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README_en.md

@@ -1305,7 +1305,6 @@ scores:
 | 7    | E     | 22                   | 23                       | 15                | 14                       | 74                 |
 | 8    | G     | 10                   | 12                       | 10                | 10                       | 42                 |
 
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 ### 👉 Subjective Effect Summary
 
@@ -1318,6 +1317,8 @@ My personal evaluation aligns with DeepSeek-R1's results，and：
 * Repeating the timeless Scaling Law: The larger the parameters and the more training data, the stronger the model's
   performance.
 
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 ## Ⅲ Objective Benchmark
 
 Now, onto the much-anticipated benchmark testing phase. We won’t bother comparing with models like Qwen or GLM-level