{"id":128750,"date":"2026-07-22T13:19:25","date_gmt":"2026-07-22T06:19:25","guid":{"rendered":"https:\/\/tino.vn\/blog\/?p=128750"},"modified":"2026-07-22T13:22:24","modified_gmt":"2026-07-22T06:22:24","slug":"laguna-m-1-la-gi","status":"publish","type":"post","link":"https:\/\/tino.vn\/blog\/laguna-m-1-la-gi\/","title":{"rendered":"Laguna M.1 l\u00e0 g\u00ec? Gi\u1ea3i m\u00e3 m\u00f4 h\u00ecnh AI Coding th\u1ebf h\u1ec7 m\u1edbi c\u1ee7a Poolside\u00a0"},"content":{"rendered":"\n

Trong l\u00e0n s\u00f3ng b\u00f9ng n\u1ed5 c\u1ee7a c\u00e1c m\u00f4 h\u00ecnh AI chuy\u00ean v\u1ec1 l\u1eadp tr\u00ecnh, c\u00e1i t\u00ean Laguna M.1 \u0111ang thu h\u00fat s\u1ef1 ch\u00fa \u00fd c\u1ee7a gi\u1edbi c\u00f4ng ngh\u1ec7 nh\u1edd ki\u1ebfn tr\u00fac Mixture-of-Experts quy m\u00f4 l\u1edbn c\u00f9ng kh\u1ea3 n\u0103ng x\u1eed l\u00fd t\u00e1c v\u1ee5 l\u1eadp tr\u00ecnh ph\u1ee9c t\u1ea1p k\u00e9o d\u00e0i nhi\u1ec1u b\u01b0\u1edbc. V\u1eady Laguna M.1 l\u00e0 g\u00ec, ai \u0111\u1ee9ng sau ph\u00e1t tri\u1ec3n v\u00e0 m\u00f4 h\u00ecnh n\u00e0y mang l\u1ea1i gi\u00e1 tr\u1ecb th\u1ef1c t\u1ebf n\u00e0o cho l\u1eadp tr\u00ecnh vi\u00ean? C\u00f9ng Tino kh\u00e1m ph\u00e1 nh\u00e9!<\/strong><\/p>\n\n\n\n

T\u1ed5ng quan v\u1ec1 Laguna M.1<\/strong><\/h2>\n\n\n\n

Laguna M.1 l\u00e0 g\u00ec?<\/strong><\/h3>\n\n\n\n

Laguna M.1 l\u00e0 m\u1ed9t m\u00f4 h\u00ecnh ng\u00f4n ng\u1eef l\u1edbn \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n b\u1edfi Poolside, chuy\u00ean ph\u1ee5c v\u1ee5 l\u1eadp tr\u00ecnh t\u1ef1 \u0111\u1ed9ng v\u00e0 c\u00e1c nhi\u1ec7m v\u1ee5 k\u1ef9 thu\u1eadt ph\u1ea7n m\u1ec1m nhi\u1ec1u b\u01b0\u1edbc. M\u00f4 h\u00ecnh \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 l\u00e0m vi\u1ec7c trong m\u00f4i tr\u01b0\u1eddng c\u00f3 c\u00f4ng c\u1ee5, ch\u1eb3ng h\u1ea1n nh\u01b0 tr\u00ecnh ch\u1ec9nh s\u1eeda m\u00e3 ngu\u1ed3n, terminal, h\u1ec7 th\u1ed1ng ki\u1ec3m th\u1eed v\u00e0 kho m\u00e3.<\/p>\n\n\n\n

Thay v\u00ec ch\u1ec9 tr\u1ea3 l\u1eddi m\u1ed9t c\u00e2u h\u1ecfi r\u1ed3i d\u1eebng l\u1ea1i, Laguna M.1 c\u00f3 th\u1ec3 l\u1eadp k\u1ebf ho\u1ea1ch, \u0111\u1ecdc c\u1ea5u tr\u00fac d\u1ef1 \u00e1n, t\u00ecm t\u1ec7p li\u00ean quan, ch\u1ec9nh s\u1eeda code, ch\u1ea1y ki\u1ec3m th\u1eed v\u00e0 ti\u1ebfp t\u1ee5c \u0111i\u1ec1u ch\u1ec9nh cho \u0111\u1ebfn khi \u0111\u1ea1t k\u1ebft qu\u1ea3 ph\u00f9 h\u1ee3p. \u0110\u00e2y ch\u00ednh l\u00e0 \u0111\u1eb7c \u0111i\u1ec3m c\u1ed1t l\u00f5i c\u1ee7a agentic coding<\/strong>.<\/p>\n\n\n

