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1
+ <!DOCTYPE html>
2
+ <html lang="zh-CN">
3
+ <head>
4
+ <meta charset="UTF-8">
5
+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
6
+ <title>Hugging Face 新模型调研 2026</title>
7
+ <style>
8
+ * {
9
+ margin: 0;
10
+ padding: 0;
11
+ box-sizing: border-box;
12
+ }
13
+
14
+ body {
15
+ font-family: 'Segoe UI', 'Microsoft YaHei', sans-serif;
16
+ background: linear-gradient(135deg, #0a0a1a 0%, #1a1a3e 25%, #2d1b4e 50%, #1a2a4a 75%, #0f1525 100%);
17
+ min-height: 100vh;
18
+ color: #fff;
19
+ overflow-x: hidden;
20
+ }
21
+
22
+ /* 背景粒子动画 */
23
+ .particles {
24
+ position: fixed;
25
+ top: 0;
26
+ left: 0;
27
+ width: 100%;
28
+ height: 100%;
29
+ pointer-events: none;
30
+ z-index: 0;
31
+ overflow: hidden;
32
+ }
33
+
34
+ .particle {
35
+ position: absolute;
36
+ width: 4px;
37
+ height: 4px;
38
+ background: rgba(255, 255, 255, 0.3);
39
+ border-radius: 50%;
40
+ animation: float 20s infinite linear;
41
+ }
42
+
43
+ @keyframes float {
44
+ 0% { transform: translateY(100vh) rotate(0deg); opacity: 0; }
45
+ 10% { opacity: 1; }
46
+ 90% { opacity: 1; }
47
+ 100% { transform: translateY(-100vh) rotate(720deg); opacity: 0; }
48
+ }
49
+
50
+ /* 主容器 */
51
+ .container {
52
+ position: relative;
53
+ z-index: 1;
54
+ max-width: 1400px;
55
+ margin: 0 auto;
56
+ padding: 20px;
57
+ min-height: 100vh;
58
+ }
59
+
60
+ /* 头部 */
61
+ header {
62
+ text-align: center;
63
+ padding: 40px 20px;
64
+ position: relative;
65
+ }
66
+
67
+ header h1 {
68
+ font-size: 3.5rem;
69
+ color: #fff;
70
+ margin-bottom: 15px;
71
+ text-shadow:
72
+ 0 0 20px rgba(168, 212, 255, 0.8),
73
+ 0 0 40px rgba(168, 212, 255, 0.5),
74
+ 0 0 60px rgba(201, 184, 255, 0.3);
75
+ letter-spacing: 2px;
76
+ }
77
+
78
+ header .subtitle {
79
+ font-size: 1.2rem;
80
+ color: #8899bb;
81
+ letter-spacing: 3px;
82
+ }
83
+
84
+ /* 轮播容器 */
85
+ .carousel-container {
86
+ position: relative;
87
+ width: 100%;
88
+ max-width: 1200px;
89
+ margin: 30px auto;
90
+ overflow: hidden;
91
+ border-radius: 20px;
92
+ background: rgba(255, 255, 255, 0.03);
93
+ backdrop-filter: blur(10px);
94
+ }
95
+
96
+ .carousel-track {
97
+ display: flex;
98
+ transition: transform 0.8s cubic-bezier(0.4, 0, 0.2, 1);
99
+ }
100
+
101
+ /* 模型卡片 */
102
+ .model-card {
103
+ min-width: 100%;
104
+ padding: 50px;
105
+ display: flex;
106
+ gap: 40px;
107
+ align-items: flex-start;
108
+ transition: all 0.3s ease;
109
+ }
110
+
111
+ .model-card:hover {
112
+ transform: scale(1.02);
113
+ }
114
+
115
+ /* 卡片左侧 - 基本信息 */
116
+ .card-left {
117
+ flex: 0 0 350px;
118
+ background: linear-gradient(145deg, rgba(255,255,255,0.95), rgba(240,245,255,0.9));
119
+ border-radius: 20px;
120
+ padding: 35px;
121
+ color: #1a1a3e;
122
+ box-shadow:
123
+ 0 25px 50px rgba(0, 0, 0, 0.4),
124
+ 0 0 100px rgba(168, 212, 255, 0.2);
125
+ transition: all 0.4s ease;
126
+ }
127
+
128
+ .card-left:hover {
129
+ box-shadow:
130
+ 0 30px 60px rgba(0, 0, 0, 0.5),
131
+ 0 0 150px rgba(168, 212, 255, 0.4),
132
+ inset 0 0 30px rgba(255, 255, 255, 0.1);
133
+ transform: translateY(-5px) scale(1.03);
134
+ }
135
+
136
+ .model-name {
137
+ font-size: 2rem;
138
+ font-weight: bold;
139
+ margin-bottom: 8px;
140
+ color: #1a1a3e;
141
+ }
142
+
143
+ .developer {
144
+ font-size: 0.95rem;
145
+ color: #666;
146
+ margin-bottom: 20px;
147
+ display: flex;
148
+ align-items: center;
149
+ gap: 8px;
150
+ }
151
+
152
+ .developer::before {
153
+ content: '🏢';
154
+ font-size: 1.1rem;
155
+ }
156
+
157
+ .param-badge {
158
+ display: inline-block;
159
+ background: linear-gradient(135deg, #6366f1, #8b5cf6);
160
+ color: white;
161
+ padding: 10px 20px;
162
+ border-radius: 30px;
163
+ font-size: 1.3rem;
164
+ font-weight: bold;
165
+ margin-bottom: 15px;
