Side-by-side comparison
Qwen3 235B A22B Thinking 2507 vs DeepSeek V3.1 Terminus
Qwen
Qwen3 235B A22B Thinking 2507
🔧 Tools
{} JSON
Input / 1M
$0.1495
Output / 1M
$1.4950
DeepSeek
DeepSeek V3.1 Terminus
🔧 Tools
{} JSON
Input / 1M
$0.2700
Output / 1M
$0.9500
| Qwen3 235B A22B Thinking 2507 | DeepSeek V3.1 Terminus | |
|---|---|---|
| Provider | Qwen | DeepSeek |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 163,840 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.1495 | 0.2700 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 1.4950 | 0.9500 |
Frequently asked questions
Which is cheaper, Qwen3 235B A22B Thinking 2507 or DeepSeek V3.1 Terminus?
DeepSeek V3.1 Terminus is cheaper than Qwen3 235B A22B Thinking 2507 on a 50/50 input/output blend by about $0.2123 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Qwen3 235B A22B Thinking 2507 or DeepSeek V3.1 Terminus?
DeepSeek V3.1 Terminus has the larger context window at 164k tokens versus 131k tokens for Qwen3 235B A22B Thinking 2507. That means DeepSeek V3.1 Terminus can ingest about 1.3x as much text per request.
What is the difference between Qwen3 235B A22B Thinking 2507 and DeepSeek V3.1 Terminus?
Qwen3 235B A22B Thinking 2507 comes from Qwen; DeepSeek V3.1 Terminus comes from DeepSeek. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.