Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design with early fusio…
Model details →Qwen: Qwen3.5-9B vs Xiaomi: MiMo-V2-Omni
Qwen: Qwen3.5-9B wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with agentic capability - visual grounding, multi-step planning, tool…
Model details →Side-by-side comparison
| Capability | Qwen: Qwen3.5-9B | Xiaomi: MiMo-V2-Omni | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 256K | 262K | 🏆 Xiaomi: MiMo-V2-Omni |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.05 | $0.40 | 🏆 Qwen: Qwen3.5-9B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.15 | $2.00 | 🏆 Qwen: Qwen3.5-9B |
| 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: Qwen3.5-9B better than Xiaomi: MiMo-V2-Omni?
Qwen: Qwen3.5-9B wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Qwen: Qwen3.5-9B and Xiaomi: MiMo-V2-Omni?
Input: $0.05 vs $0.40 per 1M tokens. Output: $0.15 vs $2.00 per 1M tokens.
What context windows do Qwen: Qwen3.5-9B and Xiaomi: MiMo-V2-Omni support?
Qwen: Qwen3.5-9B supports up to 256K tokens. Xiaomi: MiMo-V2-Omni supports up to 262K tokens.
Do both Qwen: Qwen3.5-9B and Xiaomi: MiMo-V2-Omni support tool calling?
Qwen: Qwen3.5-9B: yes. Xiaomi: MiMo-V2-Omni: yes.