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English(EN) The open-weight Qwen3.8 2.4T A95B trails Claude Fable 5.1 by 10.1 points — yet costs 8x less per 1M output tokens. That price-performance gap is the real story.

开源权重 LLM 在性价比上挑战 Claude Fable 5.1 · 跟踪 4 个来源

几款开源权重的大型语言模型在性能上正与 Anthropic 的 Claude Fable 5.1 展开竞争,同时每百万输出 token 的成本却显著降低。GLM-5.3、Qwen3.8、Qwen3.8 Max 和 Kimi K3 都以不同幅度落后于 Claude Fable 5.1,但它们的成本效益凸显了 AI 模型市场价值差距的缩小。这一趋势表明,专有模型可能面临来自更经济实惠、高性能的开源替代品的日益增长的压力。 AI

影响 开源权重模型正在迅速缩小与专有模型领导者在性能和成本上的差距,可能加速更经济实惠的 AI 解决方案的采用。

排序理由 多个来源对 LLM 性能和成本效益的比较。

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 6 个来源。 我们如何撰写摘要 →

开源权重 LLM 在性价比上挑战 Claude Fable 5.1 · 跟踪 4 个来源

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多个来源对 LLM 性能和成本效益的比较。
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model release, product
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报道来源 [6]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    GLM-5.3 比 Claude Fable 5.1 落后 6.2 分,但每百万输出 token 便宜 11 倍——价值差距正在迅速缩小。https:// olud.ai/leaderboard.html # Ope

    GLM-5.3 trails Claude Fable 5.1 by 6.2 points but is 11x cheaper per million output tokens—narrowing the value gap fast. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

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

    ⚖️ GLM 5.2 评分 42.5,Claude Fable 5.1 评分 56.8 – 相差 14.3 分。但 GLM 5.2 每百万输出 token 便宜 16 倍。真正的权衡。https:// olud.ai/l

    ⚖️ GLM 5.2 scores 42.5, Claude Fable 5.1 scores 56.8 – a 14.3-point gap. But GLM 5.2 is 16x cheaper per 1M output tokens. The real trade-off. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

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

    ⚖️ GLM 5.3 比 Claude Fable 5.1 落后 10.6 分,但每 100 万输出 token 便宜 200 倍——一个值得权衡的取舍。https:// olud.ai/leaderboard.htm

    ⚖️ GLM 5.3 Flash trails Claude Fable 5.1 by 10.6 points, but it’s 200x cheaper per 1M output tokens—a trade-off worth weighing. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

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

    开源权重 Qwen3.8 2.4T A95B 比 Claude Fable 5.1 落后 10.1 分 — 但每 100 万输出 token 成本却低 8 倍。这种性价比差距才是真正值得关注的。

    The open-weight Qwen3.8 2.4T A95B trails Claude Fable 5.1 by 10.1 points — yet costs 8x less per 1M output tokens. That price-performance gap is the real story. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

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

    ⚖️ Qwen3.8 Max 比 Claude Fable 5.1 落后 7.6 分,但每 100 万输出 token 成本低 8 倍。这几乎是以极低的价格获得了专有性能。S

    ⚖️ Qwen3.8 Max trails Claude Fable 5.1 by 7.6 points but costs 8x less per 1M output tokens. That's nearly proprietary performance at a fraction of the price. See the hourly data. https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

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

    Kimi K3 仅以 6 分之差落后于 Claude Fable 5.1 — 且每百万输出 token 成本低 3 倍。⚖️ https:// olud.ai/leaderboard.html # OpenSource # AI # LLM

    Kimi K3 trails Claude Fable 5.1 by just 6 points — and costs 3x less per 1M output tokens. ⚖️ https:// olud.ai/leaderboard.html # OpenSource # AI # LLM