{"id":1268,"date":"2026-06-23T14:45:04","date_gmt":"2026-06-23T14:45:04","guid":{"rendered":"https:\/\/convly.ai\/?p=1268"},"modified":"2026-06-23T14:45:04","modified_gmt":"2026-06-23T14:45:04","slug":"llama-3-3-70b-vs-qwen3-32b","status":"publish","type":"post","link":"https:\/\/convly.ai\/pt\/llama-3-3-70b-vs-qwen3-32b\/","title":{"rendered":"Llama 3.3 70B vs Qwen3 32B: Especifica\u00e7\u00f5es, pre\u00e7os e qual escolher (2026)"},"content":{"rendered":"

Llama 3.3 70B<\/strong> vs Qwen3 32B<\/strong> \u2014 70B versus 32B for local power users. Below is the full side-by-side: specifications, API pricing, context window, local hardware requirements, and a clear, data-driven recommendation on which to pick.<\/p>\n

\n \n \n
Especifica\u00e7\u00f5es<\/th>Llama 3.3 70B<\/a><\/th>Qwen3 32B<\/a><\/th><\/tr><\/thead>\n
Desenvolvedor<\/td>Meta<\/td>Alibaba<\/td><\/tr>\n
Tipo<\/td>LLM (densa)<\/td>LLM (densa)<\/td><\/tr>\n
Par\u00e2metros<\/td>70B<\/td>32B<\/td><\/tr>\n
Janela de contexto<\/td>128K<\/td>128K<\/td><\/tr>\n
Modalidade<\/td>Texto \u2192 Texto<\/td>Texto \u2192 Texto<\/td><\/tr>\n
Licen\u00e7a<\/td>Llama 3.3 Community (aberta)<\/td>Apache 2.0 (aberta)<\/td><\/tr>\n
Pesos abertos<\/td>\u2705 Sim<\/td>\u2705 Sim<\/td><\/tr>\n
Pre\u00e7o de entrada (US$\/1 milh\u00e3o)<\/td>$0.10<\/td>$0.08<\/td><\/tr>\n
Pre\u00e7o de sa\u00edda (US$\/1 milh\u00e3o)<\/td>$0.32<\/td>$0.28<\/td><\/tr>\n
VRAM (4 bits)<\/td>~40 GB<\/td>~20 GB<\/td><\/tr>\n
GPU m\u00ednima (local)<\/td>2\u00d7 RTX 4090 \/ 1\u00d7 GPU com 48 GB<\/td>RTX 4090 24 GB (Q4)<\/td><\/tr>\n
Lan\u00e7ado<\/td>2024<\/td>2025<\/td><\/tr>\n <\/tbody>\n <\/table>\n\n
\n

Principais diferen\u00e7as<\/h3>\n