({ name: 'AI2', icon: expect.any(String) });
+    expect(getBrand('deepcogito/cogito-v2.1-671b')).toMatchObject({ name: 'DeepCogito', icon: expect.any(String) });
+    expect(getBrand('essentialai/rnj-1-instruct')).toMatchObject({ name: 'Essential AI', icon: expect.any(String) });
+    expect(getBrand('inflection/inflection-3-pi')).toMatchObject({ name: 'Inflection', icon: expect.any(String) });
+    expect(getBrand('liquid/lfm-2-24b-a2b')).toMatchObject({ name: 'Liquid AI', icon: expect.any(String) });
+    expect(getBrand('LongCat-Flash-Lite')).toMatchObject({ name: 'LongCat', icon: expect.any(String) });
+    expect(getBrand('morph/morph-v3-fast')).toMatchObject({ name: 'Morph', icon: expect.any(String) });
+    expect(getBrand('nousresearch/hermes-4-70b')).toMatchObject({ name: 'Nous Research', icon: expect.any(String) });
+    expect(getBrand('inception/mercury')).toMatchObject({ name: 'Inception', icon: expect.any(String) });
+    expect(getBrand('upstage/solar-pro-3')).toMatchObject({ name: 'Upstage', icon: expect.any(String) });
+    expect(getBrand('2zai')).toMatchObject({ name: 'Z.ai', icon: expect.any(String) });
+  });
+
+  it('prefers intrinsic model vendors over upstream hosting platforms', () => {
+    expect(getBrand('openrouter/anthropic/claude-3-7-sonnet')?.name).toBe('Anthropic');
+    expect(getBrand('deepinfra/meta-llama/llama-3.3-70b-instruct')?.name).toBe('Meta');
+    expect(getBrand('vertexai/google/gemini-2.5-pro')?.name).toBe('Google');
+    expect(getBrand('azureai/gpt-4o')?.name).toBe('OpenAI');
+  });
+
   it('returns null for unknown model names', () => {
     expect(getBrand('totally-unknown-model')).toBeNull();
   });
diff --git a/src/web/components/brandRegistry.ts b/src/web/components/brandRegistry.ts
index 5be2e35..762b29c 100644
--- a/src/web/components/brandRegistry.ts
+++ b/src/web/components/brandRegistry.ts
@@ -1,22 +1,12 @@
-export interface BrandMatchContext {
-  raw: string;
-  cleaned: string;
-  segments: string[];
-}
-
-interface InternalBrandMatchContext extends BrandMatchContext {
-  candidates: string[];
-}
-
-export interface BrandInfo {
-  name: string;
-  icon: string;
-  color: string;
-}
-
-type BrandDefinition = BrandInfo & {
-  match: (context: InternalBrandMatchContext) => boolean;
-};
+export {
+  collectBrandCandidates,
+  getAllBrandNames,
+  getAllBrands,
+  getBrand,
+  stripCommonWrappers,
+  type BrandInfo,
+  type BrandMatchContext,
+} from '../../server/shared/modelBrand.js';
 
 const LEGACY_ICON_ALIASES: Record<string, string> = {
   anthropic: 'claude-color',
@@ -45,285 +35,6 @@ function normalizeInput(value: string): string {
   return String(value || '').trim().toLowerCase();
 }
 
-function stripCommonWrappers(value: string): string {
-  return value
-    .replace(/^(?:\[[^\]]+\]|【[^】]+】)\s*/g, '')
-    .replace(/^re:\s*/g, '')
-    .replace(/^\^+/, '')
-    .replace(/\$+$/, '')
-    .trim();
-}
-
-function collectBrandCandidates(modelName: string): string[] {
-  const queue: string[] = [];
-  const seen = new Set<string>();
-  const push = (value: string) => {
-    const normalized = normalizeInput(value);
-    if (!normalized || seen.has(normalized)) return;
-    seen.add(normalized);
-    queue.push(normalized);
-  };
-
-  push(modelName);
-
-  for (let index = 0; index < queue.length; index += 1) {
-    const candidate = queue[index]!;
-    const cleaned = stripCommonWrappers(candidate);
-    push(cleaned);
-
-    if (cleaned.includes('/')) {
-      for (const part of cleaned.split('/')) push(part);
-    }
-    if (cleaned.includes(':')) {
-      for (const part of cleaned.split(':')) push(part);
-    }
-    if (cleaned.includes(',')) {