166
+ box-shadow: 0 4px 15px rgba(99, 102, 241, 0.4);
167
+ }
168
+
169
+ .param-badge.highlight {
170
+ background: linear-gradient(135deg, #f59e0b, #ef4444);
171
+ animation: pulse 2s infinite;
172
+ }
173
+
174
+ @keyframes pulse {
175
+ 0%, 100% { box-shadow: 0 4px 15px rgba(245, 158, 11, 0.4); }
176
+ 50% { box-shadow: 0 4px 30px rgba(245, 158, 11, 0.7); }
177
+ }
178
+
179
+ .type-tag {
180
+ display: inline-block;
181
+ background: #e8f0fe;
182
+ color: #1a73e8;
183
+ padding: 6px 14px;
184
+ border-radius: 20px;
185
+ font-size: 0.85rem;
186
+ margin-right: 8px;
187
+ margin-bottom: 25px;
188
+ }
189
+
190
+ .license-tag {
191
+ display: inline-block;
192
+ background: #fef3e8;
193
+ color: #d97706;
194
+ padding: 6px 14px;
195
+ border-radius: 20px;
196
+ font-size: 0.85rem;
197
+ margin-bottom: 25px;
198
+ }
199
+
200
+ .stats-row {
201
+ display: flex;
202
+ gap: 15px;
203
+ margin-top: 20px;
204
+ }
205
+
206
+ .stat-item {
207
+ text-align: center;
208
+ padding: 12px 18px;
209
+ background: rgba(99, 102, 241, 0.08);
210
+ border-radius: 12px;
211
+ flex: 1;
212
+ }
213
+
214
+ .stat-value {
215
+ font-size: 1.4rem;
216
+ font-weight: bold;
217
+ color: #6366f1;
218
+ }
219
+
220
+ .stat-label {
221
+ font-size: 0.75rem;
222
+ color: #888;
223
+ margin-top: 3px;
224
+ }
225
+
226
+ /* 卡片右侧 - 详细信息 */
227
+ .card-right {
228
+ flex: 1;
229
+ background: rgba(255, 255, 255, 0.08);
230
+ border-radius: 20px;
231
+ padding: 30px;
232
+ backdrop-filter: blur(10px);
233
+ border: 1px solid rgba(255, 255, 255, 0.1);
234
+ }
235
+
236
+ .section-title {
237
+ font-size: 1.3rem;
238
+ color: #a8d4ff;
239
+ margin-bottom: 15px;
240
+ display: flex;
241
+ align-items: center;
242
+ gap: 10px;
243
+ }
244
+
245
+ .section-title::before {
246
+ content: '';
247
+ width: 4px;
248
+ height: 20px;
249
+ background: linear-gradient(180deg, #6366f1, #a8d4ff);
250
+ border-radius: 2px;
251
+ }
252
+
253
+ .feature-list {
254
+ list-style: none;
255
+ margin-bottom: 25px;
256
+ }
257
+
258
+ .feature-list li {
259
+ padding: 10px 0;
260
+ border-bottom: 1px solid rgba(255, 255, 255, 0.08);
261
+ display: flex;
262
+ align-items: flex-start;
263
+ gap: 12px;
264
+ line-height: 1.5;
265
+ }
266
+
267
+ .feature-list li::before {
268
+ content: '✦';
269
+ color: #a8d4ff;
270
+ font-size: 0.9rem;
271
+ margin-top: 2px;
272
+ }
273
+
274
+ .feature-list strong {
275
+ color: #c9b8ff;
276
+ }
277
+
278
+ /* Benchmark表格 */
279
+ .benchmark-table {
280
+ width: 100%;
281
+ border-collapse: collapse;
282
+ margin-top: 10px;
283
+ font-size: 0.85rem;
284
+ }
285
+
286
+ .benchmark-table th {
287
+ background: rgba(99, 102, 241, 0.3);
288
+ color: #fff;
289
+ padding: 12px 15px;
290
+ text-align: left;
291
+ font-weight: 600;
292
+ border-radius: 8px 8px 0 0;
293
+ }
294
+
295
+ .benchmark-table td {
296
+ padding: 10px 15px;
297
+ border-bottom: 1px solid rgba(255, 255, 255, 0.08);
298
+ }
299
+
300
+ .benchmark-table tr:hover td {
301
+ background: rgba(255, 255, 255, 0.05);
302
+ }
303
+
304
+ .benchmark-table .score-high {
305
+ color: #4ade80;
306
+ font-weight: bold;
307
+ }
308
+
309
+ .benchmark-table .score-mid {
310
+ color: #fbbf24;
311
+ }
312
+
313
+ /* 导航控制 */
314
+ .carousel-nav {
315
+ display: flex;
316
+ justify-content: center;
317
+ align-items: center;
318
+ gap: 20px;
319
+ margin-top: 30px;
320
+ padding-bottom: 30px;
321
+ }
322
+
323
+ .nav-btn {
324
+ width: 50px;
325
+ height: 50px;
326
+ border-radius: 50%;
327
+ background: rgba(255, 255, 255, 0.1);
328
+ border: 2px solid rgba(255, 255, 255, 0.3);
329
+ color: white;
330
+ font-size: 1.5rem;
331
+ cursor: pointer;
332
+ transition: all 0.3s ease;
333
+ display: flex;
334
+ align-items: center;
335
+ justify-content: center;
336
+ }
337
+
338
