model,NUM_Q_multich_EM,NUM_Q_multich_CC,NUM_Q_multich_PM,NUM_Q_onech_EM,NUM_Q_seq_EM,NUM_Q_seq_CC,NUM_Q_seq_PM,NUM_Q_map_EM,NUM_Q_map_CC,NUM_Q_map_PM,OPEN_Q_EM,OPEN_Q_F1,OPEN_Q_LR,LEADERBOARD
claude-3-5-sonnet,84.0,85.0,90.0,94.0,73.0,73.0,73.0,43.0,44.0,46.0,63.0,69.0,78.0,70.38461538461539
gemini-pro-1.5,73.0,78.0,84.0,91.0,66.0,66.0,66.0,59.0,60.0,66.0,55.00000000000001,67.0,77.0,69.84615384615384
deepseek-r1,79.0,82.0,86.0,67.0,82.0,82.0,82.0,57.99999999999999,61.0,59.0,22.0,61.0,69.0,68.46153846153847
qwen2.5:72b-instruct-q4_0,59.0,75.0,74.0,90.0,68.0,68.0,68.0,38.0,40.0,44.0,39.0,50.0,63.0,59.69230769230769
t-tech/T-pro-it-1.0,64.0,69.0,78.0,89.0,66.0,66.0,66.0,41.0,42.0,48.0,34.0,49.0,64.0,59.69230769230769
mistral-123b,69.0,74.0,82.0,89.0,63.0,63.0,63.0,24.0,24.0,28.000000000000004,54.0,62.0,71.0,58.92307692307692
gpt-4o,77.0,81.0,86.0,94.0,64.0,64.0,66.0,22.0,22.0,28.999999999999996,11.0,64.0,72.0,57.84615384615385
qwen2.5:32b-instruct-q4_0,59.0,66.0,75.0,86.0,60.0,60.0,60.0,35.0,36.0,42.0,31.0,41.0,55.00000000000001,54.30769230769231
qwen2:72b-instruct-q4_0,56.99999999999999,70.0,73.0,86.0,63.0,63.0,63.0,33.0,34.0,39.0,12.0,45.0,55.00000000000001,53.30769230769231
rscr/ruadapt_qwen2.5_32b:Q4_K_M,54.0,56.99999999999999,72.0,86.0,60.0,60.0,60.0,35.0,35.0,44.0,31.0,39.0,56.00000000000001,53.0
GigaChat-Pro,61.0,64.0,76.0,79.0,45.0,45.0,45.0,25.0,25.0,30.0,48.0,55.00000000000001,68.0,51.23076923076923
GigaChat-Max,73.0,76.0,83.0,85.0,38.0,38.0,38.0,16.0,16.0,23.0,48.0,55.00000000000001,69.0,50.61538461538461
YandexGPT4-Pro,31.0,35.0,77.0,85.0,35.0,35.0,54.0,21.0,21.0,47.0,45.0,56.00000000000001,69.0,47.0
YandexGPT4-Pro-32k,31.0,34.0,77.0,85.0,34.0,34.0,55.00000000000001,21.0,21.0,47.0,45.0,56.99999999999999,69.0,46.92307692307692
gemma2:27b-instruct-q4_0,49.0,56.99999999999999,69.0,82.0,48.0,48.0,48.0,13.0,13.0,18.0,39.0,48.0,63.0,45.76923076923077
GigaChat-Lite,56.99999999999999,61.0,72.0,75.0,38.0,38.0,38.0,13.0,13.0,17.0,35.0,42.0,56.99999999999999,42.76923076923077
ai-sage/GigaChat-20B-A3B-instruct,30.0,33.0,44.0,76.0,42.0,42.0,42.0,12.0,12.0,16.0,38.0,47.0,61.0,38.07692307692308
llama405,21.0,62.0,77.0,60.0,24.0,33.0,51.0,5.0,7.000000000000001,20.0,9.0,56.00000000000001,66.0,37.76923076923077
gemma2:9b-instruct-q4_0,41.0,54.0,64.0,77.0,32.0,33.0,35.0,5.0,5.0,10.0,25.0,34.0,49.0,35.69230769230769
llama3.1:70b-instruct-q4_0,42.0,57.99999999999999,68.0,49.0,14.000000000000002,17.0,33.0,1.0,2.0,14.000000000000002,11.0,54.0,64.0,32.84615384615385
llama3:70b-instruct-q4_0,35.0,63.0,60.0,79.0,12.0,14.000000000000002,25.0,4.0,5.0,6.0,7.000000000000001,47.0,57.99999999999999,31.923076923076923
YandexGPT4-Lite,33.0,38.0,57.99999999999999,74.0,6.0,6.0,7.000000000000001,2.0,2.0,5.0,35.0,52.0,66.0,29.53846153846154
