DeepSeek V3.1
DeepSeek's efficiency model. Context window: 164K tokens.
Scores by test
Methodology →What you need to know
DeepSeek V3.1 is primarily a high-reliability engine for structured data and long-context processing. It achieves perfect scores in faithfulness, structured output, and tabular data, making it highly effective for tasks requiring strict adherence to formats or the extraction of precise information from large datasets. Its 164K context window is fully utilized, as evidenced by its top-tier long-context performance.
At a blended cost of $0.775 per million tokens, the model is priced competitively for its capability set. While it ranks 89th overall out of 130 models, its value is concentrated in specialized technical tasks rather than general-purpose utility. It provides high-quality creative problem solving and persona consistency, though it struggles with basic classification and constrained rewriting.
The model's primary technical risks are its poor safety calibration and mediocre tool-calling capabilities. Developers should expect more frequent safety failures and less reliability when integrating the model into autonomous agent workflows that rely heavily on external API calls.
Use this model if your pipeline requires high faithfulness, complex tabular data handling, or processing of large documents within a budget. Skip this model if your application requires strict safety guardrails, high-accuracy classification, or robust tool-calling integration.
Strengths — Top 3
Relative weaknesses — Bottom 3
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