Comprehensive side-by-side LLM comparison
Llama 3.1 Nemotron Nano 8B leads with 11.6% higher average benchmark score. Gemma 3 12B supports multimodal inputs. Overall, Llama 3.1 Nemotron Nano 8B 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-3.1-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.
2 months newer

Llama 3.1 Nemotron Nano 8B
NVIDIA
2025-01-06

Gemma 3 12B
Google DeepMind
2025-03-12
Average performance across 1 common benchmarks
Gemma 3 12B
Llama 3.1 Nemotron Nano 8B
Performance comparison across key benchmark categories
Gemma 3 12B
Llama 3.1 Nemotron Nano 8B
Available providers and their performance metrics
Gemma 3 12B
Llama 3.1 Nemotron Nano 8B
Gemma 3 12B
Llama 3.1 Nemotron Nano 8B