Xiaomi MiMo-V2.6 Pro vs NVIDIA Nemotron Labs Dory 1.0
A direct, empirical evaluation of Xiaomi MiMo-V2.6 Pro (Xiaomi AI Lab (Fuli Luo)) against NVIDIA Nemotron Labs Dory 1.0 (NVIDIA).
Xiaomi MiMo-V2.6 Pro
Developed by Xiaomi AI Lab (Fuli Luo) · 1.02 Trillion (Sparse MoE) parameters
High-accuracy autonomous coding (71.9% DeepSWE), cybersecurity defense (94.0% CyberGym), multimodal document reasoning, and cost-effective agentic workflows.
NVIDIA Nemotron Labs Dory 1.0
Developed by NVIDIA · 4 Billion Parameters (Looped Transformer) parameters
Ultra-low VRAM memory residency (4.4 GB FP8), 256k long-context needle retrieval, and recurrent layer depth execution.
| Metric | Xiaomi MiMo-V2.6 Pro | NVIDIA Nemotron Labs Dory 1.0 |
|---|---|---|
| SWE-bench Verified | 71.9% | 66.4% |
| MMLU-Pro | 89.2% | 82.8% |
| MATH-500 | 93.8% | 85.6% |
| Context Window | 128,000 tokens | 256,000 tokens |
| Input Pricing (per 1M) | $0.10 | $0.15 |
| Output Pricing (per 1M) | $0.20 | $0.45 |
Architectural & Practical Deployment Analysis
Evaluating Xiaomi MiMo-V2.6 Pro (Xiaomi AI Lab (Fuli Luo)) alongside NVIDIA Nemotron Labs Dory 1.0 (NVIDIA) highlights key technical trade-offs across neural parameter scale and compute efficiency. Xiaomi MiMo-V2.6 Pro executes across 1.02 Trillion (Sparse MoE) total parameters with 32 Billion active tokens active per token, whereas NVIDIA Nemotron Labs Dory 1.0 operates on 4 Billion Parameters (Looped Transformer) parameters with 4.1B Active Recurrent Block (Equivalent to 16B Depth) active per token.
On SWE-bench Verified software engineering tasks, Xiaomi MiMo-V2.6 Pro achieves 71.9% autonomous resolution rate, compared to 66.4% for NVIDIA Nemotron Labs Dory 1.0. On complex reasoning benchmarks, Xiaomi MiMo-V2.6 Pro posts 89.2% on MMLU-Pro and 93.8% on MATH-500, against 82.8% and 85.6% respectively for NVIDIA Nemotron Labs Dory 1.0.
From an operational economics perspective, processing 10,000,000 mixed tokens (7M input / 3M output) costs approximately $1.30 on Xiaomi MiMo-V2.6 Pro versus $2.40 on NVIDIA Nemotron Labs Dory 1.0.
Recommendation: Deploy Xiaomi MiMo-V2.6 Pro when your infrastructure prioritizes high-accuracy autonomous coding (71.9% deepswe), cybersecurity defense (94.0% cybergym), multimodal document reasoning, and cost-effective agentic workflows.. Deploy NVIDIA Nemotron Labs Dory 1.0 when workload requirements favor ultra-low vram memory residency (4.4 gb fp8), 256k long-context needle retrieval, and recurrent layer depth execution..