diff --git a/README.md b/README.md
index d5d9715..9bf8465 100644
--- a/README.md
+++ b/README.md
@@ -11,11 +11,11 @@ library_name: transformers
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+ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Unlocking the Reasoning Potential of Language Model
From Pretraining to Posttraining
- ━━━━━━━━━━━━━━━━━━━━━━━━━
+ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
@@ -35,7 +35,41 @@ library_name: transformers
-> This model repository is licensed under the MIT License.
+---
+
+## Updates
+
+[2025.05.30] We scaled the SFT dataset from approximately 500K to 6M instances and continuously expanding the RL training window size from 32K to 48K, the performance of [MiMo-7B-RL-0530](https://huggingface.co/XiaomiMiMo/MiMo-7B-RL-0530) on AIME24 can be continuously improved and eventually surpass that of DeepSeek R1 (79.8).
+
+
+
+
+ | Benchmark |
+ MiMo-7B-RL |
+ MiMo-7B-RL-0530 |
+
+
+
+
+ | Mathematics |
+
+
 |
+
+
+ MATH500 (Pass@1) | 95.8 | 97.2 |
+ AIME 2024 (Pass@1) | 68.2 | 80.1 |
+ AIME 2025 (Pass@1) | 55.4 | 70.2 |
+ | Code |
+ LiveCodeBench v5 (Pass@1) | 57.8 | 60.9 |
+ LiveCodeBench v6 (Pass@1) | 49.3 | 52.2 |
+ | STEM |
+ GPQA-Diamond (Pass@1) | 54.4 | 60.6 |
+ | General |
+ Alignbench1.1 (Evaluated by GPT4.1) | 6.9 | 7.4 |
+
+
+
+---
## I. Introduction
@@ -122,7 +156,7 @@ MiMo-7B series
### SGLang Inference
-Thanks to the [contribution](https://github.com/sgl-project/sglang/pull/5921) from the SGLang team, we supported MiMo in SGLang mainstream within 24h with MTP coming soon.
+Thanks to the [MiMo model support](https://github.com/sgl-project/sglang/pull/5921) and [MTP](https://github.com/sgl-project/sglang/pull/6059) from the SGLang team, we supported MiMo in SGLang mainstream.
Example Script
@@ -132,9 +166,14 @@ python3 -m uv pip install "sglang[all] @ git+https://github.com/sgl-project/sgla
# Launch SGLang Server
python3 -m sglang.launch_server --model-path XiaomiMiMo/MiMo-7B-RL --host 0.0.0.0 --trust-remote-code
+
+# Launch MTP Server
+python3 -m sglang.launch_server --model-path XiaomiMiMo/MiMo-7B-RL --trust-remote-code \
+--speculative-algorithm EAGLE --speculative-num-steps 1 --speculative-eagle-topk 1 \
+--speculative-num-draft-tokens 2 --mem-fraction 0.5
```
-Detailed usage can be found in [SGLang documents](https://docs.sglang.ai/backend/send_request.html). MTP will also be supported in 24h.
+Detailed usage can be found in [SGLang documents](https://docs.sglang.ai/backend/send_request.html).
### vLLM inference
@@ -223,7 +262,7 @@ print(tokenizer.decode(output.tolist()[0]))
```bibtex
@misc{coreteam2025mimounlockingreasoningpotential,
title={MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining},
- author={{Xiaomi LLM-Core Team}},
+ author={LLM-Core-Team Xiaomi},
year={2025},
eprint={2505.07608},
archivePrefix={arXiv},