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
Qwen2-72B-Instruct is a 72-billion-parameter language model released by Alibaba's Qwen team in June 2024, serving as the flagship of the Qwen2 generation and representing a major step in open-weight multilingual modeling. Trained on data spanning 30+ languages with strong coverage of code and structured reasoning, the model was among the first openly released 70B-class models to demonstrate competitive performance across diverse benchmarks. It established the foundation architecture and training methodology that the Qwen2.5 series would later extend.
1 year newer
Qwen2 72B Instruct
Alibaba / Qwen
2024-06-07

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 72B Instruct
Gemini 3.1 Pro
Qwen2 72B Instruct
Gemini 3.1 Pro
Qwen2 72B Instruct