+ .nav-btn:hover {
339
+ background: rgba(255, 255, 255, 0.2);
340
+ transform: scale(1.1);
341
+ }
342
+
343
+ .nav-dots {
344
+ display: flex;
345
+ gap: 8px;
346
+ }
347
+
348
+ .dot {
349
+ width: 12px;
350
+ height: 12px;
351
+ border-radius: 50%;
352
+ background: rgba(255, 255, 255, 0.3);
353
+ cursor: pointer;
354
+ transition: all 0.3s ease;
355
+ }
356
+
357
+ .dot.active {
358
+ background: #a8d4ff;
359
+ box-shadow: 0 0 15px rgba(168, 212, 255, 0.5);
360
+ transform: scale(1.2);
361
+ }
362
+
363
+ .dot:hover {
364
+ background: rgba(255, 255, 255, 0.5);
365
+ }
366
+
367
+ /* 进度条 */
368
+ .progress-bar {
369
+ width: 100%;
370
+ max-width: 1200px;
371
+ height: 3px;
372
+ background: rgba(255, 255, 255, 0.1);
373
+ margin: 0 auto 20px;
374
+ border-radius: 2px;
375
+ overflow: hidden;
376
+ }
377
+
378
+ .progress-fill {
379
+ height: 100%;
380
+ background: linear-gradient(90deg, #6366f1, #a8d4ff);
381
+ width: 0%;
382
+ transition: width 0.3s ease;
383
+ }
384
+
385
+ /* 页脚 */
386
+ footer {
387
+ text-align: center;
388
+ padding: 40px 20px;
389
+ color: #667788;
390
+ font-size: 0.9rem;
391
+ border-top: 1px solid rgba(255, 255, 255, 0.1);
392
+ margin-top: 30px;
393
+ }
394
+
395
+ footer a {
396
+ color: #a8d4ff;
397
+ text-decoration: none;
398
+ }
399
+
400
+ /* 响应式 */
401
+ @media (max-width: 900px) {
402
+ .model-card {
403
+ flex-direction: column;
404
+ padding: 30px;
405
+ }
406
+
407
+ .card-left {
408
+ flex: none;
409
+ width: 100%;
410
+ }
411
+
412
+ header h1 {
413
+ font-size: 2rem;
414
+ }
415
+ }
416
+
417
+ /* 自动播放动画 */
418
+ @keyframes slideProgress {
419
+ from { width: 0%; }
420
+ to { width: 100%; }
421
+ }
422
+
423
+ .auto-playing .progress-fill {
424
+ animation: slideProgress 8s linear forwards;
425
+ }
426
+ </style>
427
+ </head>
428
+ <body>
429
+ <!-- 背景粒子 -->
430
+ <div class="particles" id="particles"></div>
431
+
432
+ <div class="container">
433
+ <!-- 头部 -->
434
+ <header>
435
+ <h1>🤗 Hugging Face 新模型调研</h1>
436
+ <p class="subtitle">2026年2月 · Trending Models 深度分析</p>
437
+ </header>
438
+
439
+ <!-- 进度条 -->
440
+ <div class="progress-bar">
441
+ <div class="progress-fill" id="progressFill"></div>
442
+ </div>
443
+
444
+ <!-- 轮播容器 -->
445
+ <div class="carousel-container auto-playing">
446
+ <div class="carousel-track" id="carouselTrack">
447
+
448
+ <!-- 模型1: Ring-2.5-1T -->
449
+ <div class="model-card">
450
+ <div class="card-left">
451
+ <div class="model-name">Ring-2.5-1T</div>
452
+ <div class="developer">inclusionAI (蚂蚁集团)</div>
453
+ <div class="param-badge highlight">1T 参数 / 63B 激活</div>
454
+ <br>
455
+ <span class="type-tag">Text Generation</span>
456
+ <span class="license-tag">MIT License</span>
457
+ <div class="stats-row">
458
+ <div class="stat-item">
459
+ <div class="stat-value">256K</div>
460
+ <div class="stat-label">上下文长度</div>
461
+ </div>
462
+ <div class="stat-item">
463
+ <div class="stat-value">3.6k</div>
464
+ <div class="stat-label">月下载量</div>
465
+ </div>
466
+ </div>
467
+ </div>
468
+ <div class="card-right">
469
+ <h3 class="section-title">核心特性</h3>
470
+ <ul class="feature-list">
471
+ <li><strong>首个开源万亿参数思考模型</strong> - 基于混合线性注意力架构</li>
472
+ <li><strong>Ling 2.5 架构</strong> - MLA + Lightning Linear Attention (1:7比例)</li>
473
+ <li><strong>内存优化</strong> - 内存访问开销降低10x+，生成吞吐量提升3x+</li>
474
+ <li><strong>Deep Thinking</strong> - IMO 2025 得分35分（金牌水平），CMO 2025 得分105分</li>
475
+ <li><strong>Long-horizon任务执行</strong> - 大规模全异步代理RL训练</li>
476
+ </ul>
477
+ <h3 class="section-title">Benchmark 数据</h3>
478
+ <table class="benchmark-table">
479
+ <tr><th>测试项目</th><th>Ring-2.5-1T</th><th>GPT-5.2</th><th>Claude 4.5 Opus</th></tr>
480
+ <tr><td>HLE-Full (w/ tools)</td><td class="score-high">50.2</td><td>45.5</td><td>43.2</td></tr>
481
