Comprehensive side-by-side LLM comparison
Kimi K2 leads with 20.5% higher average benchmark score. Gemini 2.5 Flash offers 744.0K more tokens in context window than Kimi K2. Gemini 2.5 Flash is $2.35 cheaper per million tokens. Gemini 2.5 Flash supports multimodal inputs. Overall, Kimi K2 is the stronger choice for coding tasks.
Google DeepMind
Gemini 2.5 Flash, released by Google in June 2025, is a large language model from the Gemini 2.5 family optimized for high-throughput, cost-efficient deployments with multimodal reasoning. It features a 1M token context window, hybrid thinking control, and native support for text, image, video, and audio input. Gemini 2.5 Flash targets latency-sensitive applications, document analysis, and high-volume API workloads that benefit from combined reasoning and generation in a single model.
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.
24 days newer

Gemini 2.5 Flash
Google DeepMind
2025-06-17
Kimi K2
Moonshot AI
2025-07-11
Cost per million tokens (USD)
Gemini 2.5 Flash
Kimi K2
Context window and performance specifications
Average performance across 1 common benchmarks
Gemini 2.5 Flash
Kimi K2
Performance comparison across key benchmark categories
Gemini 2.5 Flash
Kimi K2
Available providers and their performance metrics
Gemini 2.5 Flash
Google Cloud Vertex AI
Kimi K2
Gemini 2.5 Flash
Kimi K2
Gemini 2.5 Flash
Kimi K2
Moonshot AI