-      for (const part of cleaned.split(',')) push(part);
-    }
-  }
-
-  return queue;
-}
-
-function buildMatchContext(modelName: string): InternalBrandMatchContext {
-  const candidates = collectBrandCandidates(modelName);
-  const raw = candidates[0] || normalizeInput(modelName);
-  const cleaned = stripCommonWrappers(raw);
-  const segments = Array.from(new Set(
-    candidates
-      .flatMap((candidate) => candidate.split(/[/:,\s]+/g))
-      .map((segment) => segment.trim())
-      .filter(Boolean),
-  ));
-
-  return {
-    raw,
-    cleaned,
-    segments,
-    candidates,
-  };
-}
-
-function includesAny(context: InternalBrandMatchContext, needles: string[]): boolean {
-  return needles.some((needle) => (
-    context.raw.includes(needle)
-    || context.cleaned.includes(needle)
-    || context.candidates.some((candidate) => candidate.includes(needle))
-  ));
-}
-
-function startsWithAny(context: InternalBrandMatchContext, needles: string[]): boolean {
-  return needles.some((needle) => (
-    context.raw.startsWith(needle)
-    || context.cleaned.startsWith(needle)
-    || context.segments.some((segment) => segment.startsWith(needle))
-    || context.candidates.some((candidate) => candidate.startsWith(needle))
-  ));
-}
-
-function hasExactSegment(context: InternalBrandMatchContext, needles: string[]): boolean {
-  return needles.some((needle) => context.segments.includes(needle));
-}
-
-function matchesBoundary(context: InternalBrandMatchContext, pattern: RegExp): boolean {
-  return pattern.test(context.raw) || pattern.test(context.cleaned) || context.candidates.some((candidate) => pattern.test(candidate));
-}
-
-const BRAND_DEFINITIONS: BrandDefinition[] = [
-  {
-    name: 'OpenAI',
-    icon: 'openai',
-    color: 'linear-gradient(135deg, #10a37f, #1a7f5a)',
-    match: (context) => (
-      startsWithAny(context, ['gpt', 'chatgpt', 'dall-e', 'whisper', 'text-embedding', 'text-moderation', 'davinci', 'babbage', 'codex-mini'])
-      || startsWithAny(context, ['o1', 'o3', 'o4', 'tts'])
-    ),
-  },
-  {
-    name: 'Anthropic',
-    icon: 'claude-color',
-    color: 'linear-gradient(135deg, #d4a574, #c4956a)',
-    match: (context) => includesAny(context, ['claude']),
-  },
-  {
-    name: 'Google',
-    icon: 'gemini-color',
-    color: 'linear-gradient(135deg, #4285f4, #34a853)',
-    match: (context) => (
-      includesAny(context, ['gemini', 'gemma', 'google/', 'palm', 'paligemma', 'shieldgemma', 'recurrentgemma', 'deplot', 'codegemma', 'imagen', 'learnlm', 'aqa'])
-      || startsWithAny(context, ['veo', 'google/'])
-    ),
-  },
-  {
-    name: 'DeepSeek',
-    icon: 'deepseek-color',
-    color: 'linear-gradient(135deg, #4d6bfe, #44a3ec)',
-    match: (context) => includesAny(context, ['deepseek']) || hasExactSegment(context, ['ds-chat']),
-  },
-  {
-    name: '通义千问',
-    icon: 'qwen-color',
-    color: 'linear-gradient(135deg, #615cf7, #9b8afb)',
-    match: (context) => includesAny(context, ['qwen', 'qwq', 'tongyi']),
-  },
-  {
-    name: '智谱 AI',
-    icon: 'zhipu-color',
-    color: 'linear-gradient(135deg, #3b6cf5, #6366f1)',
-    match: (context) => includesAny(context, ['glm', 'chatglm', 'codegeex', 'cogview', 'cogvideo']),
-  },
-  {
-    name: 'Meta',
-    icon: 'meta-color',
-    color: 'linear-gradient(135deg, #0668E1, #1877f2)',
-    match: (context) => includesAny(context, ['llama', 'code-llama', 'codellama']),
-  },
-  {
-    name: 'Mistral',
-    icon: 'mistral-color',
-    color: 'linear-gradient(135deg, #f7d046, #f2a900)',
-    match: (context) => includesAny(context, ['mistral', 'mixtral', 'codestral', 'pixtral', 'ministral', 'voxtral', 'magistral']),
