English(EN) Gemini 4 Argon Explained: 1M Output Tokens, 77.9% on DeepSWE, and One Big Catch

Google 的 Gemini 4 Argon 拥有 100 万输出 Token 但仍不可用

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-06 09:33

Google 发布了 Gemini 4 Argon，这是一个拥有令人印象深刻的 100 万输出 Token 并在 DeepSWE 基准测试中取得 77.9% 成绩的新模型。然而，该模型目前不对公众开放使用，作者指出这是一个显著的缺点。 AI

影响为上下文窗口大小设定了新基准，可能影响需要长文本处理的未来模型开发和应用。

排序理由前沿实验室模型发布，附带系统卡。[lever_c 从 frontier_release 降级：ic=1 ai=1.0]

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

本文如何被排名

Signal score: 27 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Significant; 前沿实验室模型发布，附带系统卡。[lever_c 从 frontier_release 降级：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, product; 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。

Medium — AI coding tag TIER_1 English(EN) · Jenil D Gohel · 2026-10-06 09:33

Gemini 4 Argon 详解：100 万输出 Token、DeepSWE 准确率 77.9%，以及一个重大缺陷

<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://thejenildgohel.medium.com/gemini-4-argon-explained-1m-output-tokens-77-9-on-deepswe-and-one-big-catch-c4a398770cb4?source=rss------ai_coding-5"><img src="https://cdn-images-1.medium.com/max/1672/1*YIG2AfA…