Side-by-side comparison
DeepSeek V3.1 Terminus vs Trinity Large Thinking
DeepSeek
DeepSeek V3.1 Terminus
🔧 Tools
{} JSON
Input / 1M
$0.2700
Output / 1M
$0.9500
Arcee AI
Trinity Large Thinking
🔧 Tools
{} JSON
Input / 1M
$0.2200
Output / 1M
$0.8500
| DeepSeek V3.1 Terminus | Trinity Large Thinking | |
|---|---|---|
| Provider | DeepSeek | Arcee AI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 163,840 | 262,144 |
| 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 → | 0.2700 | 0.2200 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.9500 | 0.8500 |
Frequently asked questions
Which is cheaper, DeepSeek V3.1 Terminus or Trinity Large Thinking?
Trinity Large Thinking is cheaper than DeepSeek V3.1 Terminus on a 50/50 input/output blend by about $0.075 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, DeepSeek V3.1 Terminus or Trinity Large Thinking?
Trinity Large Thinking has the larger context window at 262k tokens versus 164k tokens for DeepSeek V3.1 Terminus. That means Trinity Large Thinking can ingest about 1.6x as much text per request.
What is the difference between DeepSeek V3.1 Terminus and Trinity Large Thinking?
DeepSeek V3.1 Terminus comes from DeepSeek; 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.