{"id":20474,"date":"2026-10-08T22:57:34","date_gmt":"2026-10-09T02:57:34","guid":{"rendered":"https:\/\/wp.glbgpt.com\/?p=20474"},"modified":"2026-10-08T22:57:35","modified_gmt":"2026-10-09T02:57:35","slug":"gpt-6-1-sol-vs-gpt-6-astra","status":"publish","type":"post","link":"https:\/\/wp.glbgpt.com\/it\/hub\/gpt-6-1-sol-vs-gpt-6-astra","title":{"rendered":"GPT-6.1 Sol vs GPT-6 Astra: quale modello scegliere?"},"content":{"rendered":"

GPT-6.1 Sol is the value default; GPT-6 Astra is the quality ceiling.<\/strong> Both expose the same 1,050,000-token context window, 128,000-token output limit, multimodal input, and broad tool set. The decisive difference is positioning and price: Sol costs $2 per million input tokens and $10 per million output tokens, while Astra costs $10 and $50. In other words, Astra must create enough extra value to justify a five-times-higher Standard token bill.<\/p>\n\n\n\n

That does not make Sol \u201cthe same model for less.\u201d OpenAI calls Astra its most capable model for the hardest end-to-end work and describes Sol as near-Astra performance for complex work at lower cost. The right decision is therefore an evaluation problem, not a brand-ranking exercise. This comparison uses current GPT-6.1 Sol documentation<\/a>, il GPT-6 Astra model page<\/a>, and identical cost scenarios checked on October 9, 2026.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
\n
Prova GPT-6.1 Sol su GlobalGPT<\/strong><\/a><\/div>\n<\/div>\n\n\n\n