Coinbase moved to open models. Cut AI spend in half while increasing token usage

https://x.com/brian_armstrong· Jul 30, 2026 · 10:43 AM UTC ·1 min read · 0 reactions · 0 comments · 1 view

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Brian Armstrong@brian_armstrongHow to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts. Better Defaults (not Usage Caps) – Engineers can choose any model they want, but defaults matter. We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task.

Key facts

▪Brian Armstrong@brian_armstrongHow to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts.
▪Better Defaults (not Usage Caps) – Engineers can choose any model they want, but defaults matter.
▪We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task.

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Original publisher	X (formerly Twitter)
Canonical URL	https://twitter.com/brian_armstrong/status/2070670644577280109
Publication time	Thu, 30 Jul 2026 10:43:31 +0000
Retrieval time	2026-07-30T10:52:02.392Z
Last seen	2026-07-30T10:52:02.392Z
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Opening excerpt (first ~120 words) tap to expand

Brian Armstrong@brian_armstrongHow to keep AI spend flat while token usage grows exponentially: Not with friction and spend alerts. With better defaults, routing, and caching. Better Defaults (not Usage Caps) – Engineers can choose any model they want, but defaults matter. We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task. 91% of our employees were never hitting their usage caps, so instead of lowering caps and driving up alerts, we're moving to cheaper defaults. Note that code reviews use a diversity of models, so they can check each other's work.

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