DeepSeek V3.1
Fast, general-purpose MoE model with long-context variants and strong coding ability.
- MoE architecture with fast default latency.
- Reported long-context support in specialized variants.
- Open-source ecosystem with broad community adoption.
DeepSeek V3.1 is a large, open-source MoE model built for general chat, coding, and long-context workflows. Reports describe ~685B total parameters with ~37B activated per token, which keeps inference efficient while preserving capacity.
The model is widely referenced as supporting 128K-class context in long-context variants and is trained on very large corpora (public reports cite ~14.8T tokens). The MIT license enables commercial use and internal fine-tuning, which has accelerated adoption across teams that need flexible deployment.
V3.1 is a strong default when you want balanced quality, speed, and cost. It handles summarization, extraction, and code generation well, and can anchor production systems while you route specialized tasks to R1, Math-7B, or multimodal models.
- General chat, code, and automation workloads.
- Long-context variants for large documents.
- Sparse MoE efficiency at scale.
- MIT-licensed for commercial deployment.
- Stable production behavior and tuning headroom.