+ <tr><td>AIME 2025</td><td>96.1</td><td class="score-high">100</td><td>92.8</td></tr>
482
+ <tr><td>HMMT 2025 (Feb)</td><td>95.4</td><td class="score-high">99.4</td><td>92.9</td></tr>
483
+ <tr><td>SWE-Bench Verified</td><td>76.8</td><td>80.0</td><td class="score-high">80.9</td></tr>
484
+ <tr><td>BrowseComp (w/ ctx manage)</td><td class="score-high">74.9</td><td>57.8</td><td>59.2</td></tr>
485
+ </table>
486
+ </div>
487
+ </div>
488
+
489
+ <!-- 模型2: Kimi-K2.5 -->
490
+ <div class="model-card">
491
+ <div class="card-left">
492
+ <div class="model-name">Kimi-K2.5</div>
493
+ <div class="developer">月之暗面 Moonshot AI</div>
494
+ <div class="param-badge highlight">1T 参数 / 32B 激活</div>
495
+ <br>
496
+ <span class="type-tag">Image-Text-to-Text</span>
497
+ <span class="license-tag">Modified-MIT</span>
498
+ <div class="stats-row">
499
+ <div class="stat-item">
500
+ <div class="stat-value">256K</div>
501
+ <div class="stat-label">上下文长度</div>
502
+ </div>
503
+ <div class="stat-item">
504
+ <div class="stat-value">895k</div>
505
+ <div class="stat-label">月下载量</div>
506
+ </div>
507
+ </div>
508
+ </div>
509
+ <div class="card-right">
510
+ <h3 class="section-title">核心特性</h3>
511
+ <ul class="feature-list">
512
+ <li><strong>原生多模态预训练</strong> - 在15T视觉语言混合token上持续预训练</li>
513
+ <li><strong>Agent Swarm能力</strong> - 自导向协调的群体执行方案，动态实例化领域代理</li>
514
+ <li><strong>Coding with Vision</strong> - 从UI设计、视频工作流等视觉规范生成代码</li>
515
+ <li><strong>双模式支持</strong> - Thinking（思考）+ Instant（即时）两种推理模式</li>
516
+ <li><strong>MoonViT视觉编码器</strong> - 400M参数，支持图像和视频输入</li>
517
+ </ul>
518
+ <h3 class="section-title">Benchmark 数据</h3>
519
+ <table class="benchmark-table">
520
+ <tr><th>测试项目</th><th>Kimi K2.5</th><th>GPT-5.2</th><th>Claude 4.5 Opus</th></tr>
521
+ <tr><td>HLE-Full (w/ tools)</td><td class="score-high">50.2</td><td>45.5</td><td>43.2</td></tr>
522
+ <tr><td>AIME 2025</td><td>96.1</td><td class="score-high">100</td><td>92.8</td></tr>
523
+ <tr><td>GPQA-Diamond</td><td>87.6</td><td class="score-high">92.4</td><td>87.0</td></tr>
524
+ <tr><td>SWE-Bench Verified</td><td>76.8</td><td>80.0</td><td class="score-high">80.9</td></tr>
525
+ <tr><td>VideoMME</td><td class="score-high">87.4</td><td>86</td><td>-</td></tr>
526
+ </table>
527
+ </div>
528
+ </div>
529
+
530
+ <!-- 模型3: GLM-5 -->
531
+ <div class="model-card">
532
+ <div class="card-left">
533
+ <div class="model-name">GLM-5</div>
534
+ <div class="developer">Z.ai (智谱AI)</div>
535
+ <div class="param-badge">754B 参数 / 40B 激活</div>
536
+ <br>
537
+ <span class="type-tag">Text Generation</span>
538
+ <span class="license-tag">MIT License</span>
539
+ <div class="stats-row">
540
+ <div class="stat-item">
541
+ <div class="stat-value">131K</div>
542
+ <div class="stat-label">上下文长度</div>
543
+ </div>
544
+ <div class="stat-item">
545
+ <div class="stat-value">170k</div>
546
+ <div class="stat-label">月下载量</div>
547
+ </div>
548
+ </div>
549
+ </div>
550
+ <div class="card-right">
551
+ <h3 class="section-title">核心特性</h3>
552
+ <ul class="feature-list">
553
+ <li><strong>DeepSeek Sparse Attention (DSA)</strong> - 稀疏注意力机制，大幅降低部署成本</li>
554
+ <li><strong>异步RL训练框架 slime</strong> - 自研强化学习基础设施，提升训练效率</li>
555
+ <li><strong>预训练数据 28.5T tokens</strong> - 相比GLM-4.5的23T显著增加</li>
556
+ <li><strong>推理与代理能力突出</strong> - 在reasoning、coding、agentic任务达到开源最佳</li>
557
+ <li><strong>支持部署</strong> - vLLM, SGLang, KTransformers, xLLM</li>
558
+ </ul>
559
+ <h3 class="section-title">Benchmark 数据</h3>
560
+ <table class="benchmark-table">
561
+ <tr><th>测试项目</th><th>GLM-5</th><th>DeepSeek-V3.2</th><th>Kimi K2.5</th></tr>
562
+ <tr><td>HLE</td><td class="score-high">30.5</td><td>25.1</td><td>31.5</td></tr>
563
+ <tr><td>HLE (w/ Tools)</td><td>50.4</td><td>40.8</td><td class="score-high">51.8</td></tr>
564
