Side-by-side comparison
Qwen3 235B A22B Instruct 2507 vs Trinity Mini
Qwen
Qwen3 235B A22B Instruct 2507
🔧 Tools
{} JSON
Input / 1M
$0.0710
Output / 1M
$0.1000
| Qwen3 235B A22B Instruct 2507 | Trinity Mini | |
|---|---|---|
| Provider | Qwen | Arcee AI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 262,144 | 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 → | 0.0710 | 0.0450 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1000 | 0.1500 |
Frequently asked questions
Which is cheaper, Qwen3 235B A22B Instruct 2507 or Trinity Mini?
Qwen3 235B A22B Instruct 2507 is cheaper than Trinity Mini on a 50/50 input/output blend by about $0.012 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, Qwen3 235B A22B Instruct 2507 or Trinity Mini?
Qwen3 235B A22B Instruct 2507 has the larger context window at 262k tokens versus 131k tokens for Trinity Mini. That means Qwen3 235B A22B Instruct 2507 can ingest about 2.0x as much text per request.
What is the difference between Qwen3 235B A22B Instruct 2507 and Trinity Mini?
Qwen3 235B A22B Instruct 2507 comes from Qwen; Trinity Mini comes from Arcee AI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.