Side-by-side comparison
Qwen3 VL 235B A22B Instruct vs Trinity Large Thinking
Qwen
Qwen3 VL 235B A22B Instruct
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.2000
Output / 1M
$0.8800
Arcee AI
Trinity Large Thinking
🔧 Tools
{} JSON
Input / 1M
$0.2200
Output / 1M
$0.8500
| Qwen3 VL 235B A22B Instruct | Trinity Large Thinking | |
|---|---|---|
| Provider | Qwen | Arcee AI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 262,144 | 262,144 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.2000 | 0.2200 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.8800 | 0.8500 |
Frequently asked questions
Which is cheaper, Qwen3 VL 235B A22B Instruct or Trinity Large Thinking?
Trinity Large Thinking is cheaper than Qwen3 VL 235B A22B Instruct on a 50/50 input/output blend by about $0.005 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
What is the difference between Qwen3 VL 235B A22B Instruct and Trinity Large Thinking?
Qwen3 VL 235B A22B Instruct comes from Qwen; Trinity Large Thinking 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.