Yes it looks that way. I pulled the energy data for GLM 5.3 as well just to check the core findings are roughly the same and they do seem to be so spec decode doesn't seem to have the same divergence as the prefill/decode energy (which is rougly a function of thinking/decode lenghts and less a property of individual tokens).
Language Strict Lenient Cap Tok/req J/req J/tok Req x EN Tok x EN J/tok x EN
English 100% 100% 0 548.7 230.33 0.4198 1.00 1.00 1.00
Chinese 96% 96% 1 754.0 694.47 0.9210 3.02 1.37 2.19
Russian 96% 98% 2 738.8 592.15 0.8015 2.57 1.35 1.91
French 100% 100% 0 631.0 1101.84 1.7462 4.78 1.15 4.16
S. Pashto 88% 98% 6 1332.1 208.06 0.1562 0.90 2.43 0.37
Tigrinya 56% 62% 19 3642.9 1445.84 0.3969 6.28 6.64 0.95
Shan 44% 54% 27 3674.8 3791.59 1.0318 16.46 6.70 2.46
Tibetan 2% 70% 15 2856.9 5306.68 1.8575 23.04 5.21 4.42
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Yes it looks that way. I pulled the energy data for GLM 5.3 as well just to check the core findings are roughly the same and they do seem to be so spec decode doesn't seem to have the same divergence as the prefill/decode energy (which is rougly a function of thinking/decode lenghts and less a property of individual tokens).