Benchmarks

What each library model measured on JevBench’s 231 public typed decisions: 48 easy, 72 standard and 111 hard. Every figure sits beside the count it was computed over.

Benchmark
JevBench bb05a335, dataset dc3995d8, 231 public items, 600 s client timeout
Measured
2026-10-09 to 2026-10-13, 1 run per quant.

Top results

Order by

Each measured size at its default quant, the one ardana pull <family>:<size> fetches, on all 231 items, best first. Sizes whose intervals overlap are not reliably different.

Ordered by accuracy, highest first.

  1. jevk5:9b 0.8658
  2. qwen3.8:27b 0.8658
  3. gemma-4:26b-a4b 0.8615
  4. gemma-4:12b 0.8571
  5. qwen3.6:35b-a3b 0.8528
  6. jevk5:4b 0.8442
  7. qwen3.5:9b 0.8398
  8. decider:4b 0.8009
  9. ornith-1.5:9b 0.7879
  10. phi-4:14b 0.7835
  11. gemma-4:e4b 0.7706
  12. qwen3:14b 0.7706
  13. decider:2b 0.7662
  14. qwen3.5:4b 0.7662
  15. gemma-3:12b 0.7576
  16. jevk5:2b 0.7359
  17. qwen3:8b 0.7229
  18. qwen3.5:2b 0.6926
  19. llama-3.1:8b 0.6797
  20. gemma-4:e2b 0.6710
  21. decider:0.8b 0.6667
  22. ling-3.0:tiny 0.6667
  23. phi-4:mini 0.6537
  24. llama-3.2:3b 0.6494
  25. qwen3:4b 0.6364
  26. olmo-3:7b 0.6234
  27. smollm3:3b 0.6234
  28. lfm2.5:2.6b 0.6061
  29. gemma-3:4b 0.6017
  30. minicpm5:1b 0.5887
  31. minicpm5:2b 0.5844
  32. qwen3:1.7b 0.5714
  33. qwen3.5:0.8b 0.5671
  34. lfm2.5:8b-a1b 0.5584
  35. qwen3:0.6b 0.5498
  36. lfm2.5:1.2b 0.5281
  37. gemma-3:1b 0.5065
  38. llama-3.2:1b 0.5065
  39. gemma-4:31b 0.0000
Top results, one row per measured size
ModelAccuracy, 95% intervalBrierECE (calibration_n)Timeouts
jevk5:9b chat layout200 / 231 0.8658 0.8193–0.90990.19420.0602 (231)0
qwen3.8:27b chat layout200 / 231 0.8658 0.8190–0.90750.17510.0476 (231)0
gemma-4:26b-a4b chat layout199 / 231 0.8615 0.8142–0.90420.20290.0790 (231)0
gemma-4:12b chat layout198 / 231 0.8571 0.8072–0.90090.20650.0886 (231)0
qwen3.6:35b-a3b chat layout197 / 231 0.8528 0.8000–0.89740.20840.0341 (231)0
jevk5:4b chat layout195 / 231 0.8442 0.7957–0.89180.20350.0468 (231)0
qwen3.5:9b chat layout194 / 231 0.8398 0.7906–0.88700.24200.0513 (231)0
decider:4b plain layout, 3 quants measured185 / 231 0.8009 0.7477–0.85060.26560.0642 (231)0
ornith-1.5:9b chat layout182 / 231 0.7879 0.7311–0.84320.27460.0572 (231)0
phi-4:14b chat layout181 / 231 0.7835 0.7265–0.83690.37160.1762 (231)0
gemma-4:e4b chat layout178 / 231 0.7706 0.7124–0.82520.32770.1287 (231)0
qwen3:14b chat layout178 / 231 0.7706 0.7130–0.82460.40660.1864 (231)0
decider:2b plain layout, 3 quants measured177 / 231 0.7662 0.7074–0.82350.32840.0759 (231)0
qwen3.5:4b chat layout177 / 231 0.7662 0.7091–0.82170.28720.0635 (231)0
gemma-3:12b chat layout175 / 231 0.7576 0.7026–0.81300.44020.2186 (231)0
jevk5:2b chat layout170 / 231 0.7359 0.6753–0.79480.36320.0721 (231)0
qwen3:8b chat layout167 / 231 0.7229 0.6622–0.78350.48510.2245 (231)0
qwen3.5:2b chat layout160 / 231 0.6926 0.6309–0.75420.42910.0893 (231)0
llama-3.1:8b chat layout157 / 231 0.6797 0.6188–0.73910.45070.1370 (231)0
gemma-4:e2b chat layout155 / 231 0.6710 0.6035–0.73140.47740.2055 (231)0
decider:0.8b plain layout154 / 231 0.6667 0.6063–0.72460.48690.1682 (231)0
ling-3.0:tiny chat layout154 / 231 0.6667 0.6034–0.72930.48350.1838 (231)0
phi-4:mini chat layout151 / 231 0.6537 0.5856–0.71730.53470.2177 (231)0
llama-3.2:3b chat layout150 / 231 0.6494 0.5823–0.71370.49420.1426 (231)0
qwen3:4b chat layout147 / 231 0.6364 0.5683–0.69660.68340.3314 (231)0
olmo-3:7b chat layout144 / 231 0.6234 0.5556–0.68860.64160.2958 (231)0
smollm3:3b chat layout144 / 231 0.6234 0.5541–0.69040.55790.2363 (231)0
lfm2.5:2.6b chat layout140 / 231 0.6061 0.5371–0.67110.62890.2558 (231)0
gemma-3:4b chat layout139 / 231 0.6017 0.5302–0.66810.77480.3900 (231)0
minicpm5:1b chat layout136 / 231 0.5887 0.5232–0.65380.66360.2472 (231)0
minicpm5:2b chat layout135 / 231 0.5844 0.5174–0.65270.63330.2730 (231)0
qwen3:1.7b chat layout132 / 231 0.5714 0.5022–0.63760.78590.3867 (231)0
qwen3.5:0.8b chat layout131 / 231 0.5671 0.4978–0.63450.56110.1101 (231)0
lfm2.5:8b-a1b chat layout129 / 231 0.5584 0.4865–0.62770.70700.3209 (231)0
qwen3:0.6b chat layout127 / 231 0.5498 0.4805–0.61740.69450.2919 (231)0
lfm2.5:1.2b chat layout122 / 231 0.5281 0.4561–0.59830.70350.3030 (231)0
gemma-3:1b chat layout117 / 231 0.5065 0.4367–0.57810.95410.4747 (231)0
llama-3.2:1b chat layout117 / 231 0.5065 0.4310–0.57510.63130.1727 (231)0
gemma-4:31b stopped chat layout0 / 4 0.0000 0.0000–0.00000.80000.2000 (1)0