+ <tr><td>AIME 2026 I</td><td>92.7</td><td>92.7</td><td class="score-mid">92.5</td></tr>
565
+ <tr><td>GPQA-Diamond</td><td>86.0</td><td>82.4</td><td class="score-high">87.6</td></tr>
566
+ <tr><td>SWE-bench Verified</td><td>77.8</td><td>73.1</td><td class="score-mid">76.8</td></tr>
567
+ </table>
568
+ </div>
569
+ </div>
570
+
571
+ <!-- 模型4: MiniMax-M2.5 -->
572
+ <div class="model-card">
573
+ <div class="card-left">
574
+ <div class="model-name">MiniMax-M2.5</div>
575
+ <div class="developer">MiniMaxAI (中国)</div>
576
+ <div class="param-badge">229B 参数</div>
577
+ <br>
578
+ <span class="type-tag">Text Generation</span>
579
+ <span class="license-tag">Modified-MIT</span>
580
+ <div class="stats-row">
581
+ <div class="stat-item">
582
+ <div class="stat-value">100</div>
583
+ <div class="stat-label">TPS速度</div>
584
+ </div>
585
+ <div class="stat-item">
586
+ <div class="stat-value">$1/h</div>
587
+ <div class="stat-label">运行成本</div>
588
+ </div>
589
+ </div>
590
+ </div>
591
+ <div class="card-right">
592
+ <h3 class="section-title">核心特性</h3>
593
+ <ul class="feature-list">
594
+ <li><strong>SOTA代理能力</strong> - coding、agentic tool use、search达到业界领先水平</li>
595
+ <li><strong>SWE-Bench Verified 80.2%</strong> - Multi-SWE-Bench 51.3%，BrowseComp 76.3%</li>
596
+ <li><strong>高推理速度</strong> - 原生支持100 tokens/秒，比其他前沿模型快近2倍</li>
597
+ <li><strong>极低成本</strong> - $1/小时 @ 100 TPS，仅为Claude Opus 4.6成本的10%</li>
598
+ <li><strong>Forge RL框架</strong> - 自研agent-native RL框架，支持40x训练加速</li>
599
+ </ul>
600
+ <h3 class="section-title">Benchmark 数据</h3>
601
+ <table class="benchmark-table">
602
+ <tr><th>测试项目</th><th>MiniMax-M2.5</th><th>Claude Opus 4.6</th><th>GPT-5.2</th></tr>
603
+ <tr><td>SWE-Bench Verified</td><td class="score-high">80.2</td><td>-</td><td>80.0</td></tr>
604
+ <tr><td>BrowseComp (w/ ctx)</td><td class="score-high">76.3</td><td>57.9</td><td>37.0</td></tr>
605
+ <tr><td>AIME25</td><td>86.3</td><td class="score-high">95.6</td><td>86.3</td></tr>
606
+ <tr><td>GPQA-D</td><td>85.2</td><td class="score-high">90.0</td><td>85.2</td></tr>
607
+ <tr><td>HLE w/o tools</td><td>19.4</td><td class="score-high">30.7</td><td>19.4</td></tr>
608
+ </table>
609
+ </div>
610
+ </div>
611
+
612
+ <!-- 模型5: Qwen3.5-397B-A17B -->
613
+ <div class="model-card">
614
+ <div class="card-left">
615
+ <div class="model-name">Qwen3.5-397B-A17B</div>
616
+ <div class="developer">阿里巴巴通义千问团队</div>
617
+ <div class="param-badge">403B 参数 / 17B 激活</div>
618
+ <br>
619
+ <span class="type-tag">Image-Text-to-Text</span>
620
+ <span class="license-tag">Apache 2.0</span>
621
+ <div class="stats-row">
622
+ <div class="stat-item">
623
+ <div class="stat-value">1M</div>
624
+ <div class="stat-label">上下文长度</div>
625
+ </div>
626
+ <div class="stat-item">
627
+ <div class="stat-value">201</div>
628
+ <div class="stat-label">支持语言数</div>
629
+ </div>
630
+ </div>
631
+ </div>
632
+ <div class="card-right">
633
+ <h3 class="section-title">核心特性</h3>
634
+ <ul class="feature-list">
635
+ <li><strong>Gated Delta Networks + MoE架构</strong> - 高效混合架构，高吞吐低延迟</li>
636
+ <li><strong>原生多模态训练</strong> - 早期融合视觉语言token训练</li>
637
+ <li><strong>超长上下文</strong> - 原生支持262K tokens，可扩展至1M tokens</li>
638
+ <li><strong>201种语言支持</strong> - 全球最广泛的语言覆盖</li>
639
+ <li><strong>架构细节</strong> - 60层网络，512专家/每次激活10+1专家</li>
640
+ </ul>
641
+ <h3 class="section-title">Benchmark 数据</h3>
642
+ <table class="benchmark-table">
643
+ <tr><th>测试项目</th><th>Qwen3.5-397B</th><th>GPT-5.2</th><th>Claude 4.5 Opus</th></tr>
644
+ <tr><td>MMLU-Pro</td><td class="score-high">87.8</td><td>87.4</td><td>89.5</td></tr>
645
+ <tr><td>HLE w/ tool</td><td>48.3</td><td>45.5</td><td class="score-high">43.4</td></tr>
646
+ <tr><td>SWE-bench Verified</td><td>76.4</td><td>80.0</td><td class="score-high">80.9</td></tr>
647
