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Deepseek | Deepseek V3.1 Terminus

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. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config) The model improves tool use, code generation, and reasoning efficiency, achieving performance comparable to DeepSeek-R1 on difficult benchmarks while responding more quickly. It supports structured tool calling, code agents, and search agents, making it suitable for research, coding, and agentic workflows.

Compare

Good

73.0
Most Recent Test

Usable with some limitations.

Strengths

  • Affirms Christian worldview
  • Excellent at 1.3. Apologetics
  • Excellent at 1.6. Problematic Vocabulary
  • Excellent at 2.1. Exclusivity of Jesus
  • Excellent at 2.2. Universality of Sin

Weaknesses

No notable weaknesses identified

Overall Score
73.0
Tier 1 (Task) 70%
71.4
Tier 2 (Doctrine) 20%
71.7
Tier 3 (Worldview) 10%
86.7
Performance Profile
Visual representation of performance across all evaluated categories
Model Information
Description

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. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config) The model improves tool use, code generation, and reasoning efficiency, achieving performance comparable to DeepSeek-R1 on difficult benchmarks while responding more quickly. It supports structured tool calling, code agents, and search agents, making it suitable for research, coding, and agentic workflows.

Provider

DeepSeek

Model ID

deepseek/deepseek-v3.1-terminus

Tests Run

1

Insights & Analysis

Categories

Category Heatmap
Performance breakdown by category - darker green indicates stronger alignment
67
1.1
60
1.2
83
1.3
70
1.4
60
1.5
87
1.6
73
1.7
100
2.1
100
2.2
60
2.3
70
2.4
40
2.5
60
2.6
75
3.1
100
3.2
75
3.3
100
3.4
100
3.5
83
3.6
Low
High
Category Breakdown (Bar Chart)
Performance across different categories
1.x = Task Capability2.x = Gospel Core3.x = Worldview Confession

Recent Tests

Recent Test Runs
DateScoreVersionTier 1 (Task)Tier 2 (Gospel)Tier 3 (Worldview)Trust Tier
10/10/202673.01.0.071.471.786.7automated