{"id":128131,"date":"2026-07-07T17:50:55","date_gmt":"2026-07-07T10:50:55","guid":{"rendered":"https:\/\/tino.vn\/blog\/?p=128131"},"modified":"2026-07-09T14:15:18","modified_gmt":"2026-07-09T07:15:18","slug":"model-ai-tot-nhat-tren-openrouter","status":"publish","type":"post","link":"https:\/\/tino.vn\/blog\/model-ai-tot-nhat-tren-openrouter\/","title":{"rendered":"X\u1ebfp h\u1ea1ng c\u00e1c model AI t\u1ed1t nh\u1ea5t tr\u00ean OpenRouter 2026 (theo t\u1eebng t\u00e1c v\u1ee5)\u00a0"},"content":{"rendered":"\n

OpenRouter hi\u1ec7n l\u00e0 n\u1ec1n t\u1ea3ng trung gian l\u1edbn nh\u1ea5t gi\u00fap l\u1eadp tr\u00ecnh vi\u00ean v\u00e0 doanh nghi\u1ec7p truy c\u1eadp h\u00e0ng tr\u0103m model AI<\/a> t\u1eeb nhi\u1ec1u nh\u00e0 ph\u00e1t tri\u1ec3n kh\u00e1c nhau ch\u1ec9 qua m\u1ed9t API duy nh\u1ea5t. V\u1eady model n\u00e0o \u0111ang d\u1eabn \u0111\u1ea7u b\u1ea3ng x\u1ebfp h\u1ea1ng? H\u00e3y c\u00f9ng Tino kh\u00e1m ph\u00e1 top 10 model AI t\u1ed1t nh\u1ea5t tr\u00ean OpenRouter theo t\u1eebng t\u00e1c v\u1ee5 qua b\u00e0i vi\u1ebft d\u01b0\u1edbi \u0111\u00e2y nh\u00e9!<\/strong><\/p>\n\n\n\n

OpenRouter Rankings l\u00e0 g\u00ec? <\/strong><\/h2>\n\n\n\n

OpenRouter Rankings l\u00e0 h\u1ec7 th\u1ed1ng b\u1ea3ng x\u1ebfp h\u1ea1ng model AI tr\u00ean OpenRouter, gi\u00fap ng\u01b0\u1eddi d\u00f9ng so s\u00e1nh c\u00e1c model theo m\u1ee9c \u0111\u1ed9 s\u1eed d\u1ee5ng th\u1ef1c t\u1ebf, t\u00e1c v\u1ee5 v\u00e0 nh\u00f3m n\u0103ng l\u1ef1c. <\/p>\n\n\n\n

\u0110i\u1ec3m kh\u00e1c bi\u1ec7t l\u1edbn nh\u1ea5t c\u1ee7a b\u1ea3ng x\u1ebfp h\u1ea1ng tr\u00ean n\u1ec1n t\u1ea3ng n\u00e0y so v\u1edbi c\u00e1c b\u00e0i \u0111\u00e1nh gi\u00e1 benchmark th\u00f4ng th\u01b0\u1eddng n\u1eb1m \u1edf ngu\u1ed3n d\u1eef li\u1ec7u. C\u00e1c con s\u1ed1 \u0111\u01b0\u1ee3c t\u00ednh to\u00e1n tr\u1ef1c ti\u1ebfp t\u1eeb l\u01b0u l\u01b0\u1ee3ng token th\u1ef1c t\u1ebf m\u00e0 h\u00e0ng tri\u1ec7u \u1ee9ng d\u1ee5ng \u0111ang g\u1eedi \u0111i m\u1ed7i tu\u1ea7n, ch\u1ee9 kh\u00f4ng d\u1ef1a tr\u00ean kh\u1ea3o s\u00e1t hay \u0111i\u1ec3m s\u1ed1 ph\u00f2ng th\u00ed nghi\u1ec7m. <\/p>\n\n\n

\n
\"OpenRouter
OpenRouter Rankings l\u00e0 g\u00ec?\u00a0<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n

Nh\u1edd v\u1eady, th\u1ee9 h\u1ea1ng ph\u1ea3n \u00e1nh kh\u00e1 s\u00e1t nhu c\u1ea7u th\u1ecb tr\u01b0\u1eddng. T\u1ee9c model n\u00e0o r\u1ebb, nhanh v\u00e0 \u0111\u1ee7 t\u1ed1t cho c\u00f4ng vi\u1ec7c th\u1ef1c t\u1ebf s\u1ebd c\u00f3 xu h\u01b0\u1edbng d\u1eabn \u0111\u1ea7u v\u1ec1 kh\u1ed1i l\u01b0\u1ee3ng s\u1eed d\u1ee5ng, trong khi model \u0111\u1eaft ti\u1ec1n h\u01a1n v\u1eabn gi\u1eef v\u1ecb tr\u00ed cao \u1edf nh\u1eefng t\u00e1c v\u1ee5 \u0111\u00f2i h\u1ecfi \u0111\u1ed9 ch\u00ednh x\u00e1c t\u1ed1i \u0111a nh\u01b0 ph\u00e2n t\u00edch t\u00e0i ch\u00ednh hay r\u00e0 so\u00e1t m\u00e3 ngu\u1ed3n ph\u1ee9c t\u1ea1p. <\/p>\n\n\n\n

