Comprehensive side-by-side LLM comparison
Kimi K2 leads with 15.1% higher average benchmark score. Gemini 2.5 Pro offers 744.0K more tokens in context window than Kimi K2. Kimi K2 is $8.15 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Kimi K2 is the stronger choice for coding tasks.
Google DeepMind
Gemini 2.5 Pro, released by Google in May 2025, is a large language model from the Gemini 2.5 family designed for complex reasoning, coding, and long-context analysis tasks. It features a 1M token context window, native support for text, image, video, and audio input, and integrated thinking capabilities for multi-step problem solving. Gemini 2.5 Pro targets advanced coding workflows, scientific reasoning, and applications requiring deep understanding across large, mixed-modality contexts.
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.
1 month newer

Gemini 2.5 Pro
Google DeepMind
2025-05-20
Kimi K2
Moonshot AI
2025-07-11
Cost per million tokens (USD)
Gemini 2.5 Pro
Kimi K2
Context window and performance specifications
Average performance across 1 common benchmarks
Gemini 2.5 Pro
Kimi K2
Performance comparison across key benchmark categories
Gemini 2.5 Pro
Kimi K2
Available providers and their performance metrics
Gemini 2.5 Pro
Google Cloud Vertex AI
Kimi K2
Gemini 2.5 Pro
Kimi K2
Gemini 2.5 Pro
Kimi K2
Moonshot AI