\n
\"Laguna
Laguna M.1 l\u00e0 g\u00ec?<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n

Laguna M.1 s\u1eed d\u1ee5ng ki\u1ebfn tr\u00fac Mixture-of-Experts v\u1edbi 225,8 t\u1ef7 tham s\u1ed1 t\u1ed5ng v\u00e0 kho\u1ea3ng 23,4 t\u1ef7 tham s\u1ed1 \u0111\u01b0\u1ee3c k\u00edch ho\u1ea1t cho m\u1ed7i token. Model card hi\u1ec7n t\u1ea1i c\u1ee7a Poolside ghi nh\u1eadn c\u1eeda s\u1ed5 ng\u1eef c\u1ea3nh 262.144 token, h\u1ed7 tr\u1ee3 suy lu\u1eadn g\u1ed1c, g\u1ecdi c\u00f4ng c\u1ee5 v\u00e0 gi\u1ea5y ph\u00e9p Apache 2.0.<\/p>\n\n\n\n

Laguna M.1 do ai ph\u00e1t tri\u1ec3n?<\/strong><\/h3>\n\n\n\n

Laguna M.1 \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n b\u1edfi Poolside<\/strong> – m\u1ed9t c\u00f4ng ty AI t\u1eadp trung v\u00e0o c\u00e1c foundation model d\u00e0nh cho k\u1ef9 thu\u1eadt ph\u1ea7n m\u1ec1m. Poolside gi\u1edbi thi\u1ec7u Laguna M.1 c\u00f9ng Laguna XS.2 v\u00e0o ng\u00e0y 28\/4\/2026, sau \u0111\u00f3 c\u00f4ng b\u1ed1 b\u00e1o c\u00e1o k\u1ef9 thu\u1eadt chi ti\u1ebft v\u00e0 m\u1edf tr\u1ecdng s\u1ed1 Laguna M.1 tr\u00ean Hugging Face.<\/p>\n\n\n\n

Poolside cho bi\u1ebft Laguna M.1 \u0111\u01b0\u1ee3c hu\u1ea5n luy\u1ec7n t\u1eeb \u0111\u1ea7u tr\u00ean h\u01a1n 30 ngh\u00ecn t\u1ef7 token b\u1eb1ng 6.144 GPU NVIDIA Hopper k\u1ebft n\u1ed1i v\u1edbi nhau. To\u00e0n b\u1ed9 qu\u00e1 tr\u00ecnh g\u1ed3m thu th\u1eadp d\u1eef li\u1ec7u, ti\u1ec1n hu\u1ea5n luy\u1ec7n, h\u1eadu hu\u1ea5n luy\u1ec7n, \u0111\u00e1nh gi\u00e1 v\u00e0 reinforcement learning \u0111\u01b0\u1ee3c t\u1ed5 ch\u1ee9c trong h\u1ec7 th\u1ed1ng n\u1ed9i b\u1ed9 mang t\u00ean Model Factory<\/strong>.<\/p>\n\n\n

\n
\"Laguna
Laguna M.1 do ai ph\u00e1t tri\u1ec3n?<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n

C\u1eadp nh\u1eadt \u0111\u1ebfn ng\u00e0y 22\/7\/2026:<\/strong> Laguna M.1 v\u1eabn l\u00e0 model M-class 225B-A23B \u0111\u01b0\u1ee3c Poolside h\u1ed7 tr\u1ee3 v\u00e0 ph\u00e1t h\u00e0nh tr\u1ecdng s\u1ed1 m\u1edf. Tuy nhi\u00ean, \u0111\u00e2y kh\u00f4ng c\u00f2n l\u00e0 b\u1ea3n ph\u00e1t h\u00e0nh m\u1edbi nh\u1ea5t trong gia \u0111\u00ecnh Laguna. Poolside \u0111\u00e3 gi\u1edbi thi\u1ec7u Laguna S 2.1<\/strong> v\u00e0o ng\u00e0y 21\/7\/2026, b\u00ean c\u1ea1nh Laguna XS 2.1<\/strong> d\u00e0nh cho nhu c\u1ea7u nh\u1eb9 h\u01a1n.<\/p>\n\n\n\n

