Comprehensive side-by-side LLM comparison
Qwen2.5 14B Instruct leads with 8.8% higher average benchmark score. Qwen2.5-Omni-7B supports multimodal inputs. Overall, Qwen2.5 14B Instruct is the stronger choice for coding tasks.
Alibaba / Qwen
Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.
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.
6 months newer
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Qwen2.5-Omni-7B
Alibaba / Qwen
2025-03-26
Average performance across 1 common benchmarks
Qwen2.5 14B Instruct
Qwen2.5-Omni-7B
Performance comparison across key benchmark categories
Qwen2.5 14B Instruct
Qwen2.5-Omni-7B
Available providers and their performance metrics
Qwen2.5 14B Instruct
Qwen2.5-Omni-7B
Qwen2.5 14B Instruct
Qwen2.5-Omni-7B