DeepSeek V3.1 vs Trinity Large Thinking
DeepSeek V3.1
Trinity Large Thinking
| DeepSeek V3.1 | Trinity Large Thinking | |
|---|---|---|
| Provider | DeepSeek | Arcee AI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 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 β | 0.2100 | 0.2200 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 0.7900 | 0.8500 |
Frequently asked questions
Which is cheaper, DeepSeek V3.1 or Trinity Large Thinking?
DeepSeek V3.1 is cheaper than Trinity Large Thinking on a 50/50 input/output blend by about $0.035 per 1M tokens. Exact savings depend on your input-vs-output ratio β use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, DeepSeek V3.1 or Trinity Large Thinking?
Trinity Large Thinking has the larger context window at 262k tokens versus 164k tokens for DeepSeek V3.1. That means Trinity Large Thinking can ingest about 1.6x as much text per request.
What is the difference between DeepSeek V3.1 and Trinity Large Thinking?
DeepSeek V3.1 comes from DeepSeek; Trinity Large Thinking comes from Arcee AI. They differ in pricing, context window, and supported capabilities β see the side-by-side table on this page for the exact figures, refreshed nightly.