MiniMax M2 vs DeepSeek-V3.2
Side-by-side specs, pricing and capabilities. Both models run on Clade under one subscription, so you can switch between them in the same conversation.
MiniMax M2 comes from MiniMax and DeepSeek-V3.2 from DeepSeek. The practical difference for most people is context, price, and which input types each one accepts.
MiniMax M2 holds more in a single conversation — 197K tokens against 128K — which matters for long documents and large codebases.
DeepSeek-V3.2 is the cheaper of the two on input tokens at $0.03 / 1M tokens.
| Specification | MiniMax M2 | DeepSeek-V3.2 |
|---|---|---|
| Provider | MiniMax | DeepSeek |
| Model ID | MiniMax-M2 | deepseek-chat |
| Context window | 197K | 128K |
| Max output | 10K | 8K |
| Input price | $0.30 / 1M tokens | $0.03 / 1M tokens |
| Output price | $1.00 / 1M tokens | $0.42 / 1M tokens |
| Knowledge cutoff | — | — |
| Input types | text, image, file | text |
| Output types | text | text |
| Plan | Free | Free |
Which should you use?
Pick MiniMax M2 when…
- You need the larger context window — 197K against 128K.
- You want longer single responses — up to 10K output tokens.
- You need image and file input, which the other model does not accept.
Pick DeepSeek-V3.2 when…
- Cost matters: input runs at $0.03 / 1M tokens versus $0.30 / 1M tokens.
Related comparisons
Try both on Clade
You do not have to choose. One Clade subscription gives you MiniMax M2, DeepSeek-V3.2, and every other model on the platform.