English(EN) The best base model for training isn't about someone else's benchmarks.

Fireworks AI 发布 Inkling，一个 975B 多模态 MoE 模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-15 22:08

Fireworks AI 发布了 Inkling，一个拥有 9750 亿参数的新型专家混合（MoE）模型。这个多模态模型可以处理文本、图像和音频，并根据 Apache 2.0 许可提供。Inkling 被设计为微调的强大基础，可通过 Fireworks AI 的平台和 Tinker 平台访问。 AI

影响为开发者提供了一个强大的、开放权重的多模态基础。

排序理由 Frontier-lab 模型发布，附带系统卡。[lever_c_demoted from frontier_release: ic=1 ai=1.0]

在 X — Fireworks (inference infra) 阅读 →

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

Fireworks AI 发布 Inkling，一个 975B 多模态 MoE 模型

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Significant; Frontier-lab 模型发布，附带系统卡。[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, infra; 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: 45 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ · 2026-07-15 22:08

用于训练的最佳基础模型并非来自他人的基准测试。

The best base model for training isn't about someone else's benchmarks. Excited to offer @thinkymachines' first open-weights model: Inkling. 975B MoE, multimodal, with Apache 2.0. A great foundation for fine-tuning. Available day-zero. https://t.co/vXAVqfpRX9

本文如何被排名

报道来源 [1]

用于训练的最佳基础模型并非来自他人的基准测试。

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