Just saw the news that Revolut has made self-hosted open-weight models (GLM-5.1 → now GLM-5.3 from Z.ai / Zhipu) the default coding assistant for ~2,000 engineers. Key points from David Abitbol’s talk (AI Engineer conference): • Previously used Claude Code (and Codex) with strict budgets because some engineers were burning $1k–$10k/month with limited ROI. • Switched to self-hosted GLM running on 56× Nvidia B200 GPUs. • Blended cost ≈ $0.30 per million tokens → roughly 1/10th of what they were paying Anthropic/OpenAI (≈90% cost cut). • Measured ~60% improvement in coding time and ~70% improvement in lead time. • Unlimited tokens → engineers now use AI for Jira, Confluence, Slack, docs, etc., not just “hard” coding tasks. • Claude Code / Codex / Gemini are still available but treated as the exception (mainly for complex or vision tasks). GLM is text-only so they route images elsewhere. Curious what people here think:
- Is this the start of a bigger shift where open/self-hosted models become the default and frontier APIs are only for the hard 10–20% of work?
- Anyone already running similar setups (GLM, DeepSeek, Qwen, etc.) in production for coding agents? How does quality compare day-to-day vs Claude Code / Cursor / Codex?
- For a regulated fintech, how big a deal is the compliance/self-hosting angle vs pure cost?
- Does this put real pressure on Anthropic/OpenAI pricing for enterprise coding use cases? Would love to hear experiences, skepticism, or “we tried this and…” stories. submitted by /u/KookyOky
Originally posted by u/KookyOky on r/ClaudeCode