metadata
license: apache-2.0
ReasonLite is an ultra-lightweight math reasoning model. With only 0.6B parameters, it leverages high-quality data distillation to achieve performance comparable to models over 10× its size, such as Qwen3-8B, reaching 75.2 on AIME24 and extending the scaling law of small models.
🔥 Best-performing 0.6B reasoning model
🔓 Fully open-source — weights, scripts, datasets, synthesis pipeline
⚙️ Distilled in two stages for both efficiency and high performance
🚀 Model
The model is trained in two progressive distillation stages. First, short-CoT data is used to distill Qwen3-0.6B into AMD-0.6B-Turbo, improving AIME24 accuracy from 11.0 → 57.1. Then, long-CoT data is used to obtain AMD-0.6B, further boosting accuracy to 75.2.
| Model | Description | AIME24 | Link |
|---|---|---|---|
| amd/ReasonLite-0.6B-Turbo | Short CoT balancing performance and efficiency | 57.1 | 🤗 HuggingFace |
| amd/ReasonLite-0.6B | Long CoT for high performance | 75.2 | 🤗 HuggingFace |
📊 Evaluation Results
Metrics
- avg@16 — average accuracy from 16 sampled answers
- pass@8 — probability at least one correct answer appears among 8 samples
| Model | Parameters | AMC23 avg@16 | AMC23 pass@8 | AIME25 avg@16 | AIME25 pass@8 | AIME24 avg@16 | AIME24 pass@8 |
|---|---|---|---|---|---|---|---|
| Qwen2.5-14B | 14B | 58.3 | 82.3 | 12.3 | 32.3 | 12.7 | 32.4 |
| Deepseek-qwen-14B | 14B | 93.9 | 98.7 | 50.2 | 71.0 | 65.0 | 83.0 |
| Qwen3-0.6B | 0.6B | 52.7 | 85.0 | 16.0 | 33.0 | 11.0 | 31.5 |
| Qwen3-1.7B | 1.7B | 83.4 | 96.3 | 36.0 | 55.1 | 47.3 | 73.9 |
| Qwen3-4B | 4B | 96.1 | 100 | 63.5 | 85.4 | 72.7 | 85.1 |
| Qwen3-8B | 8B | 94.8 | 100 | 68.3 | 84.2 | 74.6 | 85.0 |
| Qwen3-14B | 14B | 98.6 | 98.7 | 71.5 | 84.1 | 78.3 | 88.4 |
| DeepscaleR-1.5B | 1.5B | 83.8 | 95.0 | 29.0 | 48.9 | 40.4 | 69.0 |
| POLARIS-1.7B-Preview | 1.7B | 92.2 | 97.4 | 52.3 | 80.2 | 65.0 | 76.7 |
| OpenMath-Nemotron-1.5B | 1.5B | 88.8 | 96.7 | 39.8 | 65.8 | 61.5 | 81.3 |
| ReasonLite-0.6B-Turbo | 0.6B | 81.6 | 99.3 | 42.7 | 69.2 | 57.1 | 79.6 |
| ReasonLite-0.6B | 0.6B | 95.2 | 100 | 62.9 | 84.1 | 75.2 | 90.2 |
📚 Dataset
| Dataset | Description | Size | Link |
|---|---|---|---|
| amd/ReasonLite-Dataset | Short CoT | 4.3M | 🤗 HuggingFace |
| amd/ReasonLite-Dataset | Long Cot | 1.8M | 🤗 HuggingFace |
📌 Citation
@misc{reasonlite2025,
title={ReasonLite: Ultra-Lightweight Math Reasoning Model},
author={AMD AI Lab},
year={2025},
url={https://huggingface.co/amd/ReasonLite-0.6B}
}