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Kimi K2 Thinking

Kimi K2 Thinking is an open-source thinking model released by Moonshot AI as the latest evolution of the Kimi K2 lineage, distributed on Hugging Face under a Modified MIT license. According to the official model card, it was built as a thinking agent that reasons step-by-step while dynamically invoking tools, an end-to-end trained approach that interleaves chain-of-thought reasoning with function calls so it can sustain autonomous research, coding, and writing workflows across hundreds of sequential steps. The card highlights a native INT4 quantization design that preserves accuracy while reducing inference latency and GPU memory, and points to a 256k context window that supports the long, multi-step trajectories the model is meant to run.

In independent commentary, the model is described as a notable open release from a rapidly rising Chinese AI lab, signaling continued momentum in openly available reasoning systems. Its practical fit centers on agentic applications that demand stable, long-horizon tool orchestration rather than single-shot answers, making it well suited for developers who want a transparent base for custom agent pipelines, automated research assistants, and extended coding workflows. As an open-weight model with permissive licensing, it also offers a foundation for downstream fine-tuning and self-hosted deployment where control over reasoning behavior and tool integration matters.

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Provider
Charm Hyper
Model key
kimi-k2-thinking
Release date
Sep 2, 2026
Last updated
Sep 2, 2026
Knowledge cutoff
2024-08
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.60
Output token cost
$2.50

Limits

Output tokens
26,214 tokens
Context window
262,144 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Kimi K2 Thinking

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CoverageBenchmark

BenchmarkList's aggregator page for MoonshotAI Kimi K2 Thinking lists 70 benchmark rows with a snapshot timestamp of 2026-06-10. Agentic evaluations show a median 29th-percentile placement across 17 evals, including Tau2-Bench Telecom Success Rate at 93.0% (89th percentile), Terminal-Bench Hard Success Rate at 31.1% (7 The page includes comparison columns referencing other models such as Fable 5.1, Claude Opus 5, Kimi K3, Qwen3.8-2.4T-A95B, Qwen3.8-Flash-Next, GLM 5.3, and GLM 5.3 Flash, with field-leader deltas computed against them — for example, Fable 5 leading Terminal-Bench Hard at 62.9%. Because some of these comparator model n

Charm Hyper

CoverageBenchmark

CNBC reported on November 6, 2025 that Beijing-based Moonshot AI, backed by Alibaba, released Kimi K2 Thinking — its second major model update in four months — with claims of superior "agentic" capabilities versus OpenAI's ChatGPT. The model can automatically select 200 to 300 tools to complete tasks without explicit s Kimi K2 Thinking launched amid escalating U.S.–China AI competition, with Nvidia CEO Jensen Huang publicly urging the U.S. to maintain pace. CNBC frames Moonshot's positioning alongside DeepSeek, noting both Chinese labs have emphasized cost efficiency relative to U.S. hyperscalers. The article does not provide API spe

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