-  },
-  {
-    name: 'Moonshot',
-    icon: 'moonshot',
-    color: 'linear-gradient(135deg, #000000, #333333)',
-    match: (context) => includesAny(context, ['moonshot', 'kimi']),
-  },
-  {
-    name: '零一万物',
-    icon: 'yi-color',
-    color: 'linear-gradient(135deg, #1d4ed8, #3b82f6)',
-    match: (context) => (
-      startsWithAny(context, ['yi-'])
-      || matchesBoundary(context, /(^|[/:_\-\s])yi(?=$|[/:_\-\s])/)
-    ),
-  },
-  {
-    name: '文心一言',
-    icon: 'wenxin-color',
-    color: 'linear-gradient(135deg, #2932e1, #4468f2)',
-    match: (context) => includesAny(context, ['ernie', 'eb-']),
-  },
-  {
-    name: '讯飞星火',
-    icon: 'spark-color',
-    color: 'linear-gradient(135deg, #0070f3, #00d4ff)',
-    match: (context) => includesAny(context, ['spark', 'generalv']),
-  },
-  {
-    name: '腾讯混元',
-    icon: 'hunyuan-color',
-    color: 'linear-gradient(135deg, #00b7ff, #0052d9)',
-    match: (context) => includesAny(context, ['hunyuan', 'tencent-hunyuan']),
-  },
-  {
-    name: '豆包',
-    icon: 'doubao-color',
-    color: 'linear-gradient(135deg, #3b5bdb, #7048e8)',
-    match: (context) => includesAny(context, ['doubao']),
-  },
-  {
-    name: 'MiniMax',
-    icon: 'minimax-color',
-    color: 'linear-gradient(135deg, #6366f1, #818cf8)',
-    match: (context) => includesAny(context, ['minimax', 'abab']) || hasExactSegment(context, ['mini2.1']),
-  },
-  {
-    name: 'Cohere',
-    icon: 'cohere-color',
-    color: 'linear-gradient(135deg, #39594d, #5ba77f)',
-    match: (context) => includesAny(context, ['command', 'c4ai-']) || startsWithAny(context, ['embed-']),
-  },
-  {
-    name: 'Microsoft',
-    icon: 'microsoft-color',
-    color: 'linear-gradient(135deg, #00bcf2, #0078d4)',
-    match: (context) => (
-      includesAny(context, ['microsoft/', 'phi-', 'kosmos'])
-      || hasExactSegment(context, ['phi4'])
-    ),
-  },
-  {
-    name: 'xAI',
-    icon: 'xai',
-    color: 'linear-gradient(135deg, #111, #444)',
-    match: (context) => includesAny(context, ['grok']),
-  },
-  {
-    name: '阶跃星辰',
-    icon: 'stepfun-color',
-    color: 'linear-gradient(135deg, #0066ff, #3399ff)',
-    match: (context) => includesAny(context, ['stepfun']) || startsWithAny(context, ['step-', 'step3']),
-  },
-  {
-    name: 'Stability',
-    icon: 'stability-color',
-    color: 'linear-gradient(135deg, #8b5cf6, #a855f7)',
-    match: (context) => includesAny(context, ['flux', 'stablediffusion', 'stable-diffusion', 'sdxl']) || startsWithAny(context, ['sd3']),
-  },
-  {
-    name: 'NVIDIA',
-    icon: 'nvidia-color',
-    color: 'linear-gradient(135deg, #76b900, #4a8c0b)',
-    match: (context) => (
-      includesAny(context, ['nvidia/', 'nvclip', 'nemotron', 'nemoretriever', 'neva', 'riva-translate', 'cosmos'])
-      || startsWithAny(context, ['nv-'])
-    ),
-  },
-  {
-    name: 'IBM',
-    icon: 'ibm',
-    color: 'linear-gradient(135deg, #0f62fe, #4589ff)',
-    match: (context) => includesAny(context, ['ibm/', 'granite']),
-  },
-  {
-    name: 'BAAI',
-    icon: 'baai',
-    color: 'linear-gradient(135deg, #111827, #374151)',
-    match: (context) => includesAny(context, ['baai/', 'bge-']),
-  },
-  {
-    name: 'ByteDance',
-    icon: 'bytedance-color',
-    color: 'linear-gradient(135deg, #325ab4, #0f66ff)',
-    match: (context) => includesAny(context, ['bytedance', 'seed-oss', 'kolors', 'kwai', 'kwaipilot']) || startsWithAny(context, ['wan-', 'kat-']),
-  },
-  {
-    name: 'InternLM',
-    icon: 'internlm-color',
-    color: 'linear-gradient(135deg, #1b3882, #4063c5)',
-    match: (context) => includesAny(context, ['internlm']),
-  },
-  {
-    name: 'Midjourney',
-    icon: 'midjourney',