A stopped run covers fewer, easier items, so it follows the complete ones whatever the order.

Accuracy and calibration

Each measured size at its default quant: how often it is right against how far its confidence is from its accuracy. Up and to the left is better. The shaded quadrant is above the median accuracy and below the median ECE. The line, or a ring when one size beats all the others, marks the sizes no other size beats on both.

Most attractive quadrant0.600.800.000.200.40ECE (left is better calibrated)accuracy (up is better)qwen3.8:27bdecider:0.8bdecider:2bdecider:4bgemma-3:1bgemma-3:4bgemma-3:12bgemma-4:e2bgemma-4:e4bgemma-4:12bgemma-4:26b-a4bjevk5:2blfm2.5:1.2blfm2.5:2.6blfm2.5:8b-a1bling-3.0:tinyllama-3.1:8bllama-3.2:1bllama-3.2:3bminicpm5:1bminicpm5:2bolmo-3:7bphi-4:14bqwen3:0.6bqwen3:1.7bqwen3:4bqwen3:8bqwen3:14bqwen3.5:0.8bqwen3.5:4b

1 run is left out: a stopped run covers fewer items, and a run without a valid distribution has no ECE.

Accuracy and size on disk

Every measured quant: accuracy against the size of its GGUF, the download and roughly the memory it needs. Up and to the left is better. The shaded quadrant is above the median accuracy and below the median size of the quants shown; the line joins the quants no smaller quant beats. Each quant’s figures are in its family’s tables.

Most attractive quadrant0.600.800.5 GB1 GB2 GB5 GB10 GB20 GBsize on disk, log scale (left is smaller)accuracy (up is better)decider:0.8bdecider:2bjevk5:4bjevk5:9bqwen3.5:0.8bdecider:4bgemma-3:1bgemma-3:4bgemma-3:12bgemma-4:e2bgemma-4:e4bgemma-4:12bgemma-4:26b-a4bjevk5:2blfm2.5:1.2blfm2.5:2.6blfm2.5:8b-a1bling-3.0:tinyllama-3.1:8bllama-3.2:1bllama-3.2:3bminicpm5:1bminicpm5:2bolmo-3:7bphi-4:miniphi-4:14bqwen3:0.6bqwen3:1.7bqwen3:8bqwen3:14bqwen3.6:35b-a3bqwen3.8:27b

1 run is left out: a stopped run covers fewer items, and a run without a valid distribution has no accuracy.

By tier

Each measured size at its default quant, best first: its accuracy on the 48 easy, 72 standard and 111 hard items. A long line means the hard items cost it most. Tier figures carry no interval; each family’s tables give their counts.

0.000.250.500.751.00jevk5:9bqwen3.8:27bgemma-4:26b-a4bgemma-4:12bqwen3.6:35b-a3bjevk5:4bqwen3.5:9bdecider:4bornith-1.5:9bphi-4:14bgemma-4:e4bqwen3:14bdecider:2bqwen3.5:4bgemma-3:12bjevk5:2bqwen3:8bqwen3.5:2bllama-3.1:8bgemma-4:e2bdecider:0.8bling-3.0:tinyphi-4:minillama-3.2:3bqwen3:4bolmo-3:7bsmollm3:3blfm2.5:2.6bgemma-3:4bminicpm5:1bminicpm5:2bqwen3:1.7bqwen3.5:0.8blfm2.5:8b-a1bqwen3:0.6blfm2.5:1.2bgemma-3:1bllama-3.2:1bgemma-4:31b

By model

Accuracy is correct answers over attempted items, and a request that failed or timed out counts as wrong; the interval is a 95% bootstrap over items, resampling paraphrase pairs together. Brier and ECE (top-label, ten equal bins) run over the items with a valid probability distribution, whose count sits beside every ECE. Every figure is computed by JevBench’s own scorer.

Only JevBench’s public items are used (only the public half of the hard tier), so these numbers are not comparable with its published leaderboard, which includes held-out items.