Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
NVIDIA
Llama-3.3-Nemotron-Super-49B-v1 is a 49-billion-parameter model from NVIDIA, fine-tuned from Meta's Llama 3.3 using NVIDIA's Nemotron post-training pipeline that combines supervised fine-tuning with reinforcement learning to enhance reasoning, instruction alignment, and complex problem-solving. The Super tier in the Nemotron family represents a mid-range capability level — positioned above the Nano series and below the Ultra 253B flagship — offering a balance between high-quality outputs and manageable inference infrastructure requirements. Released open-weight on HuggingFace with NVIDIA NIM support, it targets teams with multi-GPU setups who need strong reasoning capability without the scale of the Ultra model.
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.
9 months newer

Llama-3.3 Nemotron Super 49B
NVIDIA
2025-03-01
MiMo-V2-Flash
Xiaomi
2025-12-16
Available providers and their performance metrics
Llama-3.3 Nemotron Super 49B
MiMo-V2-Flash
Llama-3.3 Nemotron Super 49B
MiMo-V2-Flash