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
Qwen2.5-32B-Instruct is a 32-billion-parameter open-weight model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens. The model is positioned as a high-capability option for developers with access to multi-GPU setups or high-VRAM hardware, offering strong performance on coding, structured reasoning, and multilingual tasks while remaining fully open under Apache 2.0. Its 128K context window and support for structured output generation made it a popular choice for document processing and agentic workflows in the open-source community.
1 year newer
Qwen2.5 32B Instruct
Alibaba / Qwen
2024-09-19

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 32B Instruct
Gemini 3.1 Pro
Qwen2.5 32B Instruct
Gemini 3.1 Pro
Qwen2.5 32B Instruct