Comprehensive side-by-side LLM comparison
Llama-3.3 Nemotron Super 49B leads with 18.1% higher average benchmark score. Qwen2.5-Omni-7B supports multimodal inputs. Overall, Llama-3.3 Nemotron Super 49B is the stronger choice for coding tasks.
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.
Alibaba / Qwen
Qwen2.5-Omni-7B is a 7-billion-parameter end-to-end multimodal model from Alibaba, released in March 2025 as part of the Omni series designed to unify perception and generation across text, images, audio, and video in a single model architecture. Unlike pipeline-based multimodal systems, it processes all modalities end-to-end and can generate both text and speech outputs, targeting use cases in voice assistants, multimodal agents, and real-time interactive applications. Its compact size made it notable for on-device and resource-constrained multimodal deployments.
25 days newer

Llama-3.3 Nemotron Super 49B
NVIDIA
2025-03-01
Qwen2.5-Omni-7B
Alibaba / Qwen
2025-03-26
Average performance across 1 common benchmarks
Llama-3.3 Nemotron Super 49B
Qwen2.5-Omni-7B
Performance comparison across key benchmark categories
Llama-3.3 Nemotron Super 49B
Qwen2.5-Omni-7B
Available providers and their performance metrics
Llama-3.3 Nemotron Super 49B
Qwen2.5-Omni-7B
Llama-3.3 Nemotron Super 49B
Qwen2.5-Omni-7B