DeepSeek R1 Distill Qwen 32B vs DeepSeek R1 Distill Qwen 1.5B
Comparing DeepSeek R1 Distill Qwen 32B by DeepSeek and DeepSeek R1 Distill Qwen 1.5B by DeepSeek across benchmarks, pricing, and capabilities.
DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 32B outperforms in 4 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500), while DeepSeek R1 Distill Qwen 1.5B is better at 0 benchmarks.
DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
DeepSeek R1 Distill Qwen 32B has 31.0B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 1742.7% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek R1 Distill Qwen 32B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Qwen 32B specifies output context (128,000 tokens).
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Both models were released on 2025-01-20.
They likely represent similar generations of model development.
Jan 20, 2025
1.2 years ago
Jan 20, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
Detailed Comparison
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