Unverified50% confidenceFactExact time
'Frontier' generally refers to large model systems whose capabilities are at the current cutting edge of technology and whose behavior cannot be fully predicted.
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50%
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Long-term
Relevance
9/25/2026
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UnverifiedCapability improvements in frontier models are quantifiable, demonstrable, and commercially viable, whereas the verification of safety and controllability tends to lag behind, is vague, and is difficult to prove.72% similarUnverifiedCurrent mainstream large models excel at handling isolated, well-bounded small tasks, but expose shortcomings of incomplete understanding and loss of detail when faced with highly coupled, large-context legacy systems.70% similarUnverifiedEven when the correct context is provided, frontier models still have a certain probability of generating content that contradicts the context (the hallucination problem).69% similarUnverifiedThe performance gap among mainstream frontier models on standard tasks such as general question answering, text summarization, and code generation is narrowing, a phenomenon referred to as capability homogenization.69% similarUnverifiedLocal models currently lag behind the top closed-source models in terms of performance.68% similar
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