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GigaChat-3.5 Reasoning 模型发布,采用 MoE 架构

一款新的大型语言模型 GigaChat-3.5 Reasoning 已发布。该模型采用 432B-A28B 混合专家(MoE)架构,并配备 Gated DeltaNet 以实现高效的长上下文处理。它使用领域专家进行训练,并蒸馏成单个模型,据报道其推理性能接近 DeepSeek V4 Flash Preview,但使用的 token 数量显著减少。 AI

影响 此次发布为寻求高效长上下文处理和潜在竞争性推理能力的用户提供了一个新选择。

排序理由 前沿实验室发布新模型。[lever_c_demoted from frontier_release: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

GigaChat-3.5 Reasoning 模型发布,采用 MoE 架构

本文如何被排名

Signal score
15 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Significant
前沿实验室发布新模型。[lever_c_demoted from frontier_release: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准

报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/netikas ·

    GigaChat-3.5-Reasoning

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1wchl1x/gigachat35reasoning/"> <img alt="GigaChat-3.5-Reasoning" src="https://external-preview.redd.it/iFjYEIjnD9YMwvZW7nwvws7gGCiOiwxfumjFWU1-xc0.png?width=640&amp;crop=smart&amp;auto=webp&amp;s=a9877d3e0af3a…