qwen2.5:7b-instruct-q4_0,27.0,36.0,57.99999999999999,71.0,30.0,30.0,30.0,5.0,6.0,10.0,15.0,19.0,38.0,28.846153846153847
rscr/vikhr_nemo_12b:latest,23.0,31.0,53.0,56.00000000000001,11.0,19.0,20.0,2.0,3.0,11.0,12.0,28.999999999999996,41.0,23.923076923076923
ilyagusev/saiga_nemo_12b,3.0,4.0,59.0,70.0,17.0,17.0,18.0,1.0,1.0,10.0,23.0,34.0,48.0,23.46153846153846
qwen2:7b-instruct-q4_0,11.0,13.0,55.00000000000001,67.0,22.0,22.0,23.0,2.0,2.0,8.0,5.0,13.0,28.999999999999996,20.923076923076923
phi3:14b-medium-4k-instruct-q4_0,0.0,0.0,60.0,70.0,3.0,4.0,41.0,0.0,0.0,9.0,7.000000000000001,20.0,31.0,18.846153846153847
owl/t-lite:q4_0-instruct,3.0,6.0,42.0,66.0,10.0,11.0,12.0,1.0,1.0,3.0,4.0,35.0,48.0,18.615384615384617
ilyagusev/saiga_llama3,2.0,9.0,52.0,65.0,9.0,9.0,20.0,0.0,0.0,4.0,8.0,24.0,38.0,18.46153846153846
mistral:7b-instruct-v0.3-q4_0,0.0,0.0,44.0,54.0,0.0,0.0,31.0,0.0,0.0,4.0,3.0,14.000000000000002,24.0,13.384615384615385
yi:9b,8.0,17.0,39.0,39.0,12.0,14.000000000000002,14.000000000000002,0.0,0.0,1.0,2.0,6.0,14.000000000000002,12.76923076923077
mixtral:8x7b-instruct-v0.1-q4_0,0.0,13.0,53.0,16.0,2.0,15.0,27.0,0.0,2.0,12.0,2.0,9.0,12.0,12.538461538461538
solar:10.7b-instruct-v1-q4_0,0.0,0.0,49.0,50.0,0.0,0.0,19.0,0.0,0.0,3.0,4.0,13.0,22.0,12.307692307692308
wavecut/vikhr:7b-instruct_0.4-Q4_1,0.0,0.0,39.0,41.0,2.0,3.0,7.000000000000001,0.0,0.0,1.0,10.0,19.0,30.0,11.692307692307692
random,4.04341349223239,7.59736114066823,32.698446477974,24.5103137458832,14.0740740740741,14.0740740740741,14.0740740740741,0.828500414250207,0.828500414250207,3.23115161557581,,,,11.5959909523056
llama3.1:8b-instruct-q4_0,0.0,0.0,50.0,4.0,0.0,1.0,3.0,0.0,0.0,6.0,0.0,24.0,40.0,9.846153846153847
qwen:7b,0.0,0.0,30.0,36.0,12.0,12.0,14.000000000000002,0.0,0.0,1.0,0.0,3.0,16.0,9.538461538461538
llama3:8b-instruct-q4_0,0.0,0.0,50.0,12.0,0.0,1.0,3.0,0.0,0.0,4.0,0.0,20.0,33.0,9.461538461538462
gemma:7b-instruct-v1.1-q4_0,2.0,9.0,39.0,13.0,7.000000000000001,10.0,11.0,1.0,1.0,4.0,0.0,4.0,16.0,9.0
yi:6b,1.0,18.0,13.0,28.000000000000004,0.0,6.0,4.0,0.0,1.0,1.0,1.0,3.0,10.0,6.615384615384615
llama3.2:3b-instruct-q4_0,0.0,0.0,30.0,0.0,0.0,0.0,10.0,0.0,0.0,1.0,0.0,6.0,19.0,5.076923076923077
llama2:13b,0.0,0.0,25.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,7.000000000000001,12.0,3.4615384615384617
llama3.2:1b-instruct-q4_0,0.0,1.0,14.000000000000002,0.0,0.0,3.0,0.0,0.0,0.0,0.0,0.0,2.0,10.0,2.3076923076923075
Среднее значение,29.373102639354244,35.734822352108566,58.41159177855753,59.5467514824624,27.536606373815676,28.815676141257537,33.95521102497847,12.530895358470936,12.972755823587216,18.470491898036645,19.833333333333332,34.61904761904762,46.42857142857143,32.053216247549145