-    color: 'linear-gradient(135deg, #4c6ef5, #748ffc)',
-    match: (context) => includesAny(context, ['midjourney']) || startsWithAny(context, ['mj_']),
-  },
-  {
-    name: 'DeepL',
-    icon: 'deepl-color',
-    color: 'linear-gradient(135deg, #0f2b46, #21476f)',
-    match: (context) => startsWithAny(context, ['deepl-']) || includesAny(context, ['deepl/']),
-  },
-  {
-    name: 'Jina AI',
-    icon: 'jina',
-    color: 'linear-gradient(135deg, #111827, #4b5563)',
-    match: (context) => includesAny(context, ['jina']),
-  },
-];
-
-function escapeRegExp(value: string): string {
-  return value.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
-}
-
-const BRAND_FALLBACK_BOUNDARY_RULES = BRAND_DEFINITIONS.map((brand) => ({
-  brand,
-  boundaryRegex: new RegExp(`(^|[^a-z0-9])${escapeRegExp(brand.name.toLowerCase())}(?=$|[^a-z0-9])`),
-}));
-
 const FALLBACK_COLORS = [
   'linear-gradient(135deg, #4f46e5, #818cf8)',
   'linear-gradient(135deg, #059669, #34d399)',
@@ -347,38 +58,10 @@ export function getBrandIconUrl(icon: string | null | undefined, cdn: string): s
   return `${cdn}/${normalized}.png`;
 }
 
-export function getBrand(modelName: string): BrandInfo | null {
-  const context = buildMatchContext(modelName);
-
-  for (const definition of BRAND_DEFINITIONS) {
-    if (definition.match(context)) {
-      return {
-        name: definition.name,
-        icon: definition.icon,
-        color: definition.color,
-      };
-    }
-  }
-
-  for (const candidate of context.candidates) {
-    for (const rule of BRAND_FALLBACK_BOUNDARY_RULES) {
-      if (rule.boundaryRegex.test(candidate)) {
-        return {
-          name: rule.brand.name,
-          icon: rule.brand.icon,
-          color: rule.brand.color,
-        };
-      }
-    }
-  }
-
-  return null;
-}
-
 export function hashColor(name: string): string {
   let h = 0;
   for (let i = 0; i < name.length; i += 1) h = (h * 31 + name.charCodeAt(i)) | 0;
-  return FALLBACK_COLORS[Math.abs(h) % FALLBACK_COLORS.length];
+  return FALLBACK_COLORS[Math.abs(h) % FALLBACK_COLORS.length]!;
 }
 
 export function avatarLetters(name: string): string {
diff --git a/src/web/pages/Models.marketplace-text.test.tsx b/src/web/pages/Models.marketplace-text.test.tsx
index e3d46f0..89b7437 100644
--- a/src/web/pages/Models.marketplace-text.test.tsx
+++ b/src/web/pages/Models.marketplace-text.test.tsx
@@ -195,6 +195,214 @@ describe('Models marketplace text', () => {
     }
   });
 
+  it('shows newly added provider fallback brands without losing vendor brands in the filter panel', async () => {
+    apiMock.getModelsMarketplace.mockResolvedValue({
+      models: [
+        {
+          name: 'openrouter/openrouter-auto',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 180,
+          successRate: 99,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 1,
+              site: '平台站 A',
+              username: 'tester',
+              latency: 180,
+              balance: 9.9,
+              tokens: [{ id: 1, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+        {
+          name: 'deepinfra/meta-llama/llama-3.3-70b-instruct',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 240,
+          successRate: 98,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 2,
+              site: '平台站 B',
+              username: 'tester',
+              latency: 240,
+              balance: 7.2,
+              tokens: [{ id: 2, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+        {
+          name: 'groq/compound-beta',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 95,
+          successRate: 99,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 3,
