---
base_model: simplescaling/s1.1-32B
pipeline_tag: text-generation
inference: true
language:
- en
license: apache-2.0
model_creator: simplescaling
model_name: s1.1-32B
model_type: qwen2
datasets:
  - simplescaling/s1K
quantized_by: brittlewis12

---

# s1.1 32B GGUF

**Original model**: [s1.1 32B](https://huggingface.co/simplescaling/s1.1-32B)

**Model creator**: [simplescaling](https://huggingface.co/simplescaling)

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

> s1 is a reasoning model finetuned from Qwen2.5-32B-Instruct on just 1,000 examples. It matches o1-preview & exhibits test-time scaling via budget forcing.

This repo contains GGUF format model files for simplescaling’s s1.1 32B, an open reproduction of OpenAI’s o1-preview including model, source code, and data (see [s1K](https://huggingface.co/datasets/simplescaling/s1K)).

Learn more on simplescaling’s [s1 github repo](https://github.com/simplescaling/s1), [arxiv preprint](https://arxiv.org/abs/2501.19393), and on [twitter](https://twitter.com/Muennighoff/status/1889310803746246694).

### What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, 
introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. 
Converted with llama.cpp build 4689 (revision [90e4dba](https://github.com/ggerganov/llama.cpp/commits/90e4dba461b07e635fd1daf3b491c978c7dd0013)),
using [autogguf-rs](https://github.com/brittlewis12/autogguf-rs).

### Prompt template: ChatML

```
<|im_start|>system
{{system_message}}<|im_end|>
<|im_start|>user
{{prompt}}<|im_end|>
<|im_start|>assistant

```

---

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---

## Original Model Evaluation

> 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.

| 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 |