Inception: Mercury 2
inception's efficiency model. Context window: 128K tokens.
Scores by test
Methodology →What you need to know
Inception: Mercury 2 is a high-precision model optimized for structural integrity and analytical depth. It achieves perfect scores in structured output, faithfulness, and strategic analysis, making it highly reliable for tasks requiring strict adherence to formats and factual grounding. Its capability extends to complex data handling, performing at a top tier for tabular data, multilingual processing, and long-context retrieval across its 128K window.
Pricing is aggressive for a model with these capabilities, with a blended cost of $0.625/MTok. This puts it in a budget-friendly tier relative to its performance in high-logic domains like agentic planning and strategic analysis. However, the model ranks #73 of 105 overall, suggesting that while it excels in specific technical niches, it lacks the general-purpose versatility of higher-ranked models.
The model has critical failures in safety calibration, scoring 1/5, which indicates a lack of robust guardrails. It also shows mediocre performance in tool calling and constrained rewriting, meaning it may struggle with external API integrations or strict stylistic modifications.
Use this model if you need a low-cost solution for structured data extraction, strategic analysis, or multilingual processing where safety filtering is handled by your own middleware. Skip this model if your application requires high safety standards, reliable tool calling, or precise rewriting constraints.
Strengths — Top 3
Relative weaknesses — Bottom 3
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