Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
NVIDIA
Llama-3.1-Nemotron-Nano-8B-v1 is an 8-billion-parameter model from NVIDIA, developed as a fine-tuned variant of Meta's Llama 3.1 8B using NVIDIA's Nemotron post-training methodology, which applies reinforcement learning and process reward modeling to enhance instruction-following and reasoning capability over the base model. The Nano designation marks it as the entry-level member of the Nemotron family, optimized for efficient inference on a single GPU while delivering meaningfully improved performance on instruction alignment and agentic tasks compared to standard Llama 3.1. Released open-weight on HuggingFace, it is designed for deployment in NVIDIA-accelerated environments and supports NVIDIA NIM for enterprise inference.
Xiaomi
MiMo-V2-Flash, released by Xiaomi on December 16, 2025, is a Mixture-of-Experts large language model with 309 billion total parameters and 15 billion active parameters per inference, designed for high-speed reasoning and agentic workflows. It features a 256K token context window, processes up to 150 tokens per second, and was trained on 27 trillion tokens. MiMo-V2-Flash targets open-source deployments requiring fast, capable coding and reasoning with an efficient inference footprint, under an MIT license.
11 months newer

Llama 3.1 Nemotron Nano 8B
NVIDIA
2025-01-06
MiMo-V2-Flash
Xiaomi
2025-12-16
Available providers and their performance metrics
Llama 3.1 Nemotron Nano 8B
MiMo-V2-Flash
Llama 3.1 Nemotron Nano 8B
MiMo-V2-Flash