\ud83d\udc49 Xem th\u00eam: OpenRouter l\u00e0 g\u00ec?<\/a><\/p>\n\n\n\n

Tuy nhi\u00ean, c\u0169ng c\u1ea7n l\u01b0u \u00fd r\u1eb1ng: Th\u1ee9 h\u1ea1ng theo l\u01b0u l\u01b0\u1ee3ng s\u1eed d\u1ee5ng kh\u00f4ng \u0111\u1ed3ng ngh\u0129a v\u1edbi ch\u1ea5t l\u01b0\u1ee3ng cao nh\u1ea5t tuy\u1ec7t \u0111\u1ed1i. M\u1ed9t model x\u1ebfp h\u1ea1ng cao c\u00f3 th\u1ec3 ch\u1ec9 v\u00ec m\u1ee9c gi\u00e1 c\u1ef1c r\u1ebb ho\u1eb7c m\u1edbi ra m\u1eaft v\u00e0 \u0111ang \u0111\u01b0\u1ee3c m\u1ed9t \u1ee9ng d\u1ee5ng l\u1edbn d\u00f9ng th\u1eed \u1ed3 \u1ea1t, kh\u00f4ng h\u1eb3n ph\u1ea3n \u00e1nh model ph\u00f9 h\u1ee3p nh\u1ea5t cho m\u1ecdi tr\u01b0\u1eddng h\u1ee3p. <\/p>\n\n\n\n

Top c\u00e1c model AI t\u1ed1t nh\u1ea5t tr\u00ean OpenRouter theo t\u1eebng t\u00e1c v\u1ee5<\/strong><\/h2>\n\n\n\n

L\u01b0u \u00fd: <\/strong>OpenRouter Rankings l\u00e0 b\u1ea3ng x\u1ebfp h\u1ea1ng \u0111\u1ed9ng. Th\u1ee9 h\u1ea1ng, s\u1ed1 token v\u00e0 danh s\u00e1ch model c\u00f3 th\u1ec3 thay \u0111\u1ed5i theo th\u1eddi gian. <\/p>\n\n\n\n

10 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Text<\/strong><\/h3>\n\n\n\n

