Qwen3.7-Max vs GPT-5.1
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Qwen3.7-Max | GPT-5.1 |
|---|---|---|
| Provider | Alibaba | OpenAI |
| Input Price (1M) | $1.25 | $1.25 |
| Output Price (1M) | $3.75 | $10.00 |
| Context Window | 1,000,000 | 400,000 |
Verdict
Qwen3.7-Max costs $1.25 per 1M input tokens and $3.75 per 1M output tokens. GPT-5.1 costs $1.25 per 1M input tokens and $10.00 per 1M output tokens. Qwen3.7-Max and GPT-5.1 have identical input token pricing. For output tokens, Qwen3.7-Max is the more affordable option at $3.75/1M vs $10.00.
On context window, Qwen3.7-Max 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 Qwen3.7-Max
- ✓ Your workload is output-heavy — Qwen3.7-Max generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with Alibaba
When to choose GPT-5.1
- ✓ You are already integrated with OpenAI
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 Qwen3.7-Max cheaper than GPT-5.1? ▼
Qwen3.7-Max and GPT-5.1 have identical input token pricing at $1.25/1M tokens.
What is the context window of Qwen3.7-Max vs GPT-5.1? ▼
Qwen3.7-Max has a 1,000,000-token context window. GPT-5.1 has a 400,000-token context window. Qwen3.7-Max supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Qwen3.7-Max or GPT-5.1? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Qwen3.7-Max is the cheaper option. For maximum context length, Qwen3.7-Max supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.