Side-by-side comparison
Qwen3 30B A3B Thinking 2507 vs Nemotron 3 Super
Qwen
Qwen3 30B A3B Thinking 2507
🔧 Tools
{} JSON
Input / 1M
$0.0800
Output / 1M
$0.4000
NVIDIA
Nemotron 3 Super
🔧 Tools
{} JSON
Input / 1M
$0.0900
Output / 1M
$0.4500
| Qwen3 30B A3B Thinking 2507 | Nemotron 3 Super | |
|---|---|---|
| Provider | Qwen | NVIDIA |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 262,144 |
| 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 → | 0.0800 | 0.0900 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.4000 | 0.4500 |
Frequently asked questions
Which is cheaper, Qwen3 30B A3B Thinking 2507 or Nemotron 3 Super?
Qwen3 30B A3B Thinking 2507 is cheaper than Nemotron 3 Super on a 50/50 input/output blend by about $0.03 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 30B A3B Thinking 2507 or Nemotron 3 Super?
Nemotron 3 Super has the larger context window at 262k tokens versus 131k tokens for Qwen3 30B A3B Thinking 2507. That means Nemotron 3 Super can ingest about 2.0x as much text per request.
What is the difference between Qwen3 30B A3B Thinking 2507 and Nemotron 3 Super?
Qwen3 30B A3B Thinking 2507 comes from Qwen; Nemotron 3 Super comes from NVIDIA. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.