DeepSeek
R1 Distill Qwen 32B
DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.\n\nOther benchmark results include:\n\n- AIME 2024 pass@1: 72.6\n- MATH-500 pass@1: 94.3\n- CodeForces Rating: 1691\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.
- Input / 1M tokens
- $0.290
- Output / 1M tokens
- $0.290
- Context window
- 33K tokens
- Provider
- DeepSeek
- Knowledge cutoff
- 2024-07-31
Performance
Median streaming throughput and first-token latency measured by Artificial Analysis.
- Output tokens / sec
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- Time to first token
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