Kimi K2 Thinking unlocks deep chain-of-thought reasoning in Moonshot's trillion-parameter model — the strongest open reasoning model from China, tackling olympiad math and complex software engineering with step-by-step logic.
Kimi-K2 Thinking is an AI model released July 2025 by Moonshot AI, a leading organization in large language model research. Kimi-K2 with extended thinking — chain-of-thought for deep math, science, and complex problem solving. With 1T total (32B active) and a 128K tokens context window, Kimi-K2 Thinking is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.
Kimi-K2 Thinking employs a Mixture-of-Experts (MoE) architecture with 1T total (32B active). In a MoE design, only a subset of "expert" sub-networks activates for each token during inference — Kimi-K2 Thinking has 1T total (32B active) total parameters but uses only a fraction per token. This allows the model to store significantly more learned knowledge than a comparably-priced dense model. MoE architectures have proven effective at reaching frontier-level capability while keeping serving costs manageable — a key reason Kimi-K2 Thinking can be offered at the scale that platforms like LITHOVEX AI make possible.
As of 2026-10-16, Kimi-K2 Thinking by Moonshot AI demonstrates measurable performance on standard AI evaluation benchmarks. On AIME 2025 — which tests advanced competition mathematics at the highest US high school level — it achieves 84.1%. For software engineering tasks, Kimi-K2 Thinking scores 67.3% on SWE-bench Verified, which tests ability to resolve real GitHub issues in production Python repositories. In mathematical reasoning, Kimi-K2 Thinking records 84.1% on AIME 2025. Across all 4 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Kimi-K2 Thinking — at 1T total (32B active) of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
The primary strengths of Kimi-K2 Thinking are: 84.1% AIME 2025 — near-human on elite competition mathematics; Extended thinking mode: auditable step-by-step reasoning; 67.3% SWE-bench in thinking mode. These make it particularly well-suited for Complex mathematical proofs, Research-grade scientific reasoning, Auditable AI reasoning workflows. Users working on complex, multi-step problems benefit most from Kimi-K2 Thinking's ability to maintain coherence across long inputs and produce structured, verifiable outputs.
Like all current AI systems, Kimi-K2 Thinking has limitations: Thinking mode adds significant latency; Same infrastructure requirements. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. Moonshot AI continues to improve Kimi-K2 Thinking through ongoing research.
Kimi-K2 Thinking is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making Kimi-K2 Thinking accessible to students, researchers, developers, and early-stage teams globally.
As of 2026-10-16, Kimi-K2 Thinking by Moonshot AI demonstrates measurable performance on standard AI evaluation benchmarks. On AIME 2025 — which tests advanced competition mathematics at the highest US high school level — it achieves 84.1%. For software engineering tasks, Kimi-K2 Thinking scores 67.3% on SWE-bench Verified, which tests ability to resolve real GitHub issues in production Python repositories. In mathematical reasoning, Kimi-K2 Thinking records 84.1% on AIME 2025. Across all 4 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Kimi-K2 Thinking — at 1T total (32B active) of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
MoE 1T total / 32B active, extended reasoning mode
The training pipeline for Kimi-K2 Thinking involves multiple stages: large-scale pretraining on diverse multilingual text and code corpora to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety. Moonshot AI's research team — based in China — has optimized Kimi-K2 Thinking for the specific capability profile described above.
Inference efficiency: Kimi-K2 Thinking at 1T total (32B active) is designed to deliver quality outputs at practical serving speeds. Its 128K tokens context window enables processing entire documents, multi-file codebases, and extended conversation histories — particularly valuable for contract review, technical documentation analysis, and codebase-level AI assistance.
Getting started with Kimi-K2 Thinking on LITHOVEX AI takes under two minutes. Follow these steps:
For best results with Kimi-K2 Thinking: provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions. Since Kimi-K2 Thinking supports extended reasoning, prompting it to "think step by step" or "show your reasoning" activates deeper chain-of-thought analysis for math, logic, and complex problems.
Olympiad-level mathematics and competition problems
Complex multi-step software architecture reasoning
Scientific hypothesis testing and analysis
Advanced legal and logical argumentation
Quantitative research and financial modeling
Moonshot AI is a Beijing-based startup founded in 2023, focused on ultra-long context language models and advanced agentic reasoning. Best known for its Kimi assistant — which gained prominence for processing extremely long documents — the company scaled rapidly to frontier-level models. Kimi K2, released in 2025, deploys 1 trillion total parameters in a Mixture-of-Experts configuration and achieves top scores on SWE-bench Verified, the gold standard for software engineering AI. Moonshot AI has attracted over $1 billion in funding from investors including Alibaba and Sequoia China, positioning it as one of China's fastest-growing AI research companies.
Funding: $1B+ raised (Alibaba, Sequoia China)
Founded: 2023, headquartered in China.
Kimi-K2 Thinking by Moonshot AI competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.
Both Kimi-K2 Thinking and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.
Kimi-K2 Thinking is released under Kimi K2 Model License, which means you can download and run it on your own hardware. Below are the quickest ways to get started.
LITHOVEX AI runs Kimi-K2 Thinking on cloud infrastructure, so you can use it instantly in your browser without downloading anything, configuring drivers, or managing VRAM. Create a free account and start in under 60 seconds.
Kimi K2 Thinking is China's answer to OpenAI's o1 — a model that reasons deeply before answering. For mathematically rigorous Chinese academic culture and global research communities, it represents a new level of open accessible reasoning capability.
Kimi-K2 Thinking by Moonshot AI has the following version history and notable updates:
For the complete changelog and latest release notes, visit the official Moonshot AI model page.