+ <tr><td>BrowseComp</td><td class="score-high">78.6</td><td>65.8</td><td>67.8</td></tr>
648
+ <tr><td>VideoMME (w sub)</td><td>87.5</td><td>86</td><td class="score-high">88.4</td></tr>
649
+ </table>
650
+ </div>
651
+ </div>
652
+
653
+ <!-- 模型6: Nanbeige4.1-3B -->
654
+ <div class="model-card">
655
+ <div class="card-left">
656
+ <div class="model-name">Nanbeige4.1-3B</div>
657
+ <div class="developer">Nanbeige</div>
658
+ <div class="param-badge">4B 参数</div>
659
+ <br>
660
+ <span class="type-tag">Text Generation</span>
661
+ <span class="license-tag">开源许可</span>
662
+ <div class="stats-row">
663
+ <div class="stat-item">
664
+ <div class="stat-value">50.9k</div>
665
+ <div class="stat-label">月下载量</div>
666
+ </div>
667
+ </div>
668
+ </div>
669
+ <div class="card-right">
670
+ <h3 class="section-title">核心特性</h3>
671
+ <ul class="feature-list">
672
+ <li><strong>轻量级模型</strong> - 4B参数，适合边缘设备部署</li>
673
+ <li><strong>高性价比</strong> - 小参数量但保持良好性能</li>
674
+ <li><strong>快速推理</strong> - 低延迟响应</li>
675
+ </ul>
676
+ </div>
677
+ </div>
678
+
679
+ <!-- 模型7: MiniCPM-SALA -->
680
+ <div class="model-card">
681
+ <div class="card-left">
682
+ <div class="model-name">MiniCPM-SALA</div>
683
+ <div class="developer">OpenBMB / 清华大学</div>
684
+ <div class="param-badge">9B 参数</div>
685
+ <br>
686
+ <span class="type-tag">Text Generation</span>
687
+ <span class="license-tag">开源许可</span>
688
+ <div class="stats-row">
689
+ <div class="stat-item">
690
+ <div class="stat-value">4.15k</div>
691
+ <div class="stat-label">月下载量</div>
692
+ </div>
693
+ </div>
694
+ </div>
695
+ <div class="card-right">
696
+ <h3 class="section-title">核心特性</h3>
697
+ <ul class="feature-list">
698
+ <li><strong>端侧优化模型</strong> - 清华大学OpenBMB团队开发</li>
699
+ <li><strong>SALA架构</strong> - 高效注意力机制</li>
700
+ <li><strong>移动设备友好</strong> - 适合手机等边缘部署</li>
701
+ </ul>
702
+ </div>
703
+ </div>
704
+
705
+ <!-- 模型8: personaplex-7b-v1 -->
706
+ <div class="model-card">
707
+ <div class="card-left">
708
+ <div class="model-name">personaplex-7b-v1</div>
709
+ <div class="developer">NVIDIA</div>
710
+ <div class="param-badge">~7B 参数</div>
711
+ <br>
712
+ <span class="type-tag">Audio-to-Audio</span>
713
+ <span class="license-tag">开源许可</span>
714
+ <div class="stats-row">
715
+ <div class="stat-item">
716
+ <div class="stat-value">440k</div>
717
+ <div class="stat-label">月下载量</div>
718
+ </div>
719
+ </div>
720
+ </div>
721
+ <div class="card-right">
722
+ <h3 class="section-title">核心特性</h3>
723
+ <ul class="feature-list">
724
+ <li><strong>NVIDIA语音对话模型</strong> - 支持实时音频输入输出交互</li>
725
+ <li><strong>多说话人支持</strong> - 适用于会议转录、语音助手等场景</li>
726
+ <li><strong>高质量语音理解</strong> - NVIDIA深度学习技术加持</li>
727
+ </ul>
728
+ </div>
729
+ </div>
730
+
731
+ <!-- 模型9: MOSS-TTS -->
732
+ <div class="model-card">
733
+ <div class="card-left">
734
+ <div class="model-name">MOSS-TTS</div>
735
+ <div class="developer">OpenMOSS-Team (复旦/上海AI Lab)</div>
736
+ <div class="param-badge">8B 参数</div>
737
+ <br>
738
+ <span class="type-tag">Text-to-Speech</span>
739
+ <span class="license-tag">开源许可</span>
740
+ <div class="stats-row">
741
+ <div class="stat-item">
742
+ <div class="stat-value">21.5k</div>
743
+ <div class="stat-label">月下载量</div>
744
+ </div>
745
+ </div>
746
+ </div>
747
+ <div class="card-right">
748
+ <h3 class="section-title">核心特性</h3>
749
+ <ul class="feature-list">
750
+ <li><strong>高质量中文语音合成</strong> - 复旦大学/上海AI Lab联合开发</li>
751
+ <li><strong>多说话人支持</strong> - 支持多种声音风格和情感表达</li>
752
+ <li><strong>应用场景广泛</strong> - 有声书、配音、虚拟主播等</li>
753
+ </ul>
754
+ </div>
755
+ </div>
756
+
757
+ <!-- 模型10: Ming-flash-omni-2.0 -->
758
+ <div class="model-card">
759
+ <div class="card-left">
760
+ <div class="model-name">Ming-flash-omni-2.0</div>
761
+ <div class="developer">inclusionAI (蚂蚁集团)</div>
762
+ <div class="param-badge">多模态模型</div>
763
+ <br>
764
+ <span class="type-tag">Any-to-Any</span>
765
+ <span class="license-tag">开源许可</span>
766
+ <div class="stats-row">
767
+ <div class="stat-item">
768
+ <div class="stat-value">6.91k</div>
769
+ <div class="stat-label">月下载量</div>
770
+ </div>
771
+ </div>
772
+ </div>
773
+ <div class="card-right">
774
+ <h3 class="section-title">核心特性</h3>
775
+ <ul class="feature-list">
776
+ <li><strong>全模态模型</strong> - 支持任意输入输出组合</li>
777
+ <li><strong>Flash高效架构</strong> - 快速推理响应</li>
778
+ <li><strong>蚂蚁集团出品</strong> - 与Ring系列同团队开发</li>
779
+ </ul>
780
+ </div>
781
+ </div>
782
+
783
+ <!-- 模型11: MiniCPM-o-4_5 -->
784
+ <div class="model-card">
785
+ <div class="card-left">
786
+ <div class="model-name">MiniCPM-o-4_5</div>
787
+ <div class="developer">OpenBMB / 清华大学</div>
788
+ <div class="param-badge">9B 参数</div>
789
+ <br>
790
+ <span class="type-tag">Any-to-Any</span>
791
+ <span class="license-tag">开源许可</span>
792
+ <div class="stats-row">
793
+ <div class="stat-item">
794
+ <div class="stat-value">55.4k</div>
795
+ <div class="stat-label">月下载量</div>
796
+ </div>
797
+ </div>
798
+ </div>
799
+ <div class="card-right">
800
+ <h3 class="section-title">核心特性</h3>
801
+ <ul class="feature-list">
802
+ <li><strong>端侧多模态大模型</strong> - 支持在手机等设备运行</li>
803
+ <li><strong>全模态理解与生成</strong> - 图像、视频、音频、文本全覆盖</li>
804
+ <li><strong>高效推理</strong> - 适合边缘部署场景</li>
805
+ </ul>
806
+ </div>
807
+ </div>
808
+
809
+ <!-- 模型12: Qwen3-Coder-Next -->
810
+ <div class="model-card">
811
+ <div class="card-left">
812
+ <div class="model-name">Qwen3-Coder-Next</div>
813
+ <div class="developer">阿里巴巴通义千问团队</div>
814
+ <div class="param-badge">80B 参数</div>
815
+ <br>
816
+ <span class="type-tag">Text Generation (代码)</span>
817
+ <span class="license-tag">开源许可</span>
818
+ <div class="stats-row">
819
+ <div class="stat-item">
820
+ <div class="stat-value">334k</div>
821
+ <div class="stat-label">月下载量</div>
822
+ </div>
823
+ </div>
824
+ </div>
825
+ <div class="card-right">
826
+ <h3 class="section-title">核心特性</h3>
827
+ <ul class="feature-list">
828
+ <li><strong>代码专用模型</strong> - 专为编程任务优化</li>
829
+ <li><strong>多语言支持</strong> - 支持多种编程语言的生成、补全、解释</li>
830
+ <li><strong>LiveCodeBench优异表现</strong> - 在代码评测中名列前茅</li>
831
+ </ul>
832
+ </div>
833
+ </div>
834
+
835
+ <!-- 模型13: GLM-OCR -->
836
+ <div class="model-card">
837
+ <div class="card-left">
838
+ <div class="model-name">GLM-OCR</div>
839
+ <div class="developer">Z.ai (智谱AI)</div>
840
+ <div class="param-badge">OCR专用模型</div>
841
+ <br>
842
+ <span class="type-tag">Image-to-Text (OCR)</span>
843
+ <span class="license-tag">开源许可</span>
844
+ <div class="stats-row">
845
+ <div class="stat-item">
846
+ <div class="stat-value">1.06M</div>
847
+ <div class="stat-label">月下载量</div>
848
+ </div>
849
+ </div>
850
+ </div>
851
+ <div class="card-right">
852
+ <h3 class="section-title">核心特性</h3>
853
+ <ul class="feature-list">
854
+ <li><strong>基于GLM架构的OCR专用模型</strong></li>
855
+ <li><strong>复杂文档识别</strong> - 支持表格、手写体等复杂场景</li>
856
+ <li><strong>高精度中英文混合识别</strong> - 下载量超百万，最受欢迎OCR模型之一</li>
857
+ </ul>
858
+ </div>
859
+ </div>
860
+
861
+ <!-- 模型14: Voxtral-Mini-4B -->
862
+ <div class="model-card">
863
+ <div class="card-left">
864
+ <div class="model-name">Voxtral-Mini-4B</div>
865
+ <div class="developer">Mistral AI</div>
866
+ <div class="param-badge">4B 参数</div>
867
+ <br>
868
+ <span class="type-tag">Automatic Speech Recognition</span>
869
+ <span class="license-tag">开源许可</span>
870
+ <div class="stats-row">
871
+ <div class="stat-item">
872
+ <div class="stat-value">15.5k</div>
873
+ <div class="stat-label">月下载量</div>
874
+ </div>
875
+ </div>
876
+ </div>
877
+ <div class="card-right">
878
+ <h3 class="section-title">核心特性</h3>
