Comprehensive side-by-side LLM comparison
Llama-3.3 Nemotron Super 49B leads with 18.3% higher average benchmark score. Gemma 3 12B supports multimodal inputs. Overall, Llama-3.3 Nemotron Super 49B is the stronger choice for coding tasks.
Google DeepMind
Gemma 3 12B is a 12-billion-parameter open-weight model from Google DeepMind, released in March 2025 as part of the Gemma 3 series designed to bring multimodal reasoning to accessible hardware. The model supports both text and image inputs across a 128K token context window, extending the vision capabilities that defined the Gemma 3 generation compared to earlier text-only Gemma releases. It became widely adopted for domain-specific fine-tuning in research and enterprise settings where full multimodal capability was needed without the infrastructure demands of larger frontier models.
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.
11 days newer

Llama-3.3 Nemotron Super 49B
NVIDIA
2025-03-01

Gemma 3 12B
Google DeepMind
2025-03-12
Average performance across 1 common benchmarks
Gemma 3 12B
Llama-3.3 Nemotron Super 49B
Performance comparison across key benchmark categories
Gemma 3 12B
Llama-3.3 Nemotron Super 49B
Available providers and their performance metrics
Gemma 3 12B
Llama-3.3 Nemotron Super 49B
Gemma 3 12B
Llama-3.3 Nemotron Super 49B