一周真实使用体验:光标 vs. 反重力
1 分•作者: okaris•6 个月前
2026年第一周,我先后使用了Cursor和Google Antigravity,这并非计划好的,而是因为我比预期更快地用完了两个Cursor Ultra订阅,于是决定在免费层级试用Antigravity。<p>我通常的月花费在60-100美元左右。但在几天内,费用就飙升到了500美元以上,仪表盘预测月花费将达到1600美元左右。我关闭了Max模式,但UI界面始终显示20万的上下文窗口。<p>我最终拼凑出的真相是,Cursor维护了一个大型的隐藏提示状态。除了可见的对话历史,这还包括工具追踪、代理状态、推理框架以及大量的代码库上下文。该状态使用Claude的缓存功能进行提示缓存,并且在每次请求时,都会重放完整的缓存前缀。<p>Anthropic每次发生这种情况时都会对缓存读取进行计费,即使这些内容后来在实际推理之前被总结或截断。<p>以下是我日志中的一个具体例子:
• 实际用户输入约4000个token
• 缓存读取token约2100万个
• 总计费token约2200万个
• 单次调用的费用约12美元<p>这并非仅限于Opus模型。我发现Sonnet模型也存在同样的问题。<p>技术支持解释说,这与底层API的计费方式一致。但从我的角度来看,问题不在于正确性,而在于可见性。成本已经与我在产品中能够看到或理解的任何内容脱钩。我无法检查缓存大小,了解重放行为,也无法设置有意义的保护措施。<p>我取消了订阅,并以此为借口尝试了Google Antigravity。<p>免费层级比我预期的更易于使用。它提供了对Opus 4.5的访问权限,这仍然是我进行非平凡编码工作时首选的模型。对于简单到中等复杂度的任务,它通常能干净利落地完成。限制是不透明的(从免费到Pro再到Ultra的描述非常抽象),但当你达到限制时,至少会收到一条明确的冷却消息,告诉你Opus何时再次可用。<p>当Opus耗尽时,Antigravity会回退到Gemini模型。这对于比较很有用。但在一个混乱、不断演进的代码库上进行真正的编码工作时,Gemini Flash、Pro和Thinking模型经常会丢失架构决策,并产生不尊重现有约束的一次性更改。<p>这部分是模型质量的问题,但并非全部。Cursor的代理在收集相关代码库状态、制定计划和连贯地执行方面做得更好。Antigravity的代理感觉更薄弱,我发现自己花费更多时间来审查和纠正差异,以保持不变性。<p>还有一些小的不足。Tab补全被宣传为无限的,但我无法可靠地让它工作。回到基本的自动补全,让我意识到我的工作流程有多么依赖于良好的Tab补全。从用户体验角度来看,Antigravity感觉更慢。也许不是原始的延迟,而是响应的流式传输和动画方式,无法让我像使用Cursor那样保持在同一个循环中。<p>最终结果:Antigravity免费版是一个不错的选择,适合入门和实验,特别是如果预算有限的话。但我目前还不会为它付费。Cursor仍然是一个强大的产品,但其不透明的缓存和计费行为使得难以大规模地推断成本。<p>作为背景,我正在inference.sh上自己构建一个代理运行时,专注于显式状态、持久执行以及具有复杂工具使用的可靠深度代理。正因为如此,我可能比大多数人对代理编排、隐藏状态以及成本如何从这些设计选择中产生更敏感。<p>整个体验强化了我已经相信的一件事:在代理系统中,隐藏状态是危险的。隐藏状态与不透明的计费相结合则更糟。如果用户看不到状态,他们就无法推断成本。如果他们无法推断成本,他们就不会信任这个系统。<p>目前,如果你正在进行尚未被重复千百次的工作,这些编码代理都无法做到“一劳永逸”。你仍然需要掌控全局。
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in the first week of 2026 i ended up using cursor and google antigravity back to back, not by plan but because i burned through two cursor ultra subscriptions faster than expected and decided to try antigravity on the free tier.<p>my normal usage is ~$60–100/month. within a few days it jumped to $500+, with the dashboard projecting ~$1.6k/month. max mode was off, and the ui consistently showed a 200k context window.<p>what i eventually pieced together is that cursor maintains a large hidden prompt state. beyond visible conversation history, this includes tool traces, agent state, reasoning scaffolding, and large chunks of repo context. that state is prompt-cached using claude’s cache feature, and on every request the full cached prefix is replayed.<p>anthropic bills cache reads every time this happens, even if that content is later summarized or truncated before actual inference.<p>one concrete example from my logs:
• actual user input ~4k tokens
• cache read tokens ~21 million
• total billed tokens ~22 million
• cost for a single call ~$12<p>this wasn’t limited to opus. i saw the same pattern with sonnet.<p>support explained that this matched how the underlying api is billed. from my perspective, the issue wasn’t correctness but visibility. cost had become decoupled from anything i could see or reason about in the product. i had no way to inspect cache size, understand replay behavior, or set meaningful guardrails.<p>i canceled and treated it as an excuse to try google antigravity.<p>the free tier was more usable than i expected. it gives access to opus 4.5, which is still my preferred model for nontrivial coding work. for easy to moderate complexity tasks, it usually finishes cleanly. limits are opaque (free → pro → ultra is described in very abstract terms), but when you hit a limit you at least get a clear cooldown message telling you when opus will be available again.<p>when opus is exhausted, antigravity falls back to gemini models. that was useful for comparison. for real coding work on a messy, evolving codebase, gemini flash, pro, and thinking consistently lost architectural decisions and produced one-off changes that didn’t respect existing constraints.<p>some of that is model quality, but not all of it. cursor’s agent does a better job gathering relevant repo state, forming a plan, and executing it coherently. antigravity’s agent feels thinner, and i found myself spending more time reviewing and correcting diffs to preserve invariants.<p>there were also smaller papercuts. tab completion is advertised as unlimited, but i couldn’t get it working reliably. going back to basic autocomplete was a reminder of how dependent my workflow is on good tab completion. ux-wise, antigravity feels slower. maybe not raw latency, but the way responses stream and animate doesn’t keep me in the same loop cursor does.<p>net result: antigravity free is a solid option for starting out and experimenting, especially if budget matters. i wouldn’t pay for it yet. cursor is still a strong product, but opaque caching and billing behavior makes it hard to reason about cost at scale.<p>for context, i’m building an agent runtime myself at inference.sh, focused on explicit state, durable execution, and reliable deep agents with complex tool use. because of that, i’m probably more sensitive than most to differences in agent orchestration, hidden state, and how cost emerges from those design choices.<p>this whole experience reinforced something i already believed: hidden state is dangerous in agent systems. hidden state combined with opaque billing is worse. if users can’t see state, they can’t reason about cost. and if they can’t reason about cost, they won’t trust the system.<p>right now, none of these coding agents are “set and forget” if you’re doing work that hasn’t been done a thousand times before. you still have to stay in charge.