Side-by-side comparison
GLM 4.7 vs Qwen3 235B A22B
| GLM 4.7 | Qwen3 235B A22B | |
|---|---|---|
| Provider | Z.ai | Qwen |
| 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 → | 0.4000 | 0.4550 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 1.7500 | 1.8200 |
Frequently asked questions
Which is cheaper, GLM 4.7 or Qwen3 235B A22B?
GLM 4.7 is cheaper than Qwen3 235B A22B on a 50/50 input/output blend by about $0.0625 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 or Qwen3 235B A22B?
GLM 4.7 has the larger context window at 203k tokens versus 131k tokens for Qwen3 235B A22B. That means GLM 4.7 can ingest about 1.5x as much text per request.
What is the difference between GLM 4.7 and Qwen3 235B A22B?
GLM 4.7 comes from Z.ai; Qwen3 235B A22B 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.