Comprehensive side-by-side LLM comparison
Gemini 3.1 Pro leads with 7.2% higher average benchmark score. Gemini 3.1 Pro supports multimodal inputs. Overall, Gemini 3.1 Pro is the stronger choice for coding tasks.
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.
Xiaomi
MiMo-V2-Flash, released by Xiaomi on December 16, 2025, is a Mixture-of-Experts large language model with 309 billion total parameters and 15 billion active parameters per inference, designed for high-speed reasoning and agentic workflows. It features a 256K token context window, processes up to 150 tokens per second, and was trained on 27 trillion tokens. MiMo-V2-Flash targets open-source deployments requiring fast, capable coding and reasoning with an efficient inference footprint, under an MIT license.
2 months newer
MiMo-V2-Flash
Xiaomi
2025-12-16

Gemini 3.1 Pro
Google DeepMind
2026-02-19
Context window and performance specifications
Average performance across 1 common benchmarks
Gemini 3.1 Pro
MiMo-V2-Flash
Performance comparison across key benchmark categories
Gemini 3.1 Pro
MiMo-V2-Flash
Gemini 3.1 Pro
2025-01
Available providers and their performance metrics
Gemini 3.1 Pro
MiMo-V2-Flash
Gemini 3.1 Pro
MiMo-V2-Flash
Gemini 3.1 Pro
MiMo-V2-Flash