T\u00e1c v\u1ee5 Text l\u00e0 nh\u00f3m model d\u00f9ng \u0111\u1ec3 t\u1ea1o v\u0103n b\u1ea3n, tr\u1ea3 l\u1eddi c\u00e2u h\u1ecfi, vi\u1ebft n\u1ed9i dung, l\u1eadp tr\u00ecnh, ph\u00e2n t\u00edch t\u00e0i li\u1ec7u, x\u00e2y d\u1ef1ng chatbot v\u00e0 v\u1eadn h\u00e0nh AI Agent. <\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>Ph\u00f9 h\u1ee3p cho<\/th>\u0110i\u1ec3m n\u1ed5i b\u1eadt<\/th><\/tr>
1<\/td>DeepSeek V4 Flash<\/td>DeepSeek<\/td>Chatbot, coding, AI Agent, x\u1eed l\u00fd v\u0103n b\u1ea3n kh\u1ed1i l\u01b0\u1ee3ng l\u1edbn<\/td>T\u1ed1i \u01b0u hi\u1ec7u su\u1ea5t, chi ph\u00ed t\u1ed1t, ph\u00f9 h\u1ee3p t\u00e1c v\u1ee5 c\u1ea7n t\u1ed1c \u0111\u1ed9<\/td><\/tr>
2<\/td>MiMo-V2.5<\/td>Xiaomi<\/td>Agent workflow, ph\u00e2n t\u00edch \u0111a ph\u01b0\u01a1ng th\u1ee9c, tr\u1ee3 l\u00fd th\u00f4ng minh<\/td>Context d\u00e0i, chi ph\u00ed c\u1ea1nh tranh, ph\u00f9 h\u1ee3p h\u1ec7 th\u1ed1ng c\u1ea7n \u0111a n\u0103ng<\/td><\/tr>
3<\/td>MiniMax M3<\/td>MiniMax<\/td>Coding, t\u00e1c v\u1ee5 d\u00e0i, AI Agent, x\u1eed l\u00fd t\u00e0i li\u1ec7u<\/td>H\u1ed7 tr\u1ee3 text, image, video input v\u00e0 context l\u1edbn<\/td><\/tr>
4<\/td>Hy3 preview<\/td>Tencent<\/td>L\u1eadp tr\u00ecnh, t\u00e1c v\u1ee5 doanh nghi\u1ec7p, workflow t\u1ef1 \u0111\u1ed9ng<\/td>Mixture-of-Experts, h\u1ed7 tr\u1ee3 reasoning theo c\u1ea5p \u0111\u1ed9<\/td><\/tr>
5<\/td>GLM 5.2<\/td>Z.ai<\/td>Coding, tool use, t\u00e1c v\u1ee5 nhi\u1ec1u b\u01b0\u1edbc<\/td>M\u1ea1nh v\u1ec1 t\u00e1c v\u1ee5 k\u1ef9 thu\u1eadt v\u00e0 x\u1eed l\u00fd ng\u1eef c\u1ea3nh d\u00e0i<\/td><\/tr>
6<\/td>DeepSeek V4 Pro<\/td>DeepSeek<\/td>Suy lu\u1eadn n\u00e2ng cao, ph\u00e2n t\u00edch codebase, automation<\/td>B\u1ea3n m\u1ea1nh h\u01a1n c\u1ee7a d\u00f2ng DeepSeek V4, ph\u00f9 h\u1ee3p t\u00e1c v\u1ee5 kh\u00f3<\/td><\/tr>
7<\/td>Claude Opus 4.8<\/td>Anthropic<\/td>Vi\u1ebft chuy\u00ean s\u00e2u, coding ph\u1ee9c t\u1ea1p, ph\u00e2n t\u00edch d\u00e0i<\/td>Ch\u1ea5t l\u01b0\u1ee3ng cao cho t\u00e1c v\u1ee5 c\u1ea7n \u0111\u1ed9 tin c\u1eady v\u00e0 l\u1eadp lu\u1eadn t\u1ed1t<\/td><\/tr>
8<\/td>Claude Opus 4.7<\/td>Anthropic<\/td>Vi\u1ebft n\u1ed9i dung, ph\u00e2n t\u00edch, coding, nghi\u00ean c\u1ee9u<\/td>\u1ed4n \u0111\u1ecbnh cho t\u00e1c v\u1ee5 chuy\u00ean nghi\u1ec7p v\u00e0 x\u1eed l\u00fd d\u00e0i<\/td><\/tr>
9<\/td>Step 3.7 Flash <\/td> StepFun<\/td>T\u00e1c v\u1ee5 nhanh, coding, x\u1eed l\u00fd v\u0103n b\u1ea3n<\/td>T\u1ed1i \u01b0u t\u1ed1c \u0111\u1ed9, ph\u00f9 h\u1ee3p workflow c\u1ea7n ph\u1ea3n h\u1ed3i nhanh<\/td><\/tr>
10<\/td>Claude Sonnet 4.6<\/td>Anthropic<\/td>Vi\u1ebft n\u1ed9i dung, ph\u00e2n t\u00edch, nghi\u00ean c\u1ee9u<\/td>Vi\u1ebft n\u1ed9i dung, ph\u00e2n t\u00edch, coding, nghi\u00ean c\u1ee9u<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings<\/a> <\/p>\n\n\n

\n
\"Top
Top c\u00e1c model AI t\u1ed1t nh\u1ea5t tr\u00ean OpenRouter theo t\u1eebng t\u00e1c v\u1ee5<\/strong><\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n

10 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Image <\/strong><\/h3>\n\n\n\n

T\u00e1c v\u1ee5 Image g\u1ed3m t\u1ea1o \u1ea3nh t\u1eeb prompt, ch\u1ec9nh s\u1eeda \u1ea3nh, t\u1ea1o poster, concept art, \u1ea3nh s\u1ea3n ph\u1ea9m, \u1ea3nh qu\u1ea3ng c\u00e1o v\u00e0 h\u00ecnh minh h\u1ecda.\u00a0<\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>L\u01b0\u1ee3t y\u00eau c\u1ea7u<\/th>Xu h\u01b0\u1edbng<\/th><\/tr><\/thead>
1<\/td>Nano Banana (Gemini 2.5 Flash Image)<\/td>Google<\/td>2,01M<\/td>\u2193 5%<\/td><\/tr>
2<\/td>Nano Banana 2 (Gemini 3.1 Flash Image)<\/td>Google<\/td>858K<\/td>\u2193 10%<\/td><\/tr>
3<\/td>Nano Banana 2 (Gemini 3.1 Flash Image)<\/td>Google<\/td>649K<\/td>\u2191 9%<\/td><\/tr>
4<\/td>Nano Banana Pro (Gemini 3 Pro Image)<\/td>Google<\/td>506K<\/td>\u2193 5%<\/td><\/tr>
5<\/td>Grok Imagine Image Quality<\/td>xAI<\/td>352K<\/td>\u2191 15%<\/td><\/tr>
6<\/td>Nano Banana Pro (Gemini 3 Pro Image)<\/td>Google<\/td>349K<\/td>\u2191 9%<\/td><\/tr>
7<\/td>Nano Banana 2 Lite (Gemini 3.1 Flash Image)<\/td>Google<\/td>165K<\/td>M\u1edbi<\/td><\/tr>
8<\/td>Seedream 4.5<\/td>ByteDance Seed<\/td>128K<\/td>\u2193 9%<\/td><\/tr>
9<\/td>GPT-5.4 Image 2<\/td>OpenAI<\/td>127K<\/td>\u2193 13%<\/td><\/tr>
10<\/td>FLUX.2 Klein 4B<\/td>Black Forest Labs<\/td>102K<\/td>\u2191 86%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings\/image<\/a> <\/p>\n\n\n\n

10 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Embedding<\/strong><\/h3>\n\n\n\n

Embedding l\u00e0 k\u1ef9 thu\u1eadt chuy\u1ec3n v\u0103n b\u1ea3n th\u00e0nh vector \u0111\u1ec3 ph\u1ee5c v\u1ee5 t\u00ecm ki\u1ebfm ng\u1eef ngh\u0129a, RAG, ph\u00e2n c\u1ee5m, g\u1ee3i \u00fd n\u1ed9i dung v\u00e0 so kh\u1edbp t\u00e0i li\u1ec7u.<\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>L\u01b0\u1ee3t y\u00eau c\u1ea7u<\/th>Xu h\u01b0\u1edbng<\/th><\/tr><\/thead>
1<\/td>Text Embedding 3 Small<\/td>OpenAI<\/td>71,5M<\/td>\u2191 8%<\/td><\/tr>
2<\/td>Qwen3 Embedding 8B<\/td>Qwen<\/td>54,2M<\/td>\u2191 2%<\/td><\/tr>
3<\/td>bge-m3<\/td>BAAI<\/td>15,9M<\/td>\u2191 64%<\/td><\/tr>
4<\/td>Text Embedding 3 Large<\/td>OpenAI<\/td>11,4M<\/td>\u2193 1%<\/td><\/tr>
5<\/td>Gemini Embedding 001<\/td>Google<\/td>11,2M<\/td>\u2191 16%<\/td><\/tr>
6<\/td>Embed V1 0.6B<\/td>Perplexity<\/td>9,57M<\/td>\u2193 2%<\/td><\/tr>
7<\/td>Gemini Embedding 2<\/td>Google<\/td>8,11M<\/td>\u2191 7%<\/td><\/tr>
8<\/td>Qwen3 Embedding 4B<\/td>Qwen<\/td>5,92M<\/td>\u2193 14%<\/td><\/tr>
9<\/td>Llama Nemotron Embed VL 1B V2<\/td>NVIDIA<\/td>4,67M<\/td>\u2191 0%<\/td><\/tr>
10<\/td>Multilingual-E5-Large<\/td>intfloat<\/td>2,9M<\/td>\u2191 20%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings\/embeddings<\/a> <\/p>\n\n\n\n

4 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Rerank <\/strong><\/h3>\n\n\n\n

Rerank model d\u00f9ng \u0111\u1ec3 s\u1eafp x\u1ebfp l\u1ea1i k\u1ebft qu\u1ea3 truy h\u1ed3i theo m\u1ee9c \u0111\u1ed9 li\u00ean quan. Trong h\u1ec7 th\u1ed1ng RAG, embedding th\u01b0\u1eddng l\u1ea5y ra nhi\u1ec1u t\u00e0i li\u1ec7u \u1ee9ng vi\u00ean, c\u00f2n rerank model gi\u00fap ch\u1ecdn \u0111o\u1ea1n ph\u00f9 h\u1ee3p nh\u1ea5t \u0111\u1ec3 \u0111\u01b0a v\u00e0o prompt. <\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>L\u01b0\u1ee3t y\u00eau c\u1ea7u<\/th>Xu h\u01b0\u1edbng<\/th><\/tr><\/thead>
1<\/td>Llama Nemotron Rerank VL 1B V2<\/td>NVIDIA<\/td>621K<\/td>\u2191 52%<\/td><\/tr>
2<\/td>Rerank v3.5<\/td>Cohere<\/td>507K<\/td>\u2191 22%<\/td><\/tr>
3<\/td>Rerank 4 Fast<\/td>Cohere<\/td>298K<\/td>\u2193 38%<\/td><\/tr>
4<\/td>Rerank 4 Pro<\/td>Cohere<\/td>235K<\/td>\u2193 6%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Ghi ch\u00fa:<\/strong> V\u1edbi t\u00e1c v\u1ee5 Rerank, OpenRouter hi\u1ec7n kh\u00f4ng hi\u1ec3n th\u1ecb \u0111\u1ee7 10 model c\u00f4ng khai trong d\u1eef li\u1ec7u thu th\u1eadp \u0111\u01b0\u1ee3c. V\u00ec v\u1eady, b\u1ea3ng tr\u00ean ch\u1ec9 li\u1ec7t k\u00ea c\u00e1c model c\u00f3 c\u0103n c\u1ee9 tr\u1ef1c ti\u1ebfp t\u1eeb ngu\u1ed3n. <\/p>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings\/rerank<\/a> <\/p>\n\n\n

