Side-by-side comparison
Nemotron Nano 9B V2 vs Qwen3 235B A22B Instruct 2507
NVIDIA
Nemotron Nano 9B V2
🔧 Tools
{} JSON
Input / 1M
$0.0400
Output / 1M
$0.1600
Qwen
Qwen3 235B A22B Instruct 2507
🔧 Tools
{} JSON
Input / 1M
$0.0710
Output / 1M
$0.1000
| Nemotron Nano 9B V2 | Qwen3 235B A22B Instruct 2507 | |
|---|---|---|
| Provider | NVIDIA | Qwen |
| 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 → | 0.0400 | 0.0710 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1600 | 0.1000 |
Frequently asked questions
Which is cheaper, Nemotron Nano 9B V2 or Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507 is cheaper than Nemotron Nano 9B V2 on a 50/50 input/output blend by about $0.0145 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, Nemotron Nano 9B V2 or Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507 has the larger context window at 262k tokens versus 131k tokens for Nemotron Nano 9B V2. That means Qwen3 235B A22B Instruct 2507 can ingest about 2.0x as much text per request.
What is the difference between Nemotron Nano 9B V2 and Qwen3 235B A22B Instruct 2507?
Nemotron Nano 9B V2 comes from NVIDIA; Qwen3 235B A22B Instruct 2507 comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.