Side-by-side comparison
GLM 4.7 Flash vs Llama 3.3 Nemotron Super 49B V1.5
NVIDIA
Llama 3.3 Nemotron Super 49B V1.5
🔧 Tools
{} JSON
Input / 1M
$0.1000
Output / 1M
$0.4000
| GLM 4.7 Flash | Llama 3.3 Nemotron Super 49B V1.5 | |
|---|---|---|
| Provider | Z.ai | NVIDIA |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 202,752 | 131,072 |
| 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 → | 0.0600 | 0.1000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.4000 | 0.4000 |
Frequently asked questions
Which is cheaper, GLM 4.7 Flash or Llama 3.3 Nemotron Super 49B V1.5?
GLM 4.7 Flash is cheaper than Llama 3.3 Nemotron Super 49B V1.5 on a 50/50 input/output blend by about $0.02 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 4.7 Flash or Llama 3.3 Nemotron Super 49B V1.5?
GLM 4.7 Flash has the larger context window at 203k tokens versus 131k tokens for Llama 3.3 Nemotron Super 49B V1.5. That means GLM 4.7 Flash can ingest about 1.5x as much text per request.
What is the difference between GLM 4.7 Flash and Llama 3.3 Nemotron Super 49B V1.5?
GLM 4.7 Flash comes from Z.ai; Llama 3.3 Nemotron Super 49B V1.5 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.