\n
\"4
4 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Rerank\u00a0<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n

10 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 video<\/strong><\/h3>\n\n\n\n

T\u00e1c v\u1ee5 video g\u1ed3m text-to-video, image-to-video, reference-to-video, t\u1ea1o clip ng\u1eafn, ho\u1ea1t h\u00f3a \u1ea3nh t\u0129nh, d\u1ef1ng c\u1ea3nh qu\u1ea3ng c\u00e1o v\u00e0 t\u1ea1o n\u1ed9i dung social media. OpenRouter cho bi\u1ebft video generation l\u00e0 nh\u00f3m modality m\u1edbi v\u00e0 c\u00e1c model trong nh\u00f3m n\u00e0y \u0111ang c\u1ea3i thi\u1ec7n nhanh.<\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>L\u01b0\u1ee3t y\u00eau c\u1ea7u<\/th>Xu h\u01b0\u1edbng<\/th><\/tr><\/thead>
1<\/td>Veo 3.1 Fast<\/td>Google<\/td>40K<\/td>\u2193 33%<\/td><\/tr>
2<\/td>Veo 3.1<\/td>Google<\/td>22K<\/td>\u2193 36%<\/td><\/tr>
3<\/td>Seedance 2.0<\/td>ByteDance<\/td>19K<\/td>\u2191 7%<\/td><\/tr>
4<\/td>Veo 3.1 Lite<\/td>Google<\/td>14K<\/td>\u2193 13%<\/td><\/tr>
5<\/td>Grok Imagine Video<\/td>xAI<\/td>9K<\/td>\u2193 9%<\/td><\/tr>
6<\/td>Seedance 2.0 Fast<\/td>ByteDance<\/td>7K<\/td>\u2191 4%<\/td><\/tr>
7<\/td>Seedance 1.5 Pro<\/td>ByteDance<\/td>4K<\/td>\u2191 0%<\/td><\/tr>
8<\/td>Video v3.0 Pro<\/td>kwaivgi<\/td>3K<\/td>\u2193 1%<\/td><\/tr>
9<\/td>Video v3.0 Standard<\/td>kwaivgi<\/td>3K<\/td>\u2193 9%<\/td><\/tr>
10<\/td>HappyHorse 1.1<\/td>Alibaba<\/td>2K<\/td>\u2193 4%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings\/video<\/a> <\/p>\n\n\n\n

9 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Speech<\/strong><\/h3>\n\n\n\n

Speech \u1edf \u0111\u00e2y \u0111\u01b0\u1ee3c hi\u1ec3u l\u00e0 text-to-speech, t\u1ee9c chuy\u1ec3n v\u0103n b\u1ea3n th\u00e0nh gi\u1ecdng \u0111\u1ecdc. Nh\u00f3m model n\u00e0y ph\u00f9 h\u1ee3p cho tr\u1ee3 l\u00fd \u1ea3o, t\u1ed5ng \u0111\u00e0i AI, voiceover, n\u1ed9i dung h\u1ecdc t\u1eadp, \u1ee9ng d\u1ee5ng accessibility v\u00e0 s\u1ea3n ph\u1ea9m c\u00f3 ph\u1ea3n h\u1ed3i b\u1eb1ng \u00e2m thanh. <\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>L\u01b0\u1ee3t y\u00eau c\u1ea7u<\/th>Xu h\u01b0\u1edbng<\/th><\/tr><\/thead>
1<\/td>Gemini 3.1 Flash TTS Preview<\/td>Google<\/td>838K<\/td>\u2191 99%<\/td><\/tr>
2<\/td>Kokoro 82M<\/td>hexgrad<\/td>387K<\/td>\u2191 129%<\/td><\/tr>
3<\/td>Grok Voice TTS 1.0<\/td>xAI<\/td>80K<\/td>\u2191 23%<\/td><\/tr>
4<\/td>MAI-Voice-2<\/td>Microsoft<\/td>71K<\/td>\u2191 24%<\/td><\/tr>
5<\/td>Orpheus 3B<\/td>Canopy Labs<\/td>5K<\/td>\u2191 99%<\/td><\/tr>
6<\/td>Voxtral Mini TTS<\/td>Mistral AI<\/td>4K<\/td>\u2191 65%<\/td><\/tr>
7<\/td>CSM 1B<\/td>Sesame<\/td>765<\/td>\u2193 13%<\/td><\/tr>
8<\/td>Zonos v0.1 Transformer<\/td>Zyphra<\/td>156<\/td>\u2191 88%<\/td><\/tr>
9<\/td>Zonos v0.1 Hybrid<\/td>Zyphra<\/td>92<\/td>\u2191 74%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Ghi ch\u00fa: <\/strong>V\u1edbi t\u00e1c v\u1ee5 Speech, OpenRouter c\u0169ng kh\u00f4ng hi\u1ec3n th\u1ecb \u0111\u1ee7 10 model c\u00f4ng khai trong d\u1eef li\u1ec7u thu th\u1eadp \u0111\u01b0\u1ee3c. V\u00ec v\u1eady, b\u1ea3ng tr\u00ean ch\u1ec9 li\u1ec7t k\u00ea c\u00e1c model c\u00f3 c\u0103n c\u1ee9 tr\u1ef1c ti\u1ebfp t\u1eeb ngu\u1ed3n. <\/p>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings\/speech<\/a>\u00a0<\/p>\n\n\n\n

