Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Moonshot AI
Kimi K2, released by Moonshot AI on July 11, 2025, is an open-weight Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters per inference. It features a 256K token context window (expanded from 128K in an September 2025 update) and demonstrated strong performance on agentic coding benchmarks. Kimi K2 targets software engineering agents, tool-use workflows, and open-source deployments under a modified MIT license.
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.
3 months newer
Qwen2.5-Omni-7B
Alibaba / Qwen
2025-03-26
Kimi K2
Moonshot AI
2025-07-11
Context window and performance specifications
Available providers and their performance metrics
Kimi K2
Moonshot AI
Qwen2.5-Omni-7B
Kimi K2
Qwen2.5-Omni-7B
Kimi K2
Qwen2.5-Omni-7B