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 in an inference pass.…
Model details →DeepSeek: R1 0528 vs Qwen: Qwen-Turbo
DeepSeek: R1 0528 and Qwen: Qwen-Turbo are evenly matched on 6 axes — pick the one whose provider, latency, or licensing fits your stack.
Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.
Model details →Side-by-side comparison
| Capability | DeepSeek: R1 0528 | Qwen: Qwen-Turbo | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 164K | 131K | 🏆 DeepSeek: R1 0528 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.45 | $0.03 | 🏆 Qwen: Qwen-Turbo |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $2.15 | $0.13 | 🏆 Qwen: Qwen-Turbo |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | — | 🏆 DeepSeek: R1 0528 |
Frequently asked questions
Is DeepSeek: R1 0528 better than Qwen: Qwen-Turbo?
DeepSeek: R1 0528 and Qwen: Qwen-Turbo are evenly matched on 6 axes — pick the one whose provider, latency, or licensing fits your stack.
What's the price difference between DeepSeek: R1 0528 and Qwen: Qwen-Turbo?
Input: $0.45 vs $0.03 per 1M tokens. Output: $2.15 vs $0.13 per 1M tokens.
What context windows do DeepSeek: R1 0528 and Qwen: Qwen-Turbo support?
DeepSeek: R1 0528 supports up to 164K tokens. Qwen: Qwen-Turbo supports up to 131K tokens.
Do both DeepSeek: R1 0528 and Qwen: Qwen-Turbo support tool calling?
DeepSeek: R1 0528: yes. Qwen: Qwen-Turbo: yes.