Side-by-side comparison
GLM 4 32B vs Nemotron Nano 9B V2
NVIDIA
Nemotron Nano 9B V2
🔧 Tools
{} JSON
Input / 1M
$0.0400
Output / 1M
$0.1600
| GLM 4 32B | Nemotron Nano 9B V2 | |
|---|---|---|
| Provider | Z.ai | NVIDIA |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 128,000 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.1000 | 0.0400 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1000 | 0.1600 |
Frequently asked questions
Which is cheaper, GLM 4 32B or Nemotron Nano 9B V2?
GLM 4 32B is cheaper than Nemotron Nano 9B V2 on a 50/50 input/output blend by about $0 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, GLM 4 32B or Nemotron Nano 9B V2?
Nemotron Nano 9B V2 has the larger context window at 131k tokens versus 128k tokens for GLM 4 32B . That means Nemotron Nano 9B V2 can ingest about 1.0x as much text per request.
What is the difference between GLM 4 32B and Nemotron Nano 9B V2?
GLM 4 32B comes from Z.ai; Nemotron Nano 9B V2 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.