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README
License: apache-2.0Summary
- Base model:
Qwen/Qwen3-8B-Base - Method:
INFUSER - Code repository: https://github.com/FFishy-git/INFUSER
- Data repository:
Siyuc/infuser-data
Evaluation
Released Checkpoint Scores
| Category | Benchmark | Score |
|---|---|---|
| General | MMLU-Pro | 67.81% |
| General | GPQA-Diamond | 47.47% |
| General | SuperGPQA | 38.86% |
| General | BBEH | 12.51% |
| Math & physics | MATH500 | 84.25% |
| Math & physics | AIME2024 | 19.06% |
| Math & physics | AIME2025 | 18.02% |
| Math & physics | HMMT | 9.64% |
| Math & physics | OlympiadBench (Math) | 54.45% |
| Math & physics | OlympiadBench (Phys) | 14.41% |
| Medical | MedQA | 66.46% |
| Medical | MedXpertQA | 14.57% |
| Coding | HumanEval+ | 78.86% |
| Coding | LiveCodeBench v1-5 | 28.47% |
Comparison Summary
Category and overall means are computed over the same benchmark groups. R-Few (paper) and SPICE (paper) are self-reported values from their original papers, so missing categories are shown as -.
| Category | This model | INFUSER avg | Base | R-Zero | AZR | R-Few (paper) | SPICE (paper) | General-Reasoner |
|---|---|---|---|---|---|---|---|---|
| General reasoning | 41.66% | 40.62% | 34.43% | 37.14% | 37.61% | 38.88% | 38.75% | 41.40% |
| Math & physics reasoning | 33.30% | 31.49% | 26.08% | 28.46% | 30.28% | - | - | 29.24% |
| Medical | 40.52% | 40.52% | 39.34% | 40.17% | 39.89% | - | - | 40.96% |
| Coding | 53.66% | 53.29% | 50.59% | 52.55% | 53.18% | - | - | 52.78% |
| Overall (14 benchmarks) | 39.63% | 38.50% | 33.86% | 36.05% | 37.02% | - | - | 37.75% |
Usage
python
from transformers import AutoModelForCausalLM, AutoTokenizermodel = AutoModelForCausalLM.from_pretrained("Siyuc/INFUSER-Qwen3-8B-base")tokenizer = AutoTokenizer.from_pretrained("Siyuc/INFUSER-Qwen3-8B-base")
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Siyuc
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Qwen/Qwen3-8B-Base
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