GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency use cases such as classification, d…
Model details →OpenAI: GPT-5.4 Nano vs Xiaomi: MiMo-V2-Omni
OpenAI: GPT-5.4 Nano wins on 3 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 | OpenAI: GPT-5.4 Nano | Xiaomi: MiMo-V2-Omni | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 400K | 262K | 🏆 OpenAI: GPT-5.4 Nano |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.20 | $0.40 | 🏆 OpenAI: GPT-5.4 Nano |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $1.25 | $2.00 | 🏆 OpenAI: GPT-5.4 Nano |
| 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 OpenAI: GPT-5.4 Nano better than Xiaomi: MiMo-V2-Omni?
OpenAI: GPT-5.4 Nano wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between OpenAI: GPT-5.4 Nano and Xiaomi: MiMo-V2-Omni?
Input: $0.20 vs $0.40 per 1M tokens. Output: $1.25 vs $2.00 per 1M tokens.
What context windows do OpenAI: GPT-5.4 Nano and Xiaomi: MiMo-V2-Omni support?
OpenAI: GPT-5.4 Nano supports up to 400K tokens. Xiaomi: MiMo-V2-Omni supports up to 262K tokens.
Do both OpenAI: GPT-5.4 Nano and Xiaomi: MiMo-V2-Omni support tool calling?
OpenAI: GPT-5.4 Nano: yes. Xiaomi: MiMo-V2-Omni: yes.