Comprehensive side-by-side LLM comparison
Gemini 3.1 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemini 3.1 Pro is a multimodal language model from Google DeepMind, released in preview in February 2026 as a point-version upgrade to Gemini 3 Pro focused on improving reasoning depth, factual grounding, and coding and agentic task performance. The model accepts text, images, video, audio, and PDFs as inputs across a 1M token context window, extending the multimodal breadth of the Gemini 3 series with a companion endpoint specifically optimized for custom tool use in agentic pipelines. Google describes it as built to refine the reliability and performance of the Gemini 3 Pro series, reflecting an incremental engineering iteration rather than an architectural overhaul.
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

Gemini 3.1 Pro
Google DeepMind
2026-02-19
Context window and performance specifications
Gemini 3.1 Pro
2025-01
Available providers and their performance metrics
Gemini 3.1 Pro
Qwen2.5-Coder 7B Instruct
Gemini 3.1 Pro
Qwen2.5-Coder 7B Instruct
Gemini 3.1 Pro
Qwen2.5-Coder 7B Instruct