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Knowledge Evaluation on MMLU

82.03MMLU AccuracyW16A16-Direct
18.454834.959951.46567.9701Feb 13, 2026Mar 3, 2026Mar 21, 2026Apr 8, 2026Apr 26, 2026May 14, 2026Jun 1, 2026

Evaluation results

MethodLinks
W16A16-DirectModel=Qwen3-30B2026.0482.030
W8A8-DirectModel=Qwen3-30B2026.0481.98-0.06
MXFP4-W2FP8+DynModel=Qwen3-30B2026.0479.91-2.12
MXFP4-DynamicModel=Qwen3-30B2026.0479.78-2.25
MXFP4-OSCModel=Qwen3-30B2026.0479.28-2.75
MXFP4-W2FP8Model=Qwen3-30B2026.0478.93-3.1
MXFP4-DirectModel=Qwen3-30B2026.0478.23-3.8
W16A16-DirectModel=Qwen3-8B2026.0474.970
W8A8-DirectModel=Qwen3-8B2026.0474.61-0.36
OriginalBackbone=Qwen2.5-7B2026.0274.26—
Linear-AcTBackbone=Qwen2.5-7B2026.0273.65—
Dense baselineBase Model=Qwen2.5-7B-Instruct, Sparsity=Dense2026.0673.51—
CHaRSBackbone=Qwen2.5-7B2026.0273.41—
CHaRS-PCTBackbone=Qwen2.5-7B2026.0273.31—
MXFP4-W2FP8+DynModel=Qwen3-8B2026.0472.64-2.33
MXFP4-OSCModel=Qwen3-8B2026.0472.4-2.56
MXFP4-DynamicModel=Qwen3-8B2026.0472.26-2.71
Dense baselineBase Model=Qwen3-4B-Instruct, Sparsity=Dense2026.0672.18—
SUBFITBase Model=Qwen3-4B-Instruct, Sparsity=12.5%2026.0672.08—
MXFP4-W2FP8Model=Qwen3-8B2026.0470.31-4.66
Dense baselineBase Model=Llama-3.1-8B-Instruct, Sparsity=Dense2026.0668.79—
MXFP4-DirectModel=Qwen3-8B2026.0468.24-6.73
SUBFITBase Model=Llama-3.1-8B-Instruct, Sparsity=12.5%2026.0666.65—
OriginalBackbone=Llama3-8B2026.0265.52—
Linear-AcTBackbone=Llama3-8B2026.0264.64—
CHaRSBackbone=Llama3-8B2026.0264.48—
CHaRS-PCTBackbone=Llama3-8B2026.0264.37—
Dense baselineBase Model=Llama-3.2-3B-Instruct, Sparsity=Dense2026.0661.84—
SUBFITBase Model=Llama-3.2-3B-Instruct, Sparsity=12.5%2026.0661.07—
No WatermarkBase Model=Mistral2026.0558.9—
SynthIDBase Model=Mistral2026.0558.90
DTMBase Model=Mistral2026.0558.90
TWBase Model=Mistral2026.0558.90
SAFESEALBase Model=Mistral2026.0558.90
EXPBase Model=Mistral2026.0558.7-0.3
KGWBase Model=Mistral2026.0558.6-0.5
OriginalBackbone=Gemma2-2B2026.0253.03—
Linear-AcTBackbone=Gemma2-2B2026.0251.77—
SUBFITBase Model=DeepSeek-7B-chat, Sparsity=12.5%2026.0651.32—
SUBFITBase Model=Qwen2.5-7B-Instruct, Sparsity=12.5%2026.0651.05—
Dense baselineBase Model=DeepSeek-7B-chat, Sparsity=Dense2026.0650.9—
CHaRSBackbone=Gemma2-2B2026.0250.69—
CHaRS-PCTBackbone=Gemma2-2B2026.0250.21—
FedSDR2026.0547.11—
FedSD2026.0546.96—
No WatermarkBase Model=LLaMA-22026.0546.7—
SynthIDBase Model=LLaMA-22026.0546.70
DTMBase Model=LLaMA-22026.0546.70
TWBase Model=LLaMA-22026.0546.70
SAFESEALBase Model=LLaMA-22026.0546.70
EXPBase Model=LLaMA-22026.0545.9-1.7
Dual Upload2026.0545.49—
Baseline(FedAvg)2026.0545.22—
Dual-LoRA(FedDPA)2026.0544.78—
KGWBase Model=LLaMA-22026.0544.5-4.7
Distill Rect2026.0542.65—
STOCModel Scale=1.7B, Prompts=5-shot, Freezing Layers=Best reported2026.0542.49—
STOCModel Scale=0.6B, Prompts=5-shot, Freezing Layers=Best reported2026.0540.17—
LAMOLModel Scale=1.7B, Prompts=5-shot, Freezing Layers=Best reported2026.0539.28—
LAMOLModel Scale=0.6B, Prompts=5-shot, Freezing Layers=Best reported2026.0538.87—
SIRBase Model=LLaMA-22026.0527.9-40.2
NaiveModel Scale=1.7B, Prompts=5-shot, Freezing Layers=Best reported2026.0523.63—
NaiveModel Scale=0.6B, Prompts=5-shot, Freezing Layers=Best reported2026.0522.49—
SIRBase Model=Mistral2026.0520.9-64.5