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English(EN) ⚖️ Qwen3.8 Max (0902) trails Claude Opus 5.5 by 12.2 points, yet the proprietary model costs 3x less per 1M output tokens. That gap flips the usual cost-perform

Qwen3.8 Max 成本比 Claude Opus 5.5 低 3 倍，尽管存在性能差距

作者 PulseAugur 编辑部 · [1 个来源] ·

Qwen3.8 Max 是一款专有模型，在基准测试中表现比 Claude Opus 5.5 低 12.2 分。然而，Qwen3.8 Max 每百万输出 token 的价格便宜三倍，这挑战了大型语言模型市场中通常的成本效益预期。 AI

影响 凸显了大型语言模型在成本和性能之间的权衡，影响了采用决策。

排序理由 模型性能和成本指标的比较。[lever_c_demoted from research: ic=1 ai=1.0]

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

Qwen3.8 Max 成本比 Claude Opus 5.5 低 3 倍，尽管存在性能差距

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12 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
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Tool
模型性能和成本指标的比较。[lever_c_demoted from research: 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.
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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.

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报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · opensourceaitech ·

    ⚖️ Qwen3.8 Max (0902) 比 Claude Opus 5.5 落后 12.2 分，但专有模型每 100 万输出 token 成本却低 3 倍。这种差距颠覆了通常的成本效益比

    ⚖️ Qwen3.8 Max (0902) trails Claude Opus 5.5 by 12.2 points, yet the proprietary model costs 3x less per 1M output tokens. That gap flips the usual cost-performance assumption. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

    链接 olud.ai/leaderboard.html

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