Qwen3 32B vs R1 0528
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Qwen3 32B and R1 0528.
Qwen3 32B
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
R1 0528
May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...
Technical Specifications
| Specification | Qwen3 32B | R1 0528 |
|---|---|---|
| Provider | Alibaba | DeepSeek |
| Context Window | 131,072 tokens | 163,840 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-04-28 | 2025-05-28 |
API Pricing Comparison
Input Price per Million Tokens
Qwen3 32B
$0.08
R1 0528
$0.50
Output Price per Million Tokens
Qwen3 32B
$0.28
R1 0528
$2.15
Want to test both models live?
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Qwen3 32B Quirks & Gotchas
No developer gotchas reported.
R1 0528 Quirks & Gotchas
No developer gotchas reported.