GPT-4.1 nano vs Qwen3.5-Flash
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-4.1 nano | Qwen3.5-Flash |
|---|---|---|
| Provider | OpenAI | Alibaba |
| Input Price (1M) | $0.10 | $0.10 |
| Output Price (1M) | $0.40 | $0.40 |
| Context Window | 1,000,000 | 1,000,000 |
Verdict
GPT-4.1 nano costs $0.10 per 1M input tokens and $0.40 per 1M output tokens. Qwen3.5-Flash costs $0.10 per 1M input tokens and $0.40 per 1M output tokens. GPT-4.1 nano and Qwen3.5-Flash have identical input token pricing. For output tokens, GPT-4.1 nano is the more affordable option at $0.40/1M vs $0.40.
On context window, GPT-4.1 nano 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-4.1 nano
- ✓ You are already integrated with OpenAI
When to choose Qwen3.5-Flash
- ✓ 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-4.1 nano cheaper than Qwen3.5-Flash? ▼
GPT-4.1 nano and Qwen3.5-Flash have identical input token pricing at $0.10/1M tokens.
What is the context window of GPT-4.1 nano vs Qwen3.5-Flash? ▼
GPT-4.1 nano has a 1,000,000-token context window. Qwen3.5-Flash has a 1,000,000-token context window. GPT-4.1 nano supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-4.1 nano or Qwen3.5-Flash? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GPT-4.1 nano is the cheaper option. For maximum context length, GPT-4.1 nano supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.