10 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Transcription<\/strong> <\/h3>\n\n\n\n

Transcription l\u00e0 t\u00e1c v\u1ee5 chuy\u1ec3n gi\u1ecdng th\u00e0nh v\u0103n b\u1ea3n. Nh\u00f3m model n\u00e0y ph\u00f9 h\u1ee3p cho ghi \u00e2m cu\u1ed9c h\u1ecdp, ph\u1ee5 \u0111\u1ec1 video, voice note, ph\u00e2n t\u00edch cu\u1ed9c g\u1ecdi, podcast, t\u1ed5ng \u0111\u00e0i v\u00e0 t\u00ecm ki\u1ebfm trong d\u1eef li\u1ec7u \u00e2m thanh. OpenRouter m\u00f4 t\u1ea3 nh\u00f3m speech-to-text model l\u00e0 c\u00e1c model chuy\u1ec3n \u00e2m thanh th\u00e0nh v\u0103n b\u1ea3n ph\u1ee5c v\u1ee5 transcription, captions, meeting summaries, call analysis v\u00e0 speech-driven applications. <\/p>\n\n\n\n

X\u1ebfp h\u1ea1ng<\/th>Model AI<\/th>Nh\u00e0 ph\u00e1t tri\u1ec3n<\/th>L\u01b0\u1ee3t y\u00eau c\u1ea7u<\/th>Xu h\u01b0\u1edbng<\/th><\/tr><\/thead>
1<\/td>Whisper Large V3<\/td>OpenAI<\/td>3,76M<\/td>\u2191 6%<\/td><\/tr>
2<\/td>Whisper Large V3 Turbo<\/td>OpenAI<\/td>1,07M<\/td>\u2191 129%<\/td><\/tr>
3<\/td>GPT-4o Mini Transcribe<\/td>OpenAI<\/td>801K<\/td>\u2191 1%<\/td><\/tr>
4<\/td>Qwen3 ASR Flash<\/td>Qwen<\/td>196K<\/td>\u2193 33%<\/td><\/tr>
5<\/td>Parakeet TDT 0.6B v3<\/td>NVIDIA<\/td>172K<\/td>\u2193 94%<\/td><\/tr>
6<\/td>Whisper 1<\/td>OpenAI<\/td>79K<\/td>\u2191 19%<\/td><\/tr>
7<\/td>Chirp 3<\/td>Google<\/td>70K<\/td>\u2191 88%<\/td><\/tr>
8<\/td>Voxtral Mini Transcribe<\/td>Mistral AI<\/td>65K<\/td>\u2191 43%<\/td><\/tr>
9<\/td>GPT-4o Transcribe<\/td>OpenAI<\/td>59K<\/td>\u2193 13%<\/td><\/tr>
10<\/td>MAI-Transcribe 1.5<\/td>Microsoft<\/td>21K<\/td>\u2193 40%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\ud83d\udc49 C\u1eadp nh\u1eadt m\u1edbi nh\u1ea5t t\u1ea1i: https:\/\/openrouter.ai\/rankings\/transcription<\/a>\u00a0<\/p>\n\n\n

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10 model AI t\u1ed1t nh\u1ea5t cho t\u00e1c v\u1ee5 Transcription<\/strong>\u00a0<\/figcaption><\/figure>\n<\/div>\n\n\n