Th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt n\u1ed5i b\u1eadt c\u1ee7a Laguna M.1<\/strong><\/h2>\n\n\n\n

Ki\u1ebfn tr\u00fac Mixture-of-Experts (MoE)<\/strong><\/h3>\n\n\n\n

Mixture-of-Experts, th\u01b0\u1eddng vi\u1ebft t\u1eaft l\u00e0 MoE, c\u00f3 th\u1ec3 hi\u1ec3u \u0111\u01a1n gi\u1ea3n nh\u01b0 m\u1ed9t nh\u00f3m chuy\u00ean gia c\u00f9ng l\u00e0m vi\u1ec7c. M\u1ed7i chuy\u00ean gia ph\u1ee5 tr\u00e1ch m\u1ed9t nh\u00f3m m\u1eabu ho\u1eb7c k\u1ef9 n\u0103ng kh\u00e1c nhau. Khi x\u1eed l\u00fd m\u1ed9t token, h\u1ec7 th\u1ed1ng ch\u1ec9 k\u00edch ho\u1ea1t nh\u1eefng chuy\u00ean gia ph\u00f9 h\u1ee3p thay v\u00ec huy \u0111\u1ed9ng to\u00e0n b\u1ed9 tham s\u1ed1.<\/p>\n\n\n\n

Laguna M.1 c\u00f3 225,8 t\u1ef7 tham s\u1ed1 t\u1ed5ng nh\u01b0ng ch\u1ec9 k\u00edch ho\u1ea1t kho\u1ea3ng 23,4 t\u1ef7 tham s\u1ed1 cho m\u1ed7i token. C\u00e1ch thi\u1ebft k\u1ebf n\u00e0y gi\u00fap model duy tr\u00ec n\u0103ng l\u1ef1c l\u1edbn trong khi gi\u1ea3m l\u01b0\u1ee3ng t\u00ednh to\u00e1n so v\u1edbi m\u1ed9t m\u00f4 h\u00ecnh dense c\u00f3 c\u00f9ng t\u1ed5ng s\u1ed1 tham s\u1ed1.<\/p>\n\n\n\n

V\u1ec1 c\u1ea5u tr\u00fac, Laguna M.1 c\u00f3 70 l\u1edbp Transformer. Ba l\u1edbp \u0111\u1ea7u l\u00e0 dense SwiGLU, 67 l\u1edbp c\u00f2n l\u1ea1i s\u1eed d\u1ee5ng MoE v\u1edbi 256 chuy\u00ean gia v\u00e0 c\u01a1 ch\u1ebf ch\u1ecdn 16 chuy\u00ean gia cho m\u1ed7i token. T\u1ea5t c\u1ea3 c\u00e1c l\u1edbp \u0111\u1ec1u d\u00f9ng global attention.<\/p>\n\n\n\n

C\u1eeda s\u1ed5 ng\u1eef c\u1ea3nh 256K token<\/strong><\/h3>\n\n\n\n

T\u1eeb cu\u1ed1i th\u00e1ng 5 n\u0103m 2026, Poolside n\u00e2ng c\u1eeda s\u1ed5 ng\u1eef c\u1ea3nh c\u1ee7a Laguna M.1 l\u00ean 256.000 token, \u0111\u1ed3ng th\u1eddi c\u1ea3i thi\u1ec7n \u0111i\u1ec3m s\u1ed1 tr\u00ean c\u00e1c b\u00e0i ki\u1ec3m tra nh\u01b0 SWE-bench Verified, SWE-Bench Pro v\u00e0 Terminal-Bench 2.0. C\u1eeda s\u1ed5 ng\u1eef c\u1ea3nh l\u1edbn cho ph\u00e9p m\u00f4 h\u00ecnh ghi nh\u1edb to\u00e0n b\u1ed9 m\u1ed9t d\u1ef1 \u00e1n ph\u1ea7n m\u1ec1m c\u00f3 quy m\u00f4 v\u1eeba v\u00e0 nh\u1ecf trong m\u1ed9t l\u01b0\u1ee3t x\u1eed l\u00fd duy nh\u1ea5t, h\u1ea1n ch\u1ebf t\u00ecnh tr\u1ea1ng qu\u00ean ng\u1eef c\u1ea3nh khi l\u00e0m vi\u1ec7c d\u00e0i h\u01a1i.<\/p>\n\n\n

