Alternative comparison
Qwen vs OpenAI API for structured output
Qwen 3.7 Plus is a strong first test when teams want a Chinese LLM route for structured output, data extraction, and OpenAI-compatible integration.
Route shortlist
Benchmark comparison
| Model | Total /100 | Extraction | Instructions | Math | Tools | Fully correct | Tokens | Cost (USD) | CPS ($/100 points) |
|---|---|---|---|---|---|---|---|---|---|
Qwen 3.7 Plusqwen3.7-plus | 92.72 | 99.56 | 100.00 | 72.00 | 99.33 | 52/60 | 122,334 | $0.116596 | $0.125748 |
BenchLocal V3.2 · Original 27 models: 2 October 2026; three full-suite supplements: 15 October 2026 · 60 tasks per model. Total = mean of the four category scores. The original models retain 45 V3 tasks and 15 revised tool tasks; the three additional model IDs each completed all 60 identical tasks. Near-ceiling scores do not establish general capability; V3 scores are not directly comparable. CPS = Cost per Score; shown as USD per 100 score points: retained execution cost ÷ unrounded total score × 100. Free models are shown at $0. Paid-model costs are historical charges, excluding failed requests and discarded retests.
Decision guide
Recommended route
Use Qwen 3.7 Plus for schema-heavy tests, then compare validator pass rate and total cost against your existing OpenAI route.
Structured output signal
Qwen 3.7 Plus scored 100 on structured output and 95 on data extraction in the earlier pre-V3 evaluation in the GPTokens benchmark summary.
Integration path
Most SDK integrations need only the GPTokens base URL, API key, and model name.
Related pages