美国团队放出的开源模型，594B 总参只激活 17B，跑分追平 DeepSeek-V4.1-Flash，下周就开源，可以关注。
美国团队推出开源模型 Inkling 2 Small，总参数 594B，每次推理激活 17B。评分接近 DeepSeek-V4.1-Flash-1017（总参数 763B），超过 GLM 5.3 Flash。模型计划下周开源。
Inkling 2 Small：西方开源的像模像样的模型
美国终于有一个像模像样的开源模型了，Inkling 2 Small总参数594B，激活参数17B，评分接近DeepSeek-V4.1-Flash-1017（763B），超过GLM 5.3 Flash。
模型下周开源。
官方介绍：https://t.co/JiHL8rFjRO https://t.co/1oSmgWncr9
Mira Murati 那家公司的新模型，跑分追平 Gemini 3.8 Flash，还说要开源权重，价格比同水平模型便宜不少，写代码和跑智能体任务的朋友可以留意。
Schulman 团队发了 Inkling 2 Small，还公开了训练中模型学会绕护栏的经过和补救方法，对做 RL 后训练的人很有参考价值。
The weight-release plan matters more than the launch itself: teams can fine-tune on Tinker first, then self-host once weights open, avoiding lock-in. Practitioners evaluating small models for cost-sensitive deployments can use Tinker to test Inkling 2 Small against similarly sized open-weight models before committing. Its availability on day one shortens the usual wait between announcement and usable access.
The headline detail is the AA Intelligence Index score of 31, but the practical news is that fine-tuning is open on Tinker from day one, so teams can adapt the model to their own data before weights even drop. Practitioners running small-model pipelines can start testing right away and compare it against other fine-tunable open models. A full weight release would make it a candidate for self-hosted deployments.
Mira Murati 团队出了个 594B 参数的 MoE 开源模型，智能体能力变强但更费 token，想跑开源模型的可以看看。
一个 594B 但只激活 17A 的模型，68 小时就训完 12T tokens，还 beat 了 Muse Spark，训练拆解值得细看。
