Coinbase Switches to Chinese AI Models GLM and Kimi, Cuts AI Spending by 50%
On the SWE-bench Pro coding benchmark, GLM 5.2 scored 62.1, outperforming OpenAI's GPT-5.5 at 58.6 [3].Armstrong framed the strategy not as a cost-cutting exercise but as infrastructure for sustainable growth. First, the company defaults all engineers to open-weight models — specifically GLM 5.2 and Kimi 2.7 — through its internal LLM gateway, reserving costlier frontier models for tasks that genuinely require them [2].Second, an automated routing layer matches prompts to models by difficulty. 'You may want a frontier model for planning, but not for execution where they can be overkill,' Armstrong wrote [2].
- ▪On the SWE-bench Pro coding benchmark, GLM 5.2 scored 62.1, outperforming OpenAI's GPT-5.5 at 58.6 [3].Armstrong framed the strategy not as a cost-cutting exercise but as infrastructure for sustainable growth.
- ▪First, the company defaults all engineers to open-weight models — specifically GLM 5.2 and Kimi 2.7 — through its internal LLM gateway, reserving costlier frontier models for tasks that genuinely require them [2].Second, an automated routin
- ▪'You may want a frontier model for planning, but not for execution where they can be overkill,' Armstrong wrote [2].
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,337 of its stories.
Opening excerpt (first ~120 words) tap to expand
AI AI OPENAI STOCKS TECH Coinbase Switches to Chinese AI Models GLM and Kimi, Cuts AI Spending by 50% Jun 29, 2026 · 5:20 PM · by MLQ Agent · 4 min read Key points Coinbase has defaulted engineers to GLM 5.2 from Zhipu and Kimi 2.7 from Moonshot AI through its internal LLM gateway, cutting AI spending by nearly 50% [1] GLM 5.2 costs $1.40 per million input tokens vs. $5 for Anthropic's Opus 4.8 — roughly five times cheaper — while scoring higher on the SWE-bench Pro coding benchmark [3] An automated routing system and caching overhaul pushed Coinbase's cache hit rate from 5% to 60%, a 12x improvement [1] Other U.S.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at MLQ.ai.
Discussion
0 commentsMore from MLQ.ai
