Qwen3-VL-8B-Instruct

MERA Created at 22.01.2026 05:14

Ratings for leaderboard tasks

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Board Result Attempted Score Coverage Place in the rating
Multi 0.18 0.269 0.667 19
Images 0.186 0.186 1 27
Video 0.575 0.575 1 11

Tasks

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Task Modality Result Metric
0.123
EM JudgeScore
0.283
EM JudgeScore
0.234
EM JudgeScore
0.037
EM JudgeScore
0.07
EM JudgeScore
0.647
EM JudgeScore
0.41
EM JudgeScore
0.101
EM JudgeScore
0.512
EM JudgeScore
0.401
EM JudgeScore
0.567
EM JudgeScore
0.16
EM JudgeScore
culture 0.077 / 0.162
business 0.128 / 0.281
medicine 0.096 / 0.212
social_sciences 0.134 / 0.302
fundamental_sciences 0.101 / 0.179
applied_sciences 0.136 / 0.273
0.172
EM JudgeScore
biology 0.156 / 0.216
chemistry 0.15 / 0.192
physics 0.227 / 0.312
economics 0.162 / 0.2
ru 0.099 / 0.134
all 0.101 / 0.175
0.055
EM JudgeScore
biology 0 / 0.053
chemistry 0.104 / 0.179
physics 0.02 / 0.071
science 0 / 0

Information about the submission

Mera version
v1.0.0
Torch Version
2.8.0
The version of the codebase
7e640aa
CUDA version
12.8
Precision of the model weights
bfloat16
Seed
1234
Batch
1
Transformers version
4.57.1
The number of GPUs and their type
1 x NVIDIA A100-SXM4-80GB
Architecture
openai-chat-completions

Team:

MERA

Name of the ML model:

Qwen3-VL-8B-Instruct

Model size

8.0B

Model type:

Opened

SFT

Inference parameters

Generation Parameters:
labtabvqa - until=["\n\n"];do_sample=false;temperature=0; \nrealvqa - until=["\n\n"];do_sample=false;temperature=0; \nruclevr - until=["\n\n"];do_sample=false;temperature=0; \nrunaturalsciencevqa_biology - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=64; \nrunaturalsciencevqa_chemistry - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=64; \nrunaturalsciencevqa_earth_science - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=64; \nrunaturalsciencevqa_physics - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=64; \nruhhh_image - until=["\n\n"];do_sample=false;temperature=0; \nrucommonvqa - until=["\n\n"];do_sample=false;temperature=0; \nrumathvqa - until=["\n\n"];do_sample=false;temperature=0; \nunisciencevqa_applied_sciences - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nunisciencevqa_business - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nunisciencevqa_cultural_studies - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nunisciencevqa_fundamental_sciences - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nunisciencevqa_health_and_medicine - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nunisciencevqa_social_sciences - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_biology - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_chemistry - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_earth_science - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_economics - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_history_all - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_history_ru - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nschoolsciencevqa_physics - until=["<|endoftext|>"];temperature=0;do_sample=false;max_gen_toks=256; \nweird - until=["\n\n"];do_sample=false;temperature=0; \nrealvideoqa - until=["\n\n"];do_sample=false;temperature=0; \nruhhh_video - until=["\n\n"];do_sample=false;temperature=0; \ncommonvideoqa - until=["\n\n"];do_sample=false;temperature=0;

The size of the context:
262144