LongCat-2.5 与 Qwen3.8-Max 实测对比：同样任务成本差近 3 倍
美团 LongCat-2.5 做游戏任务只要 $0.28，Qwen3.8-Max 要 $0.82，作者全程实测，价格细节都列出来了。
LongCat-2.5 用一行提示词构建了可玩的 Angry Birds 风格浏览器游戏，包含 3 个关卡、3 种小鸟、可破坏的木石玻璃方块、音效和星级评分，成本 $0.28、耗时约 34 分钟，Qwen3.8-Max 完成同样任务花费 $0.82。LongCat-2.5 总参数 1.6T，每 token 激活约 48B，支持原生多模态输入，训练序列最长 1M token。53 轮 agent 交互中 4.8M 输入 token 有 4.7M 来自缓存，缓存输入价格 $0.006/1M token，未缓存输入 $0.30、输出 $1.20。
I tested LongCat-2.5 and Qwen3.8-Max on the same browser game, and LongCat got it done for $0.28 versus $0.82. That's nearly 3x cheaper for the same task. I regularly test cheaper models on full app builds, and LongCat-2.5 from @Meituan_LongCat looks like a strong option. With 1.6T total parameters, around 48B active per token, and native multimodal input, it’s built for long-horizon tasks. Its training includes sequences of up to 1M tokens, helping it stay on track through complex, multi-step projects. I gave both models the same one-line prompt in my own harness: "Build a playable Angry Birds-style browser game." Both games worked. LongCat-2.5’s version included three levels, three bird types, breakable wood, stone, and glass blocks, plus sound effects and star ratings. LongCat-2.5 completed the task for $0.28 in about 34 minutes, compared with $0.82 for Qwen3.8-Max. It also wrote its own physics tests along the way. About 4.7M of its 4.8M input tokens came from cache, keeping costs low across 53 agent turns. Cached input is just $0.006 per 1M tokens, while uncached input costs $0.30 and output costs $1.20 per 1M tokens. Try LongCat-2.5: longcat.ai/platform/produ… Your browser does not support the video tag. 🔗 View on Twitter 💬 13 🔄 0 ❤️ 14 👀 1705 📊 12 ⚡
