Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...
Model details →Qwen: Qwen3.6 Plus vs Xiaomi: MiMo-V2.5
Xiaomi: MiMo-V2.5 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...
Model details →Side-by-side comparison
| Capability | Qwen: Qwen3.6 Plus | Xiaomi: MiMo-V2.5 | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 1M | 1.1M | 🏆 Xiaomi: MiMo-V2.5 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.33 | $0.14 | 🏆 Xiaomi: MiMo-V2.5 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $1.95 | $0.28 | 🏆 Xiaomi: MiMo-V2.5 |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | Yes | Yes | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is Qwen: Qwen3.6 Plus better than Xiaomi: MiMo-V2.5?
Xiaomi: MiMo-V2.5 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Qwen: Qwen3.6 Plus and Xiaomi: MiMo-V2.5?
Input: $0.33 vs $0.14 per 1M tokens. Output: $1.95 vs $0.28 per 1M tokens.
What context windows do Qwen: Qwen3.6 Plus and Xiaomi: MiMo-V2.5 support?
Qwen: Qwen3.6 Plus supports up to 1M tokens. Xiaomi: MiMo-V2.5 supports up to 1.1M tokens.
Do both Qwen: Qwen3.6 Plus and Xiaomi: MiMo-V2.5 support tool calling?
Qwen: Qwen3.6 Plus: yes. Xiaomi: MiMo-V2.5: yes.
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