Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...
Tested on 12 benchmarks · BenchGecko score 57.7. Top scores: HELM — WildBench (86.2%), Lech Mazur Writing (85.6%), HELM — IFEval (85.0%).
Kimi K2.5 scores 57.1 (99% as good) at $0.45/1M input · 21% cheaper
Multi-language code editing from Aider. Tests editing ability across Python, JavaScript, TypeScript, Java, C++, Go, Rust, and more.
Unusual and adversarial machine learning challenges. Tests robustness of reasoning about edge cases in ML systems.
Complex terminal-based engineering tasks. Models must use command-line tools, navigate filesystems, and debug systems through shell interaction.
Stanford HELM WildBench evaluation. Tests reasoning on challenging real-world tasks.
Deceptively simple questions that humans find easy but AI models often get wrong. Tests common sense and reasoning gaps.
Stanford HELM evaluation of mathematical reasoning across diverse problem types.
- Typetext
- Context131K tokens (~66 books)
- ReleasedJul 2025
- LicenseOpen Source
- StatusActive
- Cost / Message~$0.003
Frequently Asked Questions
Key facts · as of 2026-10-05
- Kimi K2 0711 by moonshotai. BenchGecko score 57.7, rank 102 of 312 scored models (normalized average of public benchmark scores).
- List price $0.57 input · $2.30 output per 1M tokens (as of 2026-10-05).
- Sold by 1 provider (as of 2026-10-05): Novita (fp8) $0.57 in / $2.30 out.
How to cite · data as of 2026-10-05
Kimi K2 0711 · benchmarks, pricing and providers. BenchGecko, data as of 2026-10-05. https://benchgecko.ai/model/kimi-k2
Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP