Valdemardi/s1.1-32B-AWQ

Model Summary

Quantization Details

This quantized model was created using AutoAWQ version 0.2.8 with quant_config:

{
  "zero_point": True,
  "q_group_size": 128,
  "w_bit": 4,
  "version": "GEMM"
}

Model details

s1.1 is our sucessor of s1 with better reasoning performance by leveraging reasoning traces from r1 instead of Gemini.

• Logs: https://wandb.ai/hashimoto-group/o1/runs/m1ilia77/overview
• Repository: simplescaling/s1
• Paper: https://arxiv.org/abs/2501.19393

This model is a successor of s1-32B with slightly better performance. Thanks to Ryan Marten for helping generate r1 traces for s1K.

Use

The model usage is documented here.

Evaluation

Metric	s1-32B	s1.1-32B	o1-preview	o1	DeepSeek-R1	DeepSeek-R1-Distill-Qwen-32B
# examples	1K	1K	?	?	>800K	800K
AIME2024	56.7	56.7	40.0	74.4	79.8	72.6
AIME2025 I	26.7	60.0	37.5	?	65.0	46.1
MATH500	93.0	95.4	81.4	94.8	97.3	94.3
GPQA-Diamond	59.6	63.6	75.2	77.3	71.5	62.1

Note that s1-32B and s1.1-32B use budget forcing in this table; specifically ignoring end-of-thinking and appending "Wait" once or twice.