G\u1ee3i \u00fd ch\u1ecdn model AI ph\u00f9 h\u1ee3p theo nhu c\u1ea7u th\u1ef1c t\u1ebf<\/strong>\u00a0<\/h2>\n\n\n\n
Nhu c\u1ea7u<\/strong><\/td>Nh\u00f3m model n\u00ean \u01b0u ti\u00ean<\/strong><\/td>G\u1ee3i \u00fd l\u1ef1a ch\u1ecdn<\/strong><\/td><\/tr>
Vi\u1ebft n\u1ed9i dung, chatbot, ph\u00e2n t\u00edch v\u0103n b\u1ea3n<\/td>Text<\/td>DeepSeek V4 Flash, MiMo-V2.5, MiniMax M3, Claude Opus 4.8<\/td><\/tr>
L\u1eadp tr\u00ecnh, AI Agent, tool use<\/td>Text<\/td>GLM 5.2, DeepSeek V4 Pro, Step 3.7 Flash, MiniMax M3<\/td><\/tr>
T\u1ea1o \u1ea3nh qu\u1ea3ng c\u00e1o, poster, \u1ea3nh s\u1ea3n ph\u1ea9m<\/td>Image<\/td>Nano Banana, Seedream 4.5, Grok Imagine Image Quality, FLUX.2<\/td><\/tr>
X\u00e2y d\u1ef1ng RAG, t\u00ecm ki\u1ebfm t\u00e0i li\u1ec7u<\/td>Embedding + Rerank<\/td>Text Embedding 3 Small, Qwen3 Embedding 8B, bge-m3, Cohere Rerank<\/td><\/tr>
T\u1ea1o video ng\u1eafn t\u1eeb prompt ho\u1eb7c \u1ea3nh<\/td>Video<\/td>HappyHorse, Grok Imagine Video, Kling, Veo, Seedance<\/td><\/tr>
T\u1ea1o gi\u1ecdng \u0111\u1ecdc AI<\/td>Speech<\/td>Gemini 3.1 Flash TTS, Kokoro 82M, Grok Voice TTS, MAI-Voice-2<\/td><\/tr>
Chuy\u1ec3n audio th\u00e0nh v\u0103n b\u1ea3n<\/td>Transcription<\/td>GPT-4o Mini Transcribe, GPT-4o Transcribe, Voxtral Mini Transcribe, Whisper<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

K\u1ebft lu\u1eadn<\/strong><\/h2>\n\n\n\n

B\u1ea3ng x\u1ebfp h\u1ea1ng c\u00e1c model AI t\u1ed1t nh\u1ea5t tr\u00ean OpenRouter <\/strong>cho th\u1ea5y m\u1ed7i t\u00e1c v\u1ee5 \u0111ang c\u00f3 m\u1ed9t nh\u00f3m model d\u1eabn \u0111\u1ea7u ri\u00eang. Tuy nhi\u00ean, b\u1ea3ng x\u1ebfp h\u1ea1ng n\u00e0y kh\u00f4ng n\u00ean l\u00e0 ti\u00eau ch\u00ed duy nh\u1ea5t. Khi ch\u1ecdn model AI, b\u1ea1n n\u00ean ch\u1ea1y th\u1eed v\u1edbi d\u1eef li\u1ec7u th\u1eadt, so s\u00e1nh ch\u1ea5t l\u01b0\u1ee3ng \u0111\u1ea7u ra, \u0111o l\u01b0\u1eddng chi ph\u00ed, ki\u1ec3m tra \u0111\u1ed9 tr\u1ec5 v\u00e0 \u0111\u00e1nh gi\u00e1 m\u1ee9c \u1ed5n \u0111\u1ecbnh qua nhi\u1ec1u l\u1ea7n g\u1ecdi API. <\/p>\n\n\n\n

Chi\u1ebfn l\u01b0\u1ee3c t\u1ed1t nh\u1ea5t l\u00e0 d\u00f9ng nhi\u1ec1u model theo t\u1eebng t\u1ea7ng: model nhanh cho t\u00e1c v\u1ee5 \u0111\u01a1n gi\u1ea3n, model m\u1ea1nh cho t\u00e1c v\u1ee5 kh\u00f3, embedding model cho truy h\u1ed3i d\u1eef li\u1ec7u v\u00e0 rerank model \u0111\u1ec3 t\u0103ng \u0111\u1ed9 ch\u00ednh x\u00e1c trong RAG.<\/p>\n\n\n\n

Nh\u1eefng c\u00e2u h\u1ecfi th\u01b0\u1eddng g\u1eb7p<\/strong><\/h2>\n\n\n\t\t\n\t\t\t\t

C\u00f3 n\u00ean ch\u1ecdn model \u0111\u1eaft nh\u1ea5t \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o ch\u1ea5t l\u01b0\u1ee3ng t\u1ed1t nh\u1ea5t kh\u00f4ng?\u00a0<\/h2>\t\t\t\t
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Kh\u00f4ng nh\u1ea5t thi\u1ebft. V\u1edbi ph\u1ea7n l\u1edbn t\u00e1c v\u1ee5 h\u1eb1ng ng\u00e0y nh\u01b0 tr\u1ea3 l\u1eddi c\u00e2u h\u1ecfi, t\u00f3m t\u1eaft v\u0103n b\u1ea3n hay t\u1ea1o \u1ea3nh minh h\u1ecda th\u00f4ng th\u01b0\u1eddng, c\u00e1c model t\u1ea7m trung ho\u1eb7c phi\u00ean b\u1ea3n r\u00fat g\u1ecdn th\u01b0\u1eddng \u0111\u00e3 \u0111\u00e1p \u1ee9ng \u0111\u1ee7 t\u1ed1t v\u1edbi chi ph\u00ed th\u1ea5p h\u01a1n nhi\u1ec1u. Ch\u1ec9 n\u00ean d\u00f9ng model cao c\u1ea5p nh\u1ea5t cho c\u00e1c t\u00e1c v\u1ee5 \u0111\u00f2i h\u1ecfi \u0111\u1ed9 ch\u00ednh x\u00e1c cao nh\u01b0 ph\u00e2n t\u00edch ph\u00e1p l\u00fd, t\u00e0i ch\u00ednh ho\u1eb7c r\u00e0 so\u00e1t m\u00e3 ngu\u1ed3n quan tr\u1ecdng.\u00a0<\/p>\n\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\n\t\t\t\t