\n
\"Th\u00f4ng
Th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt n\u1ed5i b\u1eadt c\u1ee7a Laguna M.1<\/strong><\/figcaption><\/figure>\n<\/div>\n\n\n

Kh\u1ea3 n\u0103ng suy lu\u1eadn t\u00edch h\u1ee3p<\/strong><\/h3>\n\n\n\n

Laguna M.1 h\u1ed7 tr\u1ee3 suy lu\u1eadn g\u1ed1c v\u00e0 c\u00f3 th\u1ec3 suy lu\u1eadn xen k\u1ebd gi\u1eefa c\u00e1c l\u1ea7n g\u1ecdi c\u00f4ng c\u1ee5. Trong m\u1ed9t nhi\u1ec7m v\u1ee5 s\u1eeda l\u1ed7i, model c\u00f3 th\u1ec3 \u0111\u1ecdc t\u1ec7p, h\u00ecnh th\u00e0nh gi\u1ea3 thuy\u1ebft, ch\u1ea1y l\u1ec7nh, xem k\u1ebft qu\u1ea3 r\u1ed3i c\u1eadp nh\u1eadt h\u01b0\u1edbng x\u1eed l\u00fd.<\/p>\n\n\n\n

Poolside c\u0169ng cho ph\u00e9p b\u1eadt ho\u1eb7c t\u1eaft ch\u1ebf \u0111\u1ed9 thinking theo t\u1eebng y\u00eau c\u1ea7u. Khi th\u1ef1c hi\u1ec7n c\u00f4ng vi\u1ec7c d\u00e0i v\u00e0 ph\u1ee9c t\u1ea1p, ch\u1ebf \u0111\u1ed9 suy lu\u1eadn th\u01b0\u1eddng ph\u00f9 h\u1ee3p h\u01a1n. V\u1edbi c\u00e2u h\u1ecfi \u0111\u01a1n gi\u1ea3n ho\u1eb7c y\u00eau c\u1ea7u ph\u1ea3n h\u1ed3i nhanh, ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 t\u1eaft ch\u1ebf \u0111\u1ed9 n\u00e0y \u0111\u1ec3 gi\u1ea3m \u0111\u1ed9 tr\u1ec5 v\u00e0 l\u01b0\u1ee3ng token \u0111\u1ea7u ra.<\/p>\n\n\n\n

Xem th\u00eam: Top 10+ m\u00f4 h\u00ecnh LLM Open Source t\u1ed1t nh\u1ea5t<\/a><\/p>\n\n\n\n

Quy tr\u00ecnh hu\u1ea5n luy\u1ec7n Model Factory<\/strong><\/h3>\n\n\n\n

Model Factory l\u00e0 c\u00e1ch Poolside t\u1ed5 ch\u1ee9c to\u00e0n b\u1ed9 v\u00f2ng \u0111\u1eddi ph\u00e1t tri\u1ec3n model th\u00e0nh m\u1ed9t d\u00e2y chuy\u1ec1n th\u1ed1ng nh\u1ea5t. D\u1eef li\u1ec7u, m\u00e3 hu\u1ea5n luy\u1ec7n, phi\u00ean b\u1ea3n checkpoint, h\u1ec7 th\u1ed1ng \u0111\u00e1nh gi\u00e1 v\u00e0 h\u1ea1 t\u1ea7ng suy lu\u1eadn \u0111\u1ec1u \u0111\u01b0\u1ee3c qu\u1ea3n l\u00fd c\u00f9ng nhau.<\/p>\n\n\n\n

Laguna M.1 tr\u1ea3i qua ti\u1ec1n hu\u1ea5n luy\u1ec7n, h\u1eadu hu\u1ea5n luy\u1ec7n v\u00e0 reinforcement learning. Trong giai \u0111o\u1ea1n reinforcement learning, model l\u00e0m vi\u1ec7c v\u1edbi c\u00e1c b\u00e0i to\u00e1n k\u1ef9 thu\u1eadt ph\u1ea7n m\u1ec1m th\u1ef1c t\u1ebf trong m\u00f4i tr\u01b0\u1eddng sandbox: \u0111\u1ecdc t\u1ec7p, ch\u1ea1y terminal, ch\u1ec9nh s\u1eeda code v\u00e0 nh\u1eadn \u0111i\u1ec3m d\u1ef1a tr\u00ean k\u1ebft qu\u1ea3.<\/p>\n\n\n\n

