B.AI Responses API ไธ็บฟ GPT-6 Astra
B.AI ่ๅ API ๆ GPT-6 Astra ไธ DeepSeekใGLMใKimi ็ญๆจกๅๆพๅจๅไธๆฅๅฃ๏ผๅนถๆฏๆๆฅๅ ฅ Codexใ

๐ ๐ผ๐ฑ๐ฒ๐น๐ ๐๐๐ฎ๐ถ๐น๐ฎ๐ฏ๐น๐ฒ ๐ผ๐ป ๐.๐๐ ๐ฅ๐ฒ๐๐ฝ๐ผ๐ป๐๐ฒ๐ ๐๐ฃ๐ One thing that can make AI development frustrating is having to switch between different providers just to test different models. http://B.AI is taking a different approach with its Responses API. Developers can now access four major model series through the platform: โ GPT โ DeepSeek โ GLM โ Kimi And the interesting part is the range of options within each series. ๐๐ฃ๐ง ๐ฆ๐ฒ๐ฟ๐ถ๐ฒ๐ GPT-5 Mini GPT-5 Nano GPT-5.2 GPT-5.4 GPT-5.4 Mini GPT-5.4 Nano GPT-5.4 Pro GPT-5.5 GPT-5.5 Instant GPT-5.6 Luna GPT-5.6 Sol GPT-5.6 Terra GPT-6 Astra ๐๐ฒ๐ฒ๐ฝ๐ฆ๐ฒ๐ฒ๐ธ ๐ฆ๐ฒ๐ฟ๐ถ๐ฒ๐ DeepSeek-V4-Pro DeepSeek-V4.1-Flash ๐๐๐ ๐ฆ๐ฒ๐ฟ๐ถ๐ฒ๐ GLM-5.1 GLM-5.2 GLM-5.3 GLM-5.3-Flash GLM-5.3-FlashX ๐๐ถ๐บ๐ถ ๐ฆ๐ฒ๐ฟ๐ถ๐ฒ๐ Kimi K2.6 Kimi K3 This matters because developers don't always need the same model for every job. One project might need strong reasoning. Another might prioritise coding. Another could be more sensitive to speed, context, cost or output quality. Having multiple model families available through one API makes it easier to test those differences and choose what actually works for the task. http://B.AI also brings these models into Codex, where developers can configure their http://B.AI API Key and Base URL, then specify the model ID they want to use. So instead of thinking: โWhich AI provider do I have to use?โ the workflow becomes more like: โWhich model is best suited for what I'm building?โ That's a more useful way to approach multi-model AI development. More models don't automatically mean better results. More choice + proper testing = better decisions. Try it on http://B.AI: http://b.ai API docs: http://docs.b.ai/llmservice/api/ #TRONEcoStar #TRONEcoStar @justinsuntron @BAI_AGI