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English(EN) Muse Spark 1.3 Pricing and the Contributor Tier

Meta 的 Muse Spark 1.3 发布,支持 100 万上下文,提供双重定价层级

Meta 发布了 Muse Spark 1.3,这是一款闭源的多模态推理模型,专为长期代理任务和编码而设计。该模型拥有 100 万 token 的上下文窗口,并在 DeepSWE v1.1 等基准测试中得分很高,超越了 Claude Opus 5。然而,其最高性能数据来自一个受限的“max”推理模式,而公开可用的“xhigh”模式则显示出明显的性能差距。 AI

影响 为长上下文推理和代理工作流程设定了新基准,其独特的定价模式可能会影响数据共享实践。

排序理由 Meta 的 Frontier-lab 模型发布,包含系统卡和定价详情。[lever_c_demoted from frontier_release: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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

Meta 的 Muse Spark 1.3 发布,支持 100 万上下文,提供双重定价层级

本文如何被排名

Signal score
12 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Significant
Meta 的 Frontier-lab 模型发布,包含系统卡和定价详情。[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, 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
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准

报道来源 [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Yunus Emre ·

    Muse Spark 1.3 定价与贡献者层级

    <p>Meta shipped <strong>Muse Spark 1.3</strong> on September 2, 2026: a closed multimodal reasoning model built for long-running agentic workflows, multi-agent setups and coding.</p> <p>Two numbers made the headlines. It scores <strong>75.4</strong> on DeepSWE v1.1, edging past C…