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Source channel @OnePlusOTA · Post #607 · 5月27日

OnePlus Nord 2 OxygenOS 12.1 C.04 IND System • Fixed the issue that the lock screen interface displayed abnormally when charging • Fixed the issue that the screen brightness displayed abnormally in certain scenarios • Fixed the occasional issue that the desktop text displayed abnormally in certain scenarios Camera • Optimized the anti-shake effect when shooting videos • Optimized the speed of enabling Camera in certain scenarios Others • Fixed the issue of abnormal crash when enabling Fortnite MD5 Component (my_manifest): c949151afe63f1cfe9fda80d0d541abc Component (my_product): 408223966738c5d0a71f39b211bb1592 Component (my_bigball): 8253f6c910a4bc7cbfe044b3b1f79751 Component (my_stock): f08eb9a61ed03567965cbc76d980e6a3 Component (my_heytap): 28db2abbedc1eafc8947749e91b197fc Component (my_carrier): f0b3b8bd50cc13f4d2a1ebdad9f75f22 Component (system_vendor): e5d935f73c54cc08ae04c9e5abeefe20 Component (my_region): ceb333df4f651e82e5c71a9d76da3273 SHA-1 Full: a3de2e204668cc33c7134bf062bb5f6873a28bce Size Component (my_manifest): 1.22 MB (1278656) Component (my_product): 413.80 MB (433902450) Component (my_bigball): 578.54 MB (606645588) Component (my_stock): 615.30 MB (645192760) Component (my_heytap): 508.90 MB (533621509) Component (my_carrier): 1.04 MB (1088872) Component (system_vendor): 2.49 GB (2675632293) Component (my_region): 3.35 MB (3513520) Full: 4.56 GB (4893267850) Downloads ColorOS Global Server: Component (my_manifest) Component (my_product) Component (my_bigball) Component (my_stock) Component (my_heytap) Component (my_carrier) Component (system_vendor) Component (my_region) Google OTA Server: Full Exported by MlgmXyysd Color OTA Bot@OnePlusOTA #Oxygen#denniz#India#Component#Full#Stable#DN2101

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@ai_machinelearning_big_data · Post #8519 · 2025/09/11 18:21

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🚀 Релиз:Qwen3-Next-80B-A3B - эффективная модель заточенная на работа работу с очень длинным контекстом! 🔹80B параметров, но активируется только 3B на токен → тренировка и инференс 10x дешевле и быстрее, чем у Qwen3-32B (особенно при 32K+ контексте). 🔹Гибридная архитектура: Gated DeltaNet + Gated Attention → сочетает скорость и точность. 🔹Ultra-sparse MoE: 512 экспертов, маршрутизируется 10 + 1 общий. 🔹Multi-Token Prediction → ускоренное speculative decoding. 🔹 По производительности обходит Qwen3-32B и приближается к Qwen3-235B в рассуждениях и long-context задачах. 🟢Qwen3-Next-80B-A3B-Instruct показатели почти на уровне 235B flagship. 🟢Qwen3-Next-80B-A3B-Thinking превосходит Gemini-2.5-Flash-Thinking. ▪Попробовать: https://chat.qwen.ai ▪Анонс: https://qwen.ai/blog?id=4074cca80393150c248e508aa62983f9cb7d27cd&from=research.latest-advancements-list ▪ HuggingFace: https://huggingface.co/collections/Qwen/qwen3-next-68c25fd6838e585db8eeea9d ▪ ModelScope: https://modelscope.cn/collections/Qwen3-Next-c314f23bd0264a ▪Kaggle: https://kaggle.com/models/qwen-lm/qwen3-next-80b ▪ Alibaba Cloud API: https://alibabacloud.com/help/en/model-studio/models#c5414da58bjgj @ai_machinelearning_big_data #AI#LLM#Qwen#DeepLearning#MoE#EfficientModels#LongContext#Reasonin

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