Frontier Model Efficiency Gains
Capability per unit of training and inference compute keeps improving, letting newer models match prior frontier performance far more cheaply and gradually loosening the link between raw scale and capability.
strengthening · confidence 98 · +2 7d · +10 30d · Medium term (3-9 months) · tracking since June 28, 2026 · updated October 10, 2026
Score history
Daily conviction score, 0 to 100. Higher means the thesis is more strongly corroborated.
Now 98 · +3 since Oct 9 · ranged 95 to 98
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Why the conviction moved
- Oct 10Strengthened +3
Haiku 5.5 raises its OSWorld score to 72.4% at one-tenth of its predecessor's price, with a one-million-token context and adjustable effort. That is more capability per dollar at Anthropic's smallest tier.
- Oct 8Strengthened +2
Google reports that EmbeddingGemma 2 adds nearly 10 points over the first version on the Massive Text Embedding Benchmark's code track while still fitting in phone memory. That is more capability per parameter at sub-billion scale.
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Source trail
Supporting · October 10, 2026
Anthropic prices Claude Haiku 5.5 at one-tenth of Haiku 4.5 and lifts its OSWorld score to 72.4%
Haiku 5.5 raises its OSWorld score to 72.4% at one-tenth of its predecessor's price, with a one-million-token context and adjustable effort. That is more capability per dollar at Anthropic's smallest tier.
Anthropic NewsSupporting · October 8, 2026
Google releases EmbeddingGemma 2, a 740-million-parameter open embedder for text, code, images and audio under Apache 2.0
Google reports that EmbeddingGemma 2 adds nearly 10 points over the first version on the Massive Text Embedding Benchmark's code track while still fitting in phone memory. That is more capability per parameter at sub-billion scale.
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