filipe(@filicroval):Benchmark results for Bonsai Q2_0 and Q1_0 on my GX10, using strict EvalPlus: Ternary Bonsai Q2_0 • HumanEval+: 152/164 92.68% • MBPP+: 305/378 80.69% • Total Plus solved: 457/542 Bonsai Q1_0 • HumanEval+: 149/164 90.85% • MBPP+: 282/378 74.60% • Total Plus solved: 431/542 Both completed all 542 generations with zero errors. Ternary recovered 26 tasks over Q1_0. Of those, 23 came from MBPP+ and only 3 from HumanEval+. For context, PrismML reports Qwen3.6-27B FP16 at 95.12% HumanEval+, 83.33% MBPP+, and 88.74% across its coding category including LiveCodeBench. That's a very very solid model for such weights and considering its file size.

2026.07.15 13:58

Benchmark results for Bonsai Q2_0 and Q1_0 on my GX10, using strict EvalPlus: Ternary Bonsai Q2_0 • HumanEval+: 152/164 92.68% • MBPP+: 305/378 80.69% • Total Plus solved: 457/542 Bonsai Q1_0 • HumanEval+: 149/164 90.85% • MBPP+: 282/378 74.60% • Total Plus solved: 431/542 Both completed all 542 generations with zero errors. Ternary recovered 26 tasks over Q1_0. Of those, 23 came from MBPP+ and only 3 from HumanEval+. For context, PrismML reports Qwen3.6-27B FP16 at 95.12% HumanEval+, 83.33% MBPP+, and 88.74% across its coding category including LiveCodeBench. That's a very very solid model for such weights and considering its file size.