NVIDIA：比价目表没用，token 效率才是选模型的关键指标
NVIDIA 的人在 Open by Design NYC 活动上说，选模型别只看单价，token 效率才是决定真实成本的关键，训练自己模型的团队也适用。现场还有 Reflection 和 Together AI 的人一起聊开源模型和 post-training，做技术选型的可以听听他们的算法。
NVIDIA 的 Jacob Loewenstein 在 Open by Design NYC 活动上提出，只用价目表比较模型成本会漏掉一半的账，token 效率应排在模型评估标准前列。
这一观点同时适用于两种场景：企业直接选用现成模型，以及团队自己训练模型。活动上还有 Reflection 的 Zach Wentz 和 Together AI 的 Hassan El Mghari，与在场开发者讨论了开源模型、post-training 和推理相关话题。
If you’re comparing models by their price sheet, you’re missing half the math.
Jacob Loewenstein @spatialjlo from NVIDIA explains why token efficiency belongs at the top of your evaluation criteria, whether you’re adopting a model or training your own.
One of the standout moments from Open by Design NYC, where Jacob, Zach Wentz @zkwentz from Reflection, and Hassan El Mghari @nutlope from Together AI chatted with builders digging into open models, post-training, and inference.
This report is categorized under AITOP's "How-to" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include token效率, 开源模型, post-training, Together AI.
Source attribution: curated from Together AI (@togethercompute). Cross-source corroboration: 6 independent sources have covered this development (including NVIDIA AI, Thomas Wolf, TestingCatalog), confirming industry-wide signal strength.
