Comprehensive side-by-side LLM comparison
Gemma 3 27B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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-3.1-Nemotron-Ultra-253B-v1 is a 253-billion-parameter model from NVIDIA, derived from Meta's Llama 3.1 405B using neural architecture search (NAS) compression combined with NVIDIA's Nemotron post-training pipeline, which recovers and exceeds the base model's capability after structural compression. Released in April 2025, it supports toggling between a standard instruction mode and an extended reasoning mode via system prompt, allowing the same model to handle both rapid responses and deliberate chain-of-thought tasks. It is the flagship of the Nemotron family, available open-weight on HuggingFace and through NVIDIA NIM for enterprise inference.
26 days newer

Gemma 3 27B
Google DeepMind
2025-03-12

Llama-3.1 Nemotron Ultra 253B
NVIDIA
2025-04-07
Available providers and their performance metrics
Gemma 3 27B
Llama-3.1 Nemotron Ultra 253B
Gemma 3 27B
Llama-3.1 Nemotron Ultra 253B