Mistral Large 3 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.
Mistral Large 3 comes from Mistral and DeepSeek-V3.2 from DeepSeek. The practical difference for most people is context, price, and which input types each one accepts.
Mistral Large 3 holds more in a single conversation — 256K 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 | Mistral Large 3 | DeepSeek-V3.2 |
|---|---|---|
| Provider | Mistral | DeepSeek |
| Model ID | mistral-large-2512 | deepseek-chat |
| Context window | 256K | 128K |
| Max output | 8K | 8K |
| Input price | $0.50 / 1M tokens | $0.03 / 1M tokens |
| Output price | $1.50 / 1M tokens | $0.42 / 1M tokens |
| Knowledge cutoff | — | — |
| Input types | text, image, file, audio | text |
| Output types | text | text |
| Plan | Free | Free |
Which should you use?
Pick Mistral Large 3 when…
- You need the larger context window — 256K against 128K.
- You want longer single responses — up to 8K output tokens.
- You need image and file and audio input, which the other model does not accept.
Pick DeepSeek-V3.2 when…
- Cost matters: input runs at $0.03 / 1M tokens versus $0.50 / 1M tokens.
Related comparisons
Try both on Clade
You do not have to choose. One Clade subscription gives you Mistral Large 3, DeepSeek-V3.2, and every other model on the platform.