
TokenWatch: AI 算力管家
实时监控 & 一键止损 · 为你的 AI 账单上份保险
What it does
厌倦了 AI 账单的“惊喜”吗? TokenWatch 是一款为 ChatGPT 和 DeepSeek 重度用户打造的开销管理工具,将模糊的 Token 消耗转化为你熟悉的预算管理。 🎯 核心亮点 实时“余额”可见:在页面右上角显示悬浮球,剩余额度一目了然。 右键设置预算:像管理手机话费一样,轻松设定每日花费上限,再也不用担心 API 账单超支。 “跑马灯”动态反馈:每当 AI 回复,悬浮球会亮起金色的跑马灯动画,让每一次 Token 消耗都清晰可见。 超额智能熔断:免费版会及时提醒;付费专业版则能自动拦截所有超限的 API 请求,从源头杜绝意外支出。 🛡️ 隐私至上 你的数据完全属于你自己。 所有预算、消费记录都只存储在你本地的浏览器中,不会被任何服务器收集。
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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