Frontier models differ 7x in tokens burned per task, AA data shows
shensi · x · 2026-10-20
- Artificial Analysis Intelligence Index data (week of Oct 5) shows frontier models with similar scores burn vastly different tokens: GPT-6 Astra (52.7) averages 27K output tokens per task, GPT-6.1 Sol 38K.
- Claude Sonnet 5.5 (56.0) uses 197K — over 7x GPT-6 Astra; Muse Spark 1.3, Gemini 4 Argon, and MiMo-V2.6-Pro land between 60K and 64K.
- Since you pay for output tokens, routing easy requests to leaner models is among the easiest ways to cut inference spend; the poster pitches its gateway for this.
Related event: Frontier Models Vary Up to 7x in Tokens Per Task, Data Shows(2 posts)→
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