B\u1ea3ng x\u1ebfp h\u1ea1ng n\u00e0y c\u00f3 \u0111\u01b0\u1ee3c c\u1eadp nh\u1eadt th\u01b0\u1eddng xuy\u00ean kh\u00f4ng?\u00a0<\/h2>\t\t\t\t
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C\u00f3. Trang x\u1ebfp h\u1ea1ng g\u1ed1c c\u1eadp nh\u1eadt g\u1ea7n nh\u01b0 h\u1eb1ng ng\u00e0y ho\u1eb7c h\u1eb1ng tu\u1ea7n d\u1ef1a tr\u00ean l\u01b0u l\u01b0\u1ee3ng th\u1ef1c t\u1ebf, v\u00ec v\u1eady th\u1ee9 h\u1ea1ng c\u00f3 th\u1ec3 thay \u0111\u1ed5i kh\u00e1 nhanh, \u0111\u1eb7c bi\u1ec7t khi c\u00f3 model m\u1edbi ra m\u1eaft k\u00e8m m\u1ee9c gi\u00e1 h\u1ea5p d\u1eabn ho\u1eb7c ch\u01b0\u01a1ng tr\u00ecnh mi\u1ec5n ph\u00ed gi\u1edbi h\u1ea1n th\u1eddi gian.\u00a0<\/p>\n\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\n\t\t\t\t

C\u00f3 n\u00ean d\u00f9ng m\u1ed9t model AI duy nh\u1ea5t cho to\u00e0n b\u1ed9 h\u1ec7 th\u1ed1ng kh\u00f4ng?<\/h2>\t\t\t\t
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Kh\u00f4ng n\u00ean trong \u0111a s\u1ed1 tr\u01b0\u1eddng h\u1ee3p. M\u1ed9t h\u1ec7 th\u1ed1ng AI hi\u1ec7u qu\u1ea3 th\u01b0\u1eddng d\u00f9ng nhi\u1ec1u model theo t\u1eebng t\u00e1c v\u1ee5: text model cho tr\u1ea3 l\u1eddi, embedding model cho t\u00ecm ki\u1ebfm, rerank model cho l\u1ecdc k\u1ebft qu\u1ea3, image model cho t\u1ea1o \u1ea3nh, speech model cho gi\u1ecdng \u0111\u1ecdc v\u00e0 transcription model cho x\u1eed l\u00fd audio.<\/p>\n\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\n\t\t\t\t

S\u1ef1 kh\u00e1c bi\u1ec7t gi\u1eefa embeddings v\u00e0 rerank l\u00e0 g\u00ec?\u00a0<\/h2>\t\t\t\t
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Embeddings chuy\u1ec3n v\u0103n b\u1ea3n th\u00e0nh vector s\u1ed1 \u0111\u1ec3 t\u00ecm ki\u1ebfm nhanh trong m\u1ed9t t\u1eadp d\u1eef li\u1ec7u l\u1edbn \u1edf b\u01b0\u1edbc \u0111\u1ea7u ti\u00ean, c\u00f2n rerank l\u00e0 b\u01b0\u1edbc x\u1eed l\u00fd th\u1ee9 hai, gi\u00fap s\u1eafp x\u1ebfp l\u1ea1i danh s\u00e1ch k\u1ebft qu\u1ea3 \u0111\u00e3 t\u00ecm \u0111\u01b0\u1ee3c theo m\u1ee9c \u0111\u1ed9 li\u00ean quan ch\u00ednh x\u00e1c h\u01a1n v\u1edbi c\u00e2u h\u1ecfi g\u1ed1c. Hai c\u00f4ng ngh\u1ec7 th\u01b0\u1eddng \u0111\u01b0\u1ee3c d\u00f9ng k\u1ebft h\u1ee3p trong c\u00f9ng m\u1ed9t h\u1ec7 th\u1ed1ng t\u00ecm ki\u1ebfm ho\u1eb7c RAG \u0111\u1ec3 \u0111\u1ea1t \u0111\u1ed9 ch\u00ednh x\u00e1c cao nh\u1ea5t.\u00a0<\/p>\n\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/section>\n\t\t\n