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DeepSeek V3.1 Terminus (exacto)

by DeepSeek

DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's performance in coding and search agents. It is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes. It extends the DeepSeek-V3 base with a two-phase long-context training process, reaching up to 128K tokens, and uses FP8 microscaling for efficient inference. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. It supports structured tool calling, code agents, and search agents, making it suitable for research, coding, and agentic workflows.

Chat with DeepSeek V3.1 Terminus (exacto)
Input Price$0.40/1M tokens
Output Price$2.00/1M tokens
Intelligence33.8
Coding33.7

Specifications

Technical details and pricing.

ProviderDeepSeek
Context Window163,840 tokens
Release DateSep 22, 2025
ModalitiesText

Benchmarks

10 benchmark scores from Artificial Analysis.

GPQA79.2%
MMLU Pro85.1%
HLE15.2%
LiveCodeBench79.8%
AIME 202589.7%
SciCode40.6%
LCR65.0%
IFBench57.0%
Tau237.1%
TerminalBench Hard30.3%

Composite Indices

Intelligence, Coding, Math

Standard Benchmarks

Academic and industry benchmarks

Frequently Asked Questions

What is DeepSeek V3.1 Terminus (exacto) good for?

Use DeepSeek V3.1 Terminus (exacto) for everyday tasks like writing, summarizing, brainstorming, and getting clear explanations.

How much does DeepSeek V3.1 Terminus (exacto) cost?

Pricing is based on usage. Current rates are $0.40/1M tokens for input and $2.00/1M tokens for output.

Can I try DeepSeek V3.1 Terminus (exacto) for free?

Yes. You can start a chat instantly and test the model before deciding on a plan.

Does DeepSeek V3.1 Terminus (exacto) support images or audio?

DeepSeek V3.1 Terminus (exacto) focuses on text-based tasks.

Benchmarks and pricing are sourced from Artificial Analysis where available. OpenRouter specs are used as a fallback.