Poolside s\u1eed d\u1ee5ng h\u1ec7 th\u1ed1ng rollout b\u1ea5t \u0111\u1ed3ng b\u1ed9 \u0111\u1ec3 ph\u1ee5c v\u1ee5 c\u00e1c nhi\u1ec7m v\u1ee5 d\u00e0i m\u00e0 kh\u00f4ng khi\u1ebfn qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n ph\u1ea3i ch\u1edd to\u00e0n b\u1ed9 phi\u00ean l\u00e0m vi\u1ec7c k\u1ebft th\u00fac.<\/p>\n\n\n\n

B\u1ea3ng th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt c\u1ee7a Laguna M.1:<\/span><\/strong><\/p>\n\n\n\n

H\u1ea1ng m\u1ee5c<\/th>Th\u00f4ng tin<\/th><\/tr><\/thead>
Nh\u00e0 ph\u00e1t tri\u1ec3n<\/td>Poolside<\/td><\/tr>
Th\u1eddi \u0111i\u1ec3m c\u00f4ng b\u1ed1 \u0111\u1ea7u ti\u00ean<\/td>28\/4\/2026<\/td><\/tr>
Lo\u1ea1i m\u00f4 h\u00ecnh<\/td>Mixture-of-Experts<\/td><\/tr>
T\u1ed5ng tham s\u1ed1<\/td>225,8 t\u1ef7<\/td><\/tr>
Tham s\u1ed1 k\u00edch ho\u1ea1t m\u1ed7i token<\/td>23,4 t\u1ef7<\/td><\/tr>
C\u1ea5u tr\u00fac r\u00fat g\u1ecdn<\/td>225B-A23B<\/td><\/tr>
S\u1ed1 l\u1edbp<\/td>70 l\u1edbp<\/td><\/tr>
S\u1ed1 chuy\u00ean gia<\/td>256 chuy\u00ean gia<\/td><\/tr>
C\u01a1 ch\u1ebf \u0111\u1ecbnh tuy\u1ebfn<\/td>Ch\u1ecdn 16 chuy\u00ean gia m\u1ed7i token<\/td><\/tr>
C\u1eeda s\u1ed5 ng\u1eef c\u1ea3nh<\/td>262.144 token<\/td><\/tr>
Ph\u01b0\u01a1ng th\u1ee9c \u0111\u1ea7u v\u00e0o<\/td>V\u0103n b\u1ea3n<\/td><\/tr>
Ph\u01b0\u01a1ng th\u1ee9c \u0111\u1ea7u ra<\/td>V\u0103n b\u1ea3n<\/td><\/tr>
Suy lu\u1eadn<\/td>C\u00f3, h\u1ed7 tr\u1ee3 b\u1eadt ho\u1eb7c t\u1eaft<\/td><\/tr>
G\u1ecdi c\u00f4ng c\u1ee5<\/td>C\u00f3<\/td><\/tr>
Ch\u1ebf \u0111\u1ed9<\/td>Agentic v\u00e0 Chat<\/td><\/tr>
Checkpoint<\/td>BF16, FP8 v\u00e0 NVFP4<\/td><\/tr>
Gi\u1ea5y ph\u00e9p<\/td>Apache 2.0<\/td><\/tr>
Framework h\u1ed7 tr\u1ee3<\/td>vLLM, SGLang, Transformers v\u00e0 TensorRT-LLM<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

L\u01b0u \u00fd:<\/strong> C\u00e1c th\u00f4ng s\u1ed1 tr\u00ean \u0111\u01b0\u1ee3c t\u1ed5ng h\u1ee3p t\u1eeb model card, t\u00e0i li\u1ec7u API v\u00e0 b\u00e1o c\u00e1o k\u1ef9 thu\u1eadt ch\u00ednh th\u1ee9c. Poolside hi\u1ec7n ghi nh\u1eadn vLLM t\u1eeb phi\u00ean b\u1ea3n 0.21.0 v\u00e0 Transformers t\u1eeb phi\u00ean b\u1ea3n 5.7.0 c\u00f3 h\u1ed7 tr\u1ee3 Laguna M.1. <\/p>\n\n\n\n

