Comprehensive side-by-side LLM comparison
Gemini 3.1 Pro offers 849.9K more tokens in context window than Kimi K2. Kimi K2 is $10.90 cheaper per million tokens. 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.
Moonshot AI
Kimi K2, released by Moonshot AI on July 11, 2025, is an open-weight Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters per inference. It features a 256K token context window (expanded from 128K in an September 2025 update) and demonstrated strong performance on agentic coding benchmarks. Kimi K2 targets software engineering agents, tool-use workflows, and open-source deployments under a modified MIT license.
7 months newer
Kimi K2
Moonshot AI
2025-07-11

Gemini 3.1 Pro
Google DeepMind
2026-02-19
Cost per million tokens (USD)
Gemini 3.1 Pro
Kimi K2
Context window and performance specifications
Gemini 3.1 Pro
2025-01
Available providers and their performance metrics
Gemini 3.1 Pro
Kimi K2
Gemini 3.1 Pro
Kimi K2
Gemini 3.1 Pro
Kimi K2
Moonshot AI