English(EN) The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs

《华盛顿邮报》每月使用 Together AI 处理 17.9 亿个 token，采用开放模型

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-24 22:11

Together AI 使《华盛顿邮报》能够每月使用 Llama 和 Mistral 等开源模型处理 17.9 亿个输入 token。此次合作使《华盛顿邮报》能够实现可预测的成本并完全控制其 AI 模型堆栈。此次合作凸显了组织如何通过利用高效的推理基础设施来实现 AI 独立性。 AI

影响使媒体组织能够在 AI 部署中实现更大的控制力和成本可预测性。

排序理由该集群描述了媒体公司（《华盛顿邮报》）使用 AI 基础设施提供商（Together AI）的具体用例，而不是新的模型发布或重大的行业性事件。

在 X — Together (inference / OSS) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

《华盛顿邮报》每月使用 Together AI 处理 17.9 亿个 token，采用开放模型

报道来源 [2]

X — Together (inference / OSS) TIER_1 English(EN) · togethercompute · 2026-07-24 22:27

The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs

The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs and full control over the model stack.
X — Together (inference / OSS) TIER_1 English(EN) · togethercompute · 2026-07-24 22:11

The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs

The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs and full control over the model stack. https://t.co/g7M1BX5r27

报道来源 [2]

The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs

The Washington Post processed 1.79B input tokens per month through Together AI, running open models like Llama and Mistral in production with predictable costs

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