Analytics India Magazine · Supreeth Koundinya · 5 小时前模型评分72
Revolut 自托管 GLM 模型，人工智能（AI，Artificial Intelligence） 编码推理成本降至原来的十分之一
Europe's Biggest Tech Startup Cuts AI Coding Costs by 90% Using Chinese Model
导读
英国金融科技公司 Revolut 通过在美国基础设施上自托管智谱（Z.人工智能（AI，Artificial Intelligence））的开源权重 GLM 模型，把 AI 编码任务的推理成本降到此前使用 Anthropic 和 OpenAI 时的约十分之一，每百万 token 综合成本约 30 美分。
分类置信度
中 · 待人工复核
- 存在未解决的相邻类别：foundation-models，需要人工复核。
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
应用领域：金融
事件类型：业务采用
证据摘录
- “The company achieved this by self-hosting the open-weight GLM model from the Chinese AI lab Z.ai on dedicated NVIDIA GPUs.”
- “The infrastructure supporting the deployment consists of 56 NVIDIA B200 GPUs serving approximately 2,000 engineers running GLM-5.3.”
- “Revolut downloads model weights and runs inference on US-based infrastructure rather than sending requests to Chinese-hosted inference endpoints.”
- “The company serves interactive workloads at around 200 tokens per second, although engineers can access throughput of up to 800 tokens per second after 5 pm, when GPU demand is lower.”
- “It still uses frontier tools such as Claude Code, Codex, and Gemini for specialised workloads, including image recognition.”
来源：Analytics India Magazine · analyticsindiamag.com