Hi\u1ec7u n\u0103ng benchmark c\u1ee7a Laguna M.1<\/strong><\/h2>\n\n\n\n

Model card hi\u1ec7n t\u1ea1i c\u1ee7a Poolside c\u00f4ng b\u1ed1 c\u00e1c k\u1ebft qu\u1ea3 sau:<\/p>\n\n\n\n

Benchmark<\/th>\u0110i\u1ec3m Laguna M.1<\/th>N\u1ed9i dung \u0111\u00e1nh gi\u00e1<\/th><\/tr><\/thead>
SWE-bench Verified<\/td>74,6%<\/td>S\u1eeda l\u1ed7i th\u1ef1c t\u1ebf trong repository m\u00e3 ngu\u1ed3n<\/td><\/tr>
SWE-bench Multilingual<\/td>63,1%<\/td>X\u1eed l\u00fd l\u1ed7i ph\u1ea7n m\u1ec1m \u1edf nhi\u1ec1u ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh<\/td><\/tr>
SWE-Bench Pro<\/td>49,2%<\/td>Nhi\u1ec7m v\u1ee5 k\u1ef9 thu\u1eadt ph\u1ea7n m\u1ec1m kh\u00f3 v\u00e0 g\u1ea7n th\u1ef1c t\u1ebf h\u01a1n<\/td><\/tr>
Terminal-Bench 2.0<\/td>45,8%<\/td>Ho\u00e0n th\u00e0nh t\u00e1c v\u1ee5 d\u00e0i th\u00f4ng qua terminal<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

C\u00e1c k\u1ebft qu\u1ea3 c\u1eadp nh\u1eadt cao h\u01a1n s\u1ed1 li\u1ec7u trong ng\u00e0y c\u00f4ng b\u1ed1 \u0111\u1ea7u ti\u00ean. Poolside \u0111\u00e1nh gi\u00e1 Laguna M.1 c\u00f3 kh\u1ea3 n\u0103ng c\u1ea1nh tranh v\u1edbi nhi\u1ec1u open-weight model m\u1ea1nh trong c\u00f9ng nh\u00f3m k\u00edch th\u01b0\u1edbc, nh\u01b0ng Laguna M.1 kh\u00f4ng d\u1eabn \u0111\u1ea7u m\u1ecdi benchmark. DeepSeek-V4 Flash, Qwen3.5 v\u00e0 m\u1ed9t s\u1ed1 model \u0111\u00f3ng v\u1eabn \u0111\u1ea1t \u0111i\u1ec3m cao h\u01a1n \u1edf m\u1ed9t s\u1ed1 b\u00e0i ki\u1ec3m tra.<\/p>\n\n\n\n

Benchmark agent ph\u1ee5 thu\u1ed9c \u0111\u00e1ng k\u1ec3 v\u00e0o agent harness, s\u1ed1 b\u01b0\u1edbc t\u1ed1i \u0111a, t\u00e0i nguy\u00ean sandbox, tham s\u1ed1 l\u1ea5y m\u1eabu v\u00e0 c\u00e1ch s\u1eeda l\u1ed7i h\u1ea1 t\u1ea7ng c\u1ee7a b\u1ed9 ki\u1ec3m th\u1eed. V\u00ec v\u1eady, b\u1ea1n v\u1eabn n\u00ean xem \u0111i\u1ec3m benchmark nh\u01b0 m\u1ed9t t\u00edn hi\u1ec7u tham kh\u1ea3o thay v\u00ec k\u1ebft lu\u1eadn tuy\u1ec7t \u0111\u1ed1i v\u1ec1 hi\u1ec7u qu\u1ea3 trong d\u1ef1 \u00e1n th\u1ef1c t\u1ebf.<\/p>\n\n\n\n

Poolside cho bi\u1ebft c\u00e1c b\u00e0i \u0111\u00e1nh gi\u00e1 Laguna M.1 \u0111\u01b0\u1ee3c ch\u1ea1y v\u1edbi t\u1ed1i \u0111a 500 b\u01b0\u1edbc trong m\u00f4i tr\u01b0\u1eddng sandbox.<\/p>\n\n\n\n

\u01afu \u0111i\u1ec3m v\u00e0 h\u1ea1n ch\u1ebf c\u1ee7a Laguna M.1<\/strong><\/h2>\n\n\n\n

\u01afu \u0111i\u1ec3m c\u1ee7a Laguna M.1<\/strong><\/h3>\n\n\n\n