Xiaomi MiMo V2 Pro Benchmarks Leaked
💡Early benchmarks of Xiaomi's new local LLM rival—check performance vs leaders
⚡ 30-Second TL;DR
What Changed
Leak originates from Reddit r/LocalLLaMA post
Why It Matters
This leak provides early insights into Xiaomi's AI model performance, potentially influencing competitor strategies and local LLM adoption.
What To Do Next
Visit artificialanalysis.ai/models/mimo-v2-pro to review leaked MiMo V2 Pro benchmarks.
Key Points
- •Leak originates from Reddit r/LocalLLaMA post
- •Benchmarks accessible at artificialanalysis.ai/models/mimo-v2-pro
- •Submitted by user /u/External_Mood4719
- •Focuses on Xiaomi's new MiMo V2 Pro model
🧠 Deep Insight
Background and context from public sources — not the original article. 6 sources cited.
🔑 Enhanced Key Takeaways
- •MiMo-V2-Flash, a related model in Xiaomi's lineup released in February 2026, is a Mixture-of-Experts (MoE) architecture with 309B total parameters and 15B active parameters[3].
- •MiMo-V2-Flash achieves top rankings among open-source models on AIME 2025 math competition and GPQA-Diamond scientific benchmark[3].
- •The model supports infinite context windows and delivers inference speeds up to 150 tokens per second at a cost of $0.1 per million input tokens[3][2].
🛠️ Technical Deep Dive
- •MiMo-V2-Flash uses a hybrid attention mechanism with a 1:5 ratio of Global Attention (GA) and Sliding Window Attention (SWA), featuring an aggressive 128-token sliding window for efficiency[3].
- •Includes a lightweight Multi-Token Prediction (MTP) block with a dense FFN and SWA, achieving 2.0–2.6× speedup and accepted lengths of 2.8–3.6 tokens[3].
- •Demonstrates near 100% long-context retrieval success from 32K to 256K tokens and robust performance on GSM-Infinite benchmark up to 128K[5].
- •Benchmark scores include 83.5% on GPQA, 33.5 coding index, and 67.7% on AIME 2025[2].
🔮 Future ImplicationsAI analysis grounded in cited sources
⏳ Timeline
📎 Sources (6)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
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Original source: Reddit r/LocalLLaMA ↗
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