GPT-5 Nano vs Qwen3-Plus
Compare GPT-5 Nano and Qwen3-Plus. Find out which one is better for your use case.
Model Comparison
| Feature | GPT-5 Nano | Qwen3-Plus |
|---|---|---|
| Provider | OpenAI | Alibaba Cloud |
| Model Type | text | text |
| Context Window | 400,000 tokens | 1,000,000 tokens |
| Input Cost | $0.05 / 1M tokens | $0.12 / 1M tokens |
| Output Cost | $0.40 / 1M tokens | $0.29 / 1M tokens |
Strengths & Best Use Cases
GPT-5 Nano
1. Extremely fast performance
- Fastest model in the GPT-5 family.
- Great for real-time workflows, rapid responses, and high-throughput systems.
2. Most cost-efficient GPT-5 model
- Lowest input and output token costs.
- Suitable for large-scale or budget-sensitive applications.
3. Ideal for lightweight, well-scoped tasks
- Excels at summarization, classification, text extraction, and simple logic tasks.
- Best used when tasks are narrow and well-defined.
4. Multimodal input
- Accepts text + image as input.
- Outputs text only.
5. Broad tool support
- Supports Web Search, File Search, Image Generation (as a tool), Code Interpreter, and MCP.
- (Does not support Computer Use.)
Qwen3-Plus
1. Major upgrade over previous Plus models
- Better reasoning, code generation, and tool-call performance.
2. Supports thinking vs non-thinking modes
- Thinking for hard problems.
- Non-thinking for speed.
3. Improved human preference alignment
- Better writing quality, multi-turn memory, and formatting stability.
4. Excellent for agent-style apps
- Accurate function calling and tool use.
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