DeepSeek R1 is here: 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 vs Qwen: Qwen-Max
DeepSeek: R1 wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-train…
Model details →Side-by-side comparison
| Capability | DeepSeek: R1 | Qwen: Qwen-Max | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 64K | 33K | 🏆 DeepSeek: R1 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.70 | $1.04 | 🏆 DeepSeek: R1 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $2.50 | $4.16 | 🏆 DeepSeek: R1 |
| 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 |
Frequently asked questions
Is DeepSeek: R1 better than Qwen: Qwen-Max?
DeepSeek: R1 wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between DeepSeek: R1 and Qwen: Qwen-Max?
Input: $0.70 vs $1.04 per 1M tokens. Output: $2.50 vs $4.16 per 1M tokens.
What context windows do DeepSeek: R1 and Qwen: Qwen-Max support?
DeepSeek: R1 supports up to 64K tokens. Qwen: Qwen-Max supports up to 33K tokens.
Do both DeepSeek: R1 and Qwen: Qwen-Max support tool calling?
DeepSeek: R1: yes. Qwen: Qwen-Max: yes.