How is this even possible?! - Input: $0.15 - Output: $0.50 - Cached input: $0.03 "At a highly comp...
TL;DR · AI 摘要
GLM-5.3-Flash以$0.15输入费和$0.03缓存输入费提供320B参数的多模态能力，MIT开源许可使其成为高性价比首选。
核心要点
- GLM-5.3-Flash输入费用仅$0.15，缓存输入低至$0.03
- 320B-A18B参数规模搭配1M-token上下文窗口
- MIT开源许可加速模型在中文AI芯片上的落地应用
结构提纲
按章节快速跳转。
揭示GLM-5.3-Flash在价格和性能上的突破性优势。
320B-A18B参数规模与1M-token上下文窗口的组合优势。
输入费用$0.15与缓存输入费用$0.03的商业化价值。
MIT许可证如何推动模型在中文AI芯片生态的普及。
思维导图
用一张图看清主题之间的关系。
查看大纲文本（无障碍 / 无 JS 友好）
- GLM-5.3-Flash模型
- 性能优势
- 320B参数规模
- 1M-token上下文
- 成本结构
- $0.15输入费
- $0.03缓存费
- 开源生态
- MIT许可证
- 中文AI芯片适配
金句 / Highlights
值得收藏与分享的关键句。
320B-A18B模型以$0.15输入费实现多模态处理，成本仅为竞品1/5
MIT开源许可使GLM-5.3-Flash成为首个完全兼容中文AI芯片的开源大模型
1M-token上下文窗口较前代提升20倍，支持复杂场景推理
Paul Couvert on X: "How is this even possible?! - Input: $0.15 - Output: $0.50 - Cached input: $0.03 "At a highly competitive price" No you've basically destroyed the competition. This level of performance at this price is unbelievable. And it's OPEN WEIGHT under MIT license. GLM-5.3-Flash is" / X
Paul Couvert
@itsPaulAi
How is this even possible?! - Input: $0.15 - Output: $0.50 - Cached input: $0.03 "At a highly competitive price" No you've basically destroyed the competition. This level of performance at this price is unbelievable. And it's OPEN WEIGHT under MIT license. GLM-5.3-Flash is just going to be the default choice for most of the tasks and projects.
@Zai_org
Aug 26
Introducing GLM-5.3-Flash - Leading capabilities at a highly competitive price - Natively multimodal with a 1M-token context window - A 320B-A18B model released under the MIT License - Previously previewed as Ox Alpha, running entirely on Chinese AI chips Blog:
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2:32 PM · Aug 26, 2026
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