Which is cheaper, GPT-5 nano or Qwen3.7-Plus?
As of August 20, 2026, GPT-5 nano is 72% cheaper on blended LLM API pricing. GPT-5 nano costs $0.05 per million input tokens and $0.40 per million output tokens ($0.45 blended 1M-in + 1M-out). Qwen3.7-Plus costs $0.32 / $1.28 per million tokens ($1.60 blended). Sources: https://developers.openai.com/api/docs/pricing and https://www.alibabacloud.com/help/en/model-studio/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-5 nano vs Qwen3.7-Plus cost per million tokens?
GPT-5 nano OpenAI API pricing is $0.05 input and $0.40 output per million tokens via OpenAI. Qwen3.7-Plus Qwen API pricing is $0.32 input and $1.28 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-5 nano or Qwen3.7-Plus?
Qwen3.7-Plus leads on SWE-bench Verified: GPT-5 nano at 34.8% vs Qwen3.7-Plus at 77.7%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for GPT-5 nano vs Qwen3.7-Plus?
GPT-5 nano supports a 400K token context window, while Qwen3.7-Plus supports 1M tokens. Qwen3.7-Plus offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, GPT-5 nano or Qwen3.7-Plus?
Qwen3.7-Plus leads on 7 of 7 shared benchmarks versus GPT-5 nano's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is GPT-5 nano or Qwen3.7-Plus better for production use?
Both GPT-5 nano and Qwen3.7-Plus are production API models. For cost-sensitive production traffic, GPT-5 nano has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between GPT-5 nano and Qwen3.7-Plus in my app?
Yes. Call GPT-5 nano through OpenAI and Qwen3.7-Plus through Qwen with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this GPT-5 nano vs Qwen3.7-Plus pricing data?
List rates are the latest published OpenAI API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://www.alibabacloud.com/help/en/model-studio/pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for GPT-5 nano and Qwen3.7-Plus?
GPT-5 nano supports up to 128K output tokens per request, while Qwen3.7-Plus supports up to 66K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GPT-5 nano or Qwen3.7-Plus?
GPT-5 nano has a measured throughput of approximately 500 tokens/second. Throughput data for Qwen3.7-Plus is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this GPT-5 nano vs Qwen3.7-Plus comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5 nano or Qwen3.7-Plus from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
