谷歌于2026年6月发布开源语言模型DiffusionGemma，首次将图像AI扩散机制引入文本生成，打破传统逐字自回归范式。该模型从随机噪声迭代优化，并行输出256个词块。经英伟达优化，在单GPU单用户模式下，运行速度比同类传统模型快近四倍，如H100显卡处理单请求时表现显著提升。
谷歌推出TurboQuant算法，通过PolarQuant和QJL技术，将大语言模型推理中的键值缓存内存需求降低至少6倍，在H100 GPU上注意力计算速度提升最高8倍，且保持零精度损失。这一突破有望降低AI部署成本，加速长上下文应用发展。
Meta发布新一代自研AI芯片MTIA3，旨在减少对外部算力依赖。该芯片专为推荐系统和推理任务定制，在内部测试中，其推理效能已超越英伟达H100。
马斯克旗下xAI公司启动全球首个吉瓦级AI训练集群“Colossus2”，用于驱动Grok聊天机器人。该超级计算机占地约13个足球场，配备10万块英伟达H100芯片，标志着AI算力竞赛进入新阶段。
Xai
$1.4
输入tokens/百万
$3.5
输出tokens/百万
2k
上下文长度
Anthropic
$105
$525
200
Google
$0.7
$2.8
1k
$7
$35
$2.1
$17.5
$21
Alibaba
-
Baidu
128
$6
$24
256
Bytedance
$1.2
$3.6
4
$2
$3.9
$15.2
64
Mungert
基于Meta Llama-3.3-70B-Instruct的大语言模型，经过多阶段训练优化，在推理、聊天等任务上表现出色，支持多种语言，适用于多种AI应用场景。采用神经架构搜索技术优化，能够在单个H100-80GB GPU上高效运行。
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