GPT-5 vs Qwen3-Omni-Flash
Compare GPT-5 and Qwen3-Omni-Flash. Find out which one is better for your use case.
Model Comparison
| Feature | GPT-5 | Qwen3-Omni-Flash |
|---|---|---|
| Provider | OpenAI | Alibaba Cloud |
| Model Type | text | multimodal |
| Context Window | 400,000 tokens | 65,536 tokens |
| Input Cost | $1.25 / 1M tokens | $0.43 / 1M tokens |
| Output Cost | $10.00 / 1M tokens | $1.66 / 1M tokens |
Strengths & Best Use Cases
GPT-5
1. High reasoning capability
- Designed for intelligent reasoning across complex domains.
- Supports reasoning tokens and adjustable reasoning effort.
2. Strong coding and agentic performance
- Optimized for multi-step coding tasks, tool-use chains, and agent workflows.
- Handles complex logic, planning, and structured problem solving reliably.
3. Multimodal input
- Accepts text + image as input.
- Produces text outputs with strong instruction following.
4. Extensive tool support
- Works with Web Search, File Search, Image Generation (as a tool), Code Interpreter, MCP, and more.
- Integrated across Chat Completions, Responses API, Realtime, Assistants, Batch, Embeddings, etc.
Qwen3-Omni-Flash
1. Advanced multimodal reasoning
- Vision, audio, video inputs.
2. Supports thinking mode
- Unique for multimodal.
3. 17 voices, 10 languages
- Great for voice agents.
4. Designed for real-world interactions
- Recognition, teaching, analysis.
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