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DeepSeektext->text

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.

Context Window

33K

Input Price

$0.2900/M tokens

Output Price

$0.2900/M tokens

Modality

text->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.2900/M tokens
Output$0.2900/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.003190

Context Window Size
Maximum tokens the model can process in a single request
Context Window33K tokens
3% of 1M max

~25K

Words Equivalent

~16

Pages of Text

~328

Code Functions

Best Use Cases
What this model excels at
General-purpose

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