+              site: '平台站 C',
+              username: 'tester',
+              latency: 95,
+              balance: 5.1,
+              tokens: [{ id: 3, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+      ],
+    });
+
+    let root!: WebTestRenderer;
+
+    try {
+      await act(async () => {
+        root = create(
+          <MemoryRouter initialEntries={['/models']}>
+            <ToastProvider>
+              <Models />
+            </ToastProvider>
+          </MemoryRouter>,
+        );
+      });
+      await flushMicrotasks();
+
+      const text = collectText(root!.root);
+      expect(text).toContain('OpenRouter');
+      expect(text).toContain('Meta');
+      expect(text).toContain('Groq');
+      expect(text).not.toContain('其他未归类的模型');
+    } finally {
+      root?.unmount();
+    }
+  });
+
+  it('shows user-reported recognizable brands in the marketplace filter panel', async () => {
+    apiMock.getModelsMarketplace.mockResolvedValue({
+      models: [
+        {
+          name: 'xiaomi/mimo-v2-pro',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 180,
+          successRate: 99,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 1,
+              site: '平台站 A',
+              username: 'tester',
+              latency: 180,
+              balance: 9.9,
+              tokens: [{ id: 1, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+        {
+          name: 'arcee-ai/trinity-mini',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 240,
+          successRate: 98,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 2,
+              site: '平台站 B',
+              username: 'tester',
+              latency: 240,
+              balance: 7.2,
+              tokens: [{ id: 2, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+        {
+          name: 'amazon/nova-premier-v1',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 95,
+          successRate: 99,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 3,
+              site: '平台站 C',
+              username: 'tester',
+              latency: 95,
+              balance: 5.1,
+              tokens: [{ id: 3, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+        {
+          name: 'LongCat-Flash-Lite',
+          accountCount: 1,
+          tokenCount: 1,
+          avgLatency: 95,
+          successRate: 99,
+          description: null,
+          tags: [],
+          supportedEndpointTypes: [],
+          pricingSources: [],
+          accounts: [
+            {
+              id: 4,
+              site: '平台站 D',
+              username: 'tester',
+              latency: 95,
+              balance: 5.1,
+              tokens: [{ id: 4, name: 'default', isDefault: true }],
+            },
+          ],
+        },
+      ],
+    });
+
+    let root!: WebTestRenderer;
+
+    try {
+      await act(async () => {
+        root = create(
+          <MemoryRouter initialEntries={['/models']}>
+            <ToastProvider>
+              <Models />
+            </ToastProvider>
+          </MemoryRouter>,
+        );
+      });
+      await flushMicrotasks();
+
+      const text = collectText(root!.root);
+      expect(text).toContain('Xiaomi MiMo');
+      expect(text).toContain('Arcee');
+      expect(text).toContain('Amazon Nova');
+      expect(text).toContain('LongCat');
+      expect(text).not.toContain('其他未归类的模型');
+    } finally {
+      root?.unmount();
+    }
+  });
+
   it('keeps a visible mobile filter entry on small screens', async () => {
     const nextWindow = (originalWindow ? { ...originalWindow } : {}) as Window & typeof globalThis;
     nextWindow.innerWidth = 768;