Side-by-side comparison
GLM 4.7 Flash vs Llama 3.3 70B Instruct
Meta
Llama 3.3 70B Instruct
🔧 Tools
{} JSON
Input / 1M
$0.1000
Output / 1M
$0.3200
| GLM 4.7 Flash | Llama 3.3 70B Instruct | |
|---|---|---|
| Provider | Z.ai | Meta |
| 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 | 0.3200 |
Frequently asked questions
Which is cheaper, GLM 4.7 Flash or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is cheaper than GLM 4.7 Flash 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 70B Instruct?
GLM 4.7 Flash has the larger context window at 203k tokens versus 131k tokens for Llama 3.3 70B Instruct. 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 70B Instruct?
GLM 4.7 Flash comes from Z.ai; Llama 3.3 70B Instruct comes from Meta. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.