DeepSeek-V3.2 vs Qwen3 235B A22B Instruct 2507

How to read this comparison

This page compares DeepSeek-V3.2 and Qwen3 235B A22B Instruct 2507 on the dimensions that matter most for production LLM selection: per-token cost, context window, declared capabilities (tool calling, structured output, reasoning, vision), and provider availability.

Green highlights in the table indicate which model leads on a given row. "Leads" means lower price or higher context/capability — not necessarily "better for your use case". A model that costs 3× more may still be the right choice if it unlocks a capability you need.

What this comparison does NOT tell you

• Quality / accuracy — we have no benchmark data. Declared capabilities ≠ measured performance.
• Latency — time-to-first-token varies by provider, region and load. Test with your actual traffic.
• Prompt caching savings — if you reuse system prompts, the cheaper model on headline rate may not be cheapest in practice.
• Fine-tuning availability — not all models can be fine-tuned, even if they are open-weight.

Data is refreshed daily. If a model's capabilities or pricing change, this page updates automatically on the next build cycle.