Side-by-side comparison
MiniMax M2.1 vs DeepSeek V3.1
| MiniMax M2.1 | DeepSeek V3.1 | |
|---|---|---|
| Provider | MiniMax | DeepSeek |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 196,608 | 163,840 |
| 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 → | 0.2900 | 0.2100 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.9500 | 0.7900 |
Frequently asked questions
Which is cheaper, MiniMax M2.1 or DeepSeek V3.1?
DeepSeek V3.1 is cheaper than MiniMax M2.1 on a 50/50 input/output blend by about $0.12 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, MiniMax M2.1 or DeepSeek V3.1?
MiniMax M2.1 has the larger context window at 197k tokens versus 164k tokens for DeepSeek V3.1. That means MiniMax M2.1 can ingest about 1.2x as much text per request.
What is the difference between MiniMax M2.1 and DeepSeek V3.1?
MiniMax M2.1 comes from MiniMax; DeepSeek V3.1 comes from DeepSeek. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.