With hybrid inference, optimized tool integration, and expanded context window, it offers a practical balance of power and speed, making it well suited for real-world, high-throughput AI tasks.
DeepSeek V3.1 Terminus non-reasoning mode is a robust and efficient large language model suited for applications demanding fast, stable, and consistent output generation.
Model Overview
DeepSeek V3.1 Terminus is an advanced large language model designed primarily for fast, efficient, and lightweight generation tasks without the overhead of in-depth reasoning. It is part of the DeepSeek V3.1 series, optimized for agent workflows with significant improvements in stability, multilingual consistency, and tool use reliability. The non-reasoning mode emphasizes quick, robust output generation suitable for straightforward generation scenarios, making it highly efficient for practical applications requiring speed and low resource consumption.
Technical Specifications
Model Family: DeepSeek V3.1 Terminus (Non-Reasoning Mode)
Parameters: 671 billion total parameters, with 37 billion active parameters in inference
Architecture: Hybrid large language model with dual-mode inference support (thinking and non-thinking)
Context Window: Supports up to 128,000 tokens long-context training
Precision & Efficiency: Uses FP8 microscaling for memory and inference efficiency
Modes: Non-reasoning mode disables elaborate chain-of-thought reasoning for faster responses
Language Support: Improved multilingual consistency, especially English and Chinese, with reduced language mixing and tokenization errors
Performance Benchmarks
Reasoning Benchmarks (MMLU-Pro): 85.0 (slightly improved over previous version)
Agentic Web Navigation (BrowseComp): 38.5 (significant improvements in multi-step tool use)
Command Line Competence (Terminal-bench): 36.7 (better handling of command sequences)
Code Generation (LiveCodeBench): 74.9 (maintains high code generation capabilities)
Overall Stability: Reduced variance and more deterministic outputs in agent workflows, enhancing real-world use reliability
Performance Benchmarks
Key Features
Fast and Lightweight Generation: Prioritized non-thinking mode reduces processing time and resources, ideal for quick outputs
Robust Multilingual Output: Fixes to avoid language mixing and inconsistent tokens, supporting global applications
Improved Tool Use: Enhances reliability in tool invocation workflows such as code execution and web search chains
Flexible Long-Context: Supports very large token contexts of up to 128K tokens for extensive input histories
Stable and Consistent Outputs: Post-training optimization reduces hallucinations and tokenization artifacts
Backward Compatible: Integrates seamlessly into existing DeepSeek API ecosystems without disruptive changes
Scalable Hybrid Inference: Balances large-scale model capacity with efficient active parameter deployment
API Pricing
1М input tokens (cache hit): $0.0735
1М input tokens (cache miss): $0.588
1М output tokens: $1.764
Use Cases
Fast customer support and chatbot responses
Multilingual marketing copy and content generation
Automated coding assistance and script execution
Knowledge base querying with long context
Tool-assisted task automation workflows
Quick summarization of long documents without deep explanation
Code Sample
Comparison with Other Models
vs GPT-4: DeepSeek V3.1 Terminus offers a much larger context window (up to 128K tokens) compared to GPT-4's 32K tokens, making it better suited for extremely long documents and research tasks. It also runs in a specialized non-reasoning mode for faster generation, while GPT-4 is optimized for detailed reasoning but with higher latency.
vs GPT-5: GPT-5 supports an even larger context length and excels in multimodal tasks, providing broad ecosystem integration for enterprise applications. DeepSeek V3.1 Terminus emphases cost-efficiency and open-weight licensing, making it attractive for developers and startups with infrastructure capabilities.
vs Claude 4.5: Claude 4.5 prioritizes safety, alignment, and strong reasoning capabilities and robust constitutional AI features to reduce hallucinations. DeepSeek V3.1 Terminus focuses more on lightweight, rapid output. Claude often comes with higher per-task pricing and is favored in regulated industries, while DeepSeek offers open licensing and accessible use for rapid prototyping.
vs OpenAI GPT-4.5: GPT-4.5 improves on GPT-4 with better reasoning and creative writing capabilities but retains a shorter context window (128K tokens) compared to DeepSeek’s extended 128K token-long context support. DeepSeek V3.1 Terminus achieves faster response times in its non-reasoning mode, making it preferable for applications needing speed without deep chain-of-thought. GPT-4.5 has stronger creative generation and ecosystem integration, while DeepSeek excels in scalability and cost efficiency.
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