Thomson Reuters 发布其首个 LLM「Thomson」,基于阿里 Qwen3.5-397B 构建,总研发投入约 4000 万美元,网传的 45 万美元只覆盖最后一次训练运行。
Thomson Reuters has launched Thomson, its first LLM — built on Alibaba's Qwen3.5-397B. Total R&D: ~$40M (the $450K figure circulating online covers only the final training run).
Retrained with Imperial College London for safety, ethics, and political neutrality, then further trained on Thomson Reuters' own content.
Billed as a top-tier model: 0.823 on Stanford LegalBench (behind Gemini 3.1 Pro & GPT-5.5), nearly matching Opus 4.8 on Harvey's Legal Agent Benchmark. Caveat: Thomson used inference-time scaling; GPT-5.5 didn't. Deep search: 0.53 vs GPT-5.4's 0.65.
Why skip OpenAI/Anthropic? High long-term costs and limited customizability — a smaller in-house model fits document review better.
来源:@thexpin · x.com