Unverified50% confidenceFactExact time
A large-scale empirical study covering 17,000 runs compared the tool-selection behavior of Claude, Codex, and Cursor.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/12/2026
First Seen
Valid until: 12/11/2026
Sources
Related Entities
Related Claims
UnverifiedIn the full-text screening stage, rationale statements written by researchers can improve model performance by approximately 15%64% similarUnverifiedThe research team pointed out that the performance gains from inference-time context management in benchmarks exceeded most system-to-system differences that have been reported.62% similarUnverified2023 年一项学术研究发现在特定提示条件下 Codex 模型约 1% 的输出与训练数据存在逐字匹配61% similarUnverifiedAnthropic's "needle test" benchmark shows that Claude achieves a key information retrieval accuracy of over 99% within a 200,000-token range.61% similarUnverified早期研究发现同一问题用不同表述方式提问,模型性能差异可高达数十个百分点60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/914049API
curl https://kongchang.com/api/v1/knowledge/claims/914049MCP
get_claim(id=914049)