Side-by-side comparison
gpt-oss-20b vs Qwen2.5 7B Instruct
Qwen
Qwen2.5 7B Instruct
🔧 Tools
{} JSON
Input / 1M
$0.0400
Output / 1M
$0.1000
| gpt-oss-20b | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | OpenAI | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 32,768 |
| 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 → | 0.0300 | 0.0400 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1400 | 0.1000 |
Frequently asked questions
Which is cheaper, gpt-oss-20b or Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is cheaper than gpt-oss-20b on a 50/50 input/output blend by about $0.015 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, gpt-oss-20b or Qwen2.5 7B Instruct?
gpt-oss-20b has the larger context window at 131k tokens versus 33k tokens for Qwen2.5 7B Instruct. That means gpt-oss-20b can ingest about 4.0x as much text per request.
What is the difference between gpt-oss-20b and Qwen2.5 7B Instruct?
gpt-oss-20b comes from OpenAI; Qwen2.5 7B Instruct 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.