凡人小北· @frxiaobei · X·· 5 小时前AI 评分72
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Revolut 把 2000 名工程师写代码的默认模型换成自部署的开源 GLM,其 AI 运维负责人 David Abitbol 在 AI Engineer 大会上披露。
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Revolut 把 2000 个工程师写代码默认用的模型换成了自己部署的开源 GLM。
他们 AI 运维负责人 David Abitbol 在 AI Engineer 大会上讲的。
56 张 B200,综合成本每百万 token 大约 0.3 美元,账单是以前付给 Anthropic 和 OpenAI 的十分之一。
Claude Code、Codex 只留给那些难的活。不再限 token 之后,coding time 和 lead time 分别改善了大约 60% 和 70%。
这个价没算机器和人力,但方向应该足够清楚了。国货的机会全面到来。
Revolut: Europe's most valuable startup ($200B) just showed the world its AI strategy. Every company will end up copying it. At the start of this year, Revolut leaned on the frontier labs. Its 2,000 engineers used Claude Code and Codex, and some burned $1,000 to $10,000 a month each. The bills kept climbing, and the returns weren't there. So Revolut switched its default to an open-source model called GLM. All it needs is GPUs, which it rents from Together AI. The results, by Revolut's own count: - The bill is about a tenth of what it paid OpenAI and Anthropic - Engineers get unlimited tokens instead of spending caps - Coding time is down 60% and lead time is down 70% That's the chart below. Revolut still uses Claude and GPT, but only as "the exception," for the tasks they do best. Everything else runs on open source. So here's the question I keep coming back to: how many use cases can companies really justify sending to frontier models? My answer is very few. Plenty of companies still route everything to OpenAI and Anthropic today. For how long? I think open source ends up handling the vast majority of corporate AI work, and frontier models get a short list of the hardest jobs. That's a problem for labs whose revenue forecasts assume unlimited growth. If you appreciate unpopular takes, follow me @m0xt_ for more.在 X 查看被引用的帖子
来源:凡人小北 · x.com