Token costs will become a dominant topic in enterprises going forward with AI. Just got out of a dinner with many Fortune 500 enterprise CIOs and this was the most heated topic. A mix of strategies are being employed, but basically no one feels like they have the right solution. A mix of: figuring out how to prioritize workloads to different models, giving out access to better or worse agents by user type, setting different spend caps by team, having teams justify AI by their use-case, and some just having unfettered access. Everyone is trying to figure out a semi/predictable model right now in a world where the underlying tech and cost models are constantly evolving.
随着 AI 在企业中的推进，token 成本将成为一个主导性话题。刚参加完一场与许多 Fortune 500 企业 CIO 共进的晚餐，这就是现场讨论最激烈的话题。大家正在采用各种策略，但基本上没有人觉得自己已经找到了正确解法。做法包括：研究如何把不同工作负载优先分配给不同模型；按用户类型提供能力更强或更弱的 agent（智能体）访问权限；按团队设置不同的支出上限；要求团队根据其 use-case（使用场景）为 AI 的投入作出论证；还有一些公司则是完全不设限制地开放访问。眼下，所有人都在试图摸索出一种半可预测 / 可预测的模式，而底层技术和成本模型却一直在不断演变。
Gemini 3.5 Flash is out, and it's a major jump over Gemini 3 Flash in model capability for knowledge work. We've been evaluating it on our Box AI Complex Work Eval in early release, and the model delivers a 12 percentage point jump on complex document tasks. For testing this model, we give the Box AI Agent (using Gemini 3.5) complex problems to solve that represent common but difficult knowledge worker tasks in banking, consulting, public sector, healthcare, and other industries. These tasks can be things like drafting reports, doing due diligence, and more, given a set of relevant documents. In our tests, Gemini 3.5 Flash delivered jumps across every industry, including: * Financial services: 81% vs 73% (+8pp) * Public sector: 76% vs 59%, (+17pp) * Healthcare: 73% vs 51%, (+22pp) * Life Sciences: 67% vs 47%, (+20pp) Incredible to see the continued performance gains. Gemini 3.5 Flash will be available soon in Box AI Studio and through the Box API. The Box MCP Server will soon be available in the Gemini app with more details to come.
Gemini 3.5 Flash 已发布，相比 Gemini 3 Flash，它在知识型工作方面的模型能力有了重大跃升。我们在早期版本中，使用 Box AI Complex Work Eval 对它进行了评估，该模型在复杂文档任务上的表现提升了 12 个百分点。在测试这个模型时，我们让 Box AI Agent（使用 Gemini 3.5）去解决复杂问题，这些问题代表了银行、咨询、公共部门、医疗保健及其他行业中常见但困难的知识工作者任务。给定一组相关文档后，这些任务可能包括起草报告、开展 due diligence（尽职调查）等。在我们的测试中，Gemini 3.5 Flash 在各个行业都实现了提升，包括：* Financial services：81%，对比 73%（+8pp）* Public sector：76%，对比 59%（+17pp）* Healthcare：73%，对比 51%（+22pp）* Life Sciences：67%，对比 47%（+20pp）持续的性能提升令人惊叹。Gemini 3.5 Flash 很快将在 Box AI Studio 和通过 Box API 提供。Box MCP Server 也将很快在 Gemini app 中可用，更多细节即将公布。