879
+ <ul class="feature-list">
880
+ <li><strong>Mistral最新轻量级语音识别模型</strong></li>
881
+ <li><strong>实时转录</strong> - 低延迟，适合边缘部署</li>
882
+ <li><strong>多语言支持</strong> - 支持多种语言的语音转文字</li>
883
+ </ul>
884
+ </div>
885
+ </div>
886
+
887
+ </div>
888
+ </div>
889
+
890
+ <!-- 导航控制 -->
891
+ <div class="carousel-nav">
892
+ <button class="nav-btn" id="prevBtn">◀</button>
893
+ <div class="nav-dots" id="navDots"></div>
894
+ <button class="nav-btn" id="nextBtn">▶</button>
895
+ </div>
896
+
897
+ <!-- 页脚 -->
898
+ <footer>
899
+ <p>📅 调研日期：2026年02月18日 | 数据来源：<a href="https://huggingface.co/models" target="_blank">Hugging Face Models Trending</a></p>
900
+ <p style="margin-top: 10px; font-size: 0.8rem;">本页面自动轮播展示，按 ← → 键或点击导航点切换模型</p>
901
+ </footer>
902
+ </div>
903
+
904
+ <script>
905
+ // 创建背景粒子
906
+ function createParticles() {
907
+ const container = document.getElementById('particles');
908
+ for (let i = 0; i < 50; i++) {
909
+ const particle = document.createElement('div');
910
+ particle.className = 'particle';
911
+ particle.style.left = Math.random() * 100 + '%';
912
+ particle.style.animationDelay = Math.random() * 20 + 's';
913
+ particle.style.animationDuration = (15 + Math.random() * 10) + 's';
914
+ container.appendChild(particle);
915
+ }
916
+ }
917
+
918
+ // 轮播功能
919
+ const track = document.getElementById('carouselTrack');
920
+ const dotsContainer = document.getElementById('navDots');
921
+ const progressFill = document.getElementById('progressFill');
922
+ const totalSlides = 14;
923
+ let currentSlide = 0;
924
+ let autoPlayInterval;
925
+ let isAutoPlaying = true;
926
+
927
+ // 创建导航点
928
+ for (let i = 0; i < totalSlides; i++) {
929
+ const dot = document.createElement('div');
930
+ dot.className = 'dot' + (i === 0 ? ' active' : '');
931
+ dot.addEventListener('click', () => goToSlide(i));
932
+ dotsContainer.appendChild(dot);
933
+ }
934
+
935
+ function updateDots() {
936
+ const dots = document.querySelectorAll('.dot');
937
+ dots.forEach((dot, index) => {
938
+ dot.classList.toggle('active', index === currentSlide);
939
+ });
940
+ }
941
+
942
+ function goToSlide(index) {
943
+ currentSlide = index;
944
+ track.style.transform = `translateX(-${currentSlide * 100}%)`;
945
+ updateDots();
946
+ resetAutoPlay();
947
+ }
948
+
949
+ function nextSlide() {
950
+ currentSlide = (currentSlide + 1) % totalSlides;
951
+ goToSlide(currentSlide);
952
+ }
953
+
954
+ function prevSlide() {
955
+ currentSlide = (currentSlide - 1 + totalSlides) % totalSlides;
956
+ goToSlide(currentSlide);
957
+ }
958
+
959
+ function resetAutoPlay() {
960
+ clearInterval(autoPlayInterval);
961
+ progressFill.style.animation = 'none';
962
+ progressFill.offsetHeight; // 触发重绘
963
+ progressFill.style.animation = 'slideProgress 8s linear forwards';
964
+
965
+ autoPlayInterval = setInterval(() => {
966
+ nextSlide();
967
+ }, 8000);
968
+ }
969
+
970
+ // 按钮事件
971
+ document.getElementById('prevBtn').addEventListener('click', () => {
972
+ prevSlide();
973
+ });
974
+
975
+ document.getElementById('nextBtn').addEventListener('click', () => {
976
+ nextSlide();
977
+ });
978
+
979
+ // 键盘控制
980
+ document.addEventListener('keydown', (e) => {
981
+ if (e.key === 'ArrowLeft') prevSlide();
982
+ if (e.key === 'ArrowRight') nextSlide();
983
+ });
984
+
985
+ // 初始化
986
+ createParticles();
987
+ resetAutoPlay();
988
+
989
+ // 悬停暂停自动播放
990
+ const carouselContainer = document.querySelector('.carousel-container');
991
+ carouselContainer.addEventListener('mouseenter', () => {
992
+ clearInterval(autoPlayInterval);
993
+ progressFill.style.animationPlayState = 'paused';
994
+ });
995
+
996
+ carouselContainer.addEventListener('mouseleave', () => {
997
+ resetAutoPlay();
998
+ });
999
+ </script>
1000
+ </body>
1001
+ </html>