GPT-4o vs Qwen3.5-Plus
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-4o | Qwen3.5-Plus |
|---|---|---|
| Provider | OpenAI | Alibaba |
| Input Price (1M) | $2.50 | $0.40 |
| Output Price (1M) | $10.00 | $2.40 |
| Context Window | 128,000 | 1,000,000 |
Verdict
GPT-4o costs $2.50 per 1M input tokens and $10.00 per 1M output tokens. Qwen3.5-Plus costs $0.40 per 1M input tokens and $2.40 per 1M output tokens. Qwen3.5-Plus is 84% cheaper on input tokens than GPT-4o. For output tokens, Qwen3.5-Plus is the more affordable option at $2.40/1M vs $10.00.
On context window, Qwen3.5-Plus supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-4o
- ✓ You are already integrated with OpenAI
When to choose Qwen3.5-Plus
- ✓ You need the lowest input token cost ($ 0.40/1M)
- ✓ Your workload is output-heavy — Qwen3.5-Plus generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with Alibaba
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is GPT-4o cheaper than Qwen3.5-Plus? ▼
Qwen3.5-Plus is cheaper on input tokens at $0.40/1M vs $2.50/1M for GPT-4o — a 84% saving.
What is the context window of GPT-4o vs Qwen3.5-Plus? ▼
GPT-4o has a 128,000-token context window. Qwen3.5-Plus has a 1,000,000-token context window. Qwen3.5-Plus supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-4o or Qwen3.5-Plus? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Qwen3.5-Plus is the cheaper option. For maximum context length, Qwen3.5-Plus supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.