complete 5-model quality leaderboard

README.md

@@ -35,11 +35,14 @@ Generative evaluation through llama-server chat completions. Replicates standard
 
 | Model | Params | Quant | MMLU | ARC-C | HellaSwag | GSM8K | HumanEval |
 |-------|-------:|-------|-----:|------:|----------:|------:|----------:|
+| Gemma 4 31B-it | 30.70B | Q6_K | 87.8 | 97.6 | 92.0 | 97.5 | 95.7 |
 | Qwen3.6-27B | 26.90B | Q6_K | 87.9 | 96.9 | 95.4 | 97.3 | 18.9 |
 | Qwen3.6-35B-A3B | 34.66B | UD-Q4_K_M | 85.0 | 95.7 | 93.4 | 96.7 | 37.2 |
+| Qwen3-Coder-Next | 79.67B | UD-Q2_K_XL | 83.7 | 96.0 | 89.3 | 96.0 | 10.4 |
+| Nemotron-Cascade-2 | 31.58B | Q4_K_M | 74.4 | 91.5 | 75.7 | 87.1 | 79.3 |
 | gpt-oss-20b | 20.91B | Q4_K_M | 78.6 | 94.6 | 74.5 | 94.8 | 12.2 |
 
-> All models benchmarked with 50% stratified sampling (seed=42), thinking disabled. More models running — Gemma 4 31B, Nemotron-Cascade-2 30B, Qwen3-Coder-Next.
+> All models benchmarked with 50% stratified sampling (seed=42), thinking disabled. Full per-model reports in [`reports/`](reports/).
 
 ### Methodology