Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
Moonshot AI
Kimi K2.5, released by Moonshot AI in January 2026, is an updated Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters. It builds on Kimi K2 with improved coding performance across multiple languages and an expanded context window. Kimi K2.5 targets agentic development workflows, polyglot code generation, and open-source deployments requiring large-scale MoE reasoning.
Alibaba / Qwen
Qwen2.5-Coder-7B-Instruct is a 7-billion-parameter code-specialized model from Alibaba, released in November 2024 as part of the Qwen2.5-Coder family, trained on a curated corpus spanning 92 programming languages with emphasis on code generation, debugging, and fill-in-the-middle completion. Built on the Qwen2.5 architecture, it extends the base series' improvements in instruction-following and long-context handling to coding-specific tasks within a compact deployable footprint. It became popular for integration into IDE extensions, CI pipelines, and self-hosted code assistant tools.
1 year newer
Qwen2.5-Coder 7B Instruct
Alibaba / Qwen
2024-11-12
Kimi K2.5
Moonshot AI
2026-01
Context window and performance specifications
Available providers and their performance metrics
Kimi K2.5
Moonshot AI
Qwen2.5-Coder 7B Instruct
Kimi K2.5
Qwen2.5-Coder 7B Instruct
Kimi K2.5
Qwen2.5-Coder 7B Instruct