Update README.md

README.md

@@ -66,6 +66,9 @@ Performance evaluation is ongoing. The model shows promising results in:
 -   Maintaining base model capabilities while achieving linear attention efficiency
 -   Significantly improved needle-in-haystack task performance compared to pure RWKV architectures
 -   Competitive performance on standard language modeling benchmarks
+-   mmlu: 78.39%(Base 82.41%)
+-   gsm8k: 86.88%(Base93.93%) with gentoken=2048
+-   passkey 130k+(Base 500k)
 
 ## Usage with RWKV-Infer
 -   **RWKV-Infer** Triton based Hybrid RWKV Inference engine, can be check at: [https://github.com/OpenMOSE/RWKV-Infer/wiki/How-to-Running-RWKV-hxa079-models%3F](https://github.com/OpenMOSE/RWKV-Infer/wiki/How-to-Running-RWKV-hxa079-models%3F)