{"id":1279,"date":"2026-06-23T14:45:04","date_gmt":"2026-06-23T14:45:04","guid":{"rendered":"https:\/\/convly.ai\/?p=1279"},"modified":"2026-06-23T14:45:04","modified_gmt":"2026-06-23T14:45:04","slug":"gemma-3-27b-vs-llama-3-3-70b","status":"publish","type":"post","link":"https:\/\/convly.ai\/fr\/gemma-3-27b-vs-llama-3-3-70b\/","title":{"rendered":"Gemma 3 27B contre Llama 3.3 70B : sp\u00e9cifications, tarifs et choix (2026)"},"content":{"rendered":"

Gemma 3 27B<\/strong> contre Llama 3.3 70B<\/strong> \u2014 La version efficace de 27 milliards de param\u00e8tres de Google compar\u00e9e \u00e0 celle de 70 milliards de param\u00e8tres de Meta. Le tableau comparatif complet ci-dessous pr\u00e9sente les sp\u00e9cifications techniques, les tarifs d\u2019API, la taille de la fen\u00eatre de contexte, les exigences mat\u00e9rielles locales et une recommandation claire, fond\u00e9e sur des donn\u00e9es objectives, quant au mod\u00e8le \u00e0 privil\u00e9gier.<\/p>\n

\n \n \n
Sp\u00e9cifications<\/th>Gemma 3 27B<\/a><\/th>Llama 3.3 70B<\/a><\/th><\/tr><\/thead>\n
D\u00e9veloppeur<\/td>Google<\/td>Meta<\/td><\/tr>\n
Type<\/td>LLM (multimodale)<\/td>LLM (dense)<\/td><\/tr>\n
Param\u00e8tres<\/td>27 milliards<\/td>70 milliards<\/td><\/tr>\n
Fen\u00eatre de contexte<\/td>128 K<\/td>128 K<\/td><\/tr>\n
Modalit\u00e9<\/td>Texte, image \u2192 texte<\/td>Texte \u2192 Texte<\/td><\/tr>\n
Licence<\/td>Gemma (ouverte)<\/td>Llama 3.3 Community (ouverte)<\/td><\/tr>\n
Poids ouverts<\/td>\u2705 Yes<\/td>\u2705 Yes<\/td><\/tr>\n
Co\u00fbt d\u2019entr\u00e9e (en $\/million)<\/td>$0.08<\/td>$0.10<\/td><\/tr>\n
Co\u00fbt de sortie (en $\/million)<\/td>$0.16<\/td>$0.32<\/td><\/tr>\n
VRAM (4 bits)<\/td>~16 Go<\/td>~40 Go<\/td><\/tr>\n
GPU minimal requis (en local)<\/td>RTX 4080 16 Go \/ RTX 4090<\/td>2 \u00d7 RTX 4090 \/ 1 \u00d7 GPU 48 Go<\/td><\/tr>\n
Publi\u00e9<\/td>2025<\/td>2024<\/td><\/tr>\n <\/tbody>\n <\/table>\n\n
\n

Principales diff\u00e9rences<\/h3>\n