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DeepSeek Advanced

DeepSeek-V3.1

DeepSeek-V3.1 is a 671B/37B hybrid reasoning MoE with 128K context and MIT weights; its original provider API generation has been superseded.

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In plain English

What is this model and why does it matter?

DeepSeek-V3.1 is a 671B-total, 37B-active MIT-licensed MoE model with 128K context and hybrid thinking/non-thinking modes.

Reasoning researchAgent researchTool-use experimentsHistorical benchmarkingLarge-scale self-hosting
Model overview

DeepSeek-V3.1: features, use cases and important details

DeepSeek-V3.1 is DeepSeek’s August 2025 hybrid model supporting thinking and non-thinking inference.

Verified model facts

Official sources list 671B total parameters, 37B active parameters, 128K context, MIT licensing and stronger agent/tool-use post-training.

Current status

The weights remain downloadable, but hosted aliases moved through V3.1-Terminus, V3.2 and V4.

Best fit

It is best for research, historical benchmarking, agent experiments and organizations capable of large-scale self-hosting.

Limitations

The model is extremely large, current DeepSeek pricing does not apply and it can still make reasoning or tool-use errors.

Get started

How to use this model

  1. Download the official V3.1 checkpoint.
  2. Provision distributed inference infrastructure.
  3. Use the documented chat template for thinking or non-thinking mode.
  4. Configure tools with a compatible runtime.
  5. Use current DeepSeek V4 models for new hosted API integrations.
Copy and try

Example prompts

  • Analyze this repository and propose a multi-step repair plan.
  • Reason through this technical problem and verify the conclusion.
  • Select the appropriate tool sequence for this workflow.
Capabilities

What it can do

  • 128K context
  • Hybrid thinking
  • Non-thinking mode
  • Agent tasks
  • Tool use
  • Coding
Best for

Practical use cases

  • Reasoning research
  • Agent workflows
  • Coding research
  • Historical comparison
Pricing

What does it cost?

The original DeepSeek-V3.1 API generation has been superseded; current DeepSeek V4 pricing does not apply to this checkpoint.

Simple summaryMIT weights remain downloadable, but full-model self-hosting requires very large infrastructure. Historical API prices are obsolete.

What stands out

  • MIT license
  • 128K context
  • Hybrid reasoning modes
  • Official open weights

Things to consider

  • Original API generation superseded
  • Enormous 671B model
  • Complex local deployment
Limitations

Important restrictions and trade-offs

  • Not the model behind current DeepSeek API aliases
  • Self-hosting is infrastructure intensive
  • Can hallucinate or choose tools incorrectly
SimplifyAITools verdict

Our editorial take

Important as DeepSeek’s first hybrid V3 model and still useful as open weights, but it is no longer a current DeepSeek API generation.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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