Comprehensive side-by-side LLM comparison
Llama-3.3 Nemotron Super 49B leads with 16.9% higher average benchmark score. Gemma 3 27B supports multimodal inputs. Overall, Llama-3.3 Nemotron Super 49B is the stronger choice for coding tasks.
Google DeepMind
Gemma 3 27B is a 27-billion-parameter open-weight model from Google DeepMind, released in March 2025 alongside the Gemma 3 12B as the higher-capability variant in the series, built with native vision-language support for text and image inputs across a 128K token context window. Among the Gemma 3 releases, the 27B delivered the strongest results on instruction-following and knowledge-intensive reasoning tasks, making it the preferred option for developers needing greater accuracy from a self-hostable model. Its open-weight availability under a permissive license made it a common starting point for vision-language fine-tuning projects.
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 27B
Google DeepMind
2025-03-12
Average performance across 1 common benchmarks
Gemma 3 27B
Llama-3.3 Nemotron Super 49B
Performance comparison across key benchmark categories
Gemma 3 27B
Llama-3.3 Nemotron Super 49B
Available providers and their performance metrics
Gemma 3 27B
Llama-3.3 Nemotron Super 49B
Gemma 3 27B
Llama-3.3 Nemotron Super 49B