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Kimi K2 Thinking

Kimi K2 Thinking sits in Moonshot AI's kimi-thinking family and was framed by independent commentary as a landmark open-weights release positioned to compete with leading proprietary systems. Its name signals an explicit focus on extended, deliberate reasoning rather than fast-turnaround chat, and that emphasis is consistent with the "Thinking" branding carried across the broader Kimi lineup. The model belongs to the same ecosystem documented on Moonshot's own platform, where Kimi reasoning variants are presented as long-context, agent-oriented models designed for complex multi-step work.

In practical terms, Kimi K2 Thinking is aimed at developers and teams who want strong reasoning and tool use without giving up the ability to self-host or inspect weights. Its open-weights posture, combined with reasoning-oriented design, makes it well suited to agentic pipelines, multi-step research, and code or analysis tasks where the model can be allowed to think longer before answering. The fact that it ships on Amazon Bedrock means teams can integrate it through a managed endpoint while still benefiting from the open-weights lineage, which is a useful bridge between proprietary convenience and open-model flexibility.

Amazon Bedrockmoonshot.kimi-k2-thinkingkimi-thinking

Quick Info

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Provider
Amazon Bedrock
Model key
moonshot.kimi-k2-thinking
Release date
Dec 2, 2025
Last updated
Dec 2, 2025
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.60
Output token cost
$2.50

Limits

Output tokens
16,000 tokens
Context window
262,143 tokens

Latest news about Kimi K2 Thinking

Amazon Bedrock

CoverageBenchmark

Artificial Analysis benchmarks Kimi K2 Thinking across four API providers: Amazon Bedrock, Microsoft Azure, Google Vertex, and Novita. On Bedrock, the model delivers roughly 122.2 output tokens per second with about 17.81 seconds time-to-first-token and a blended price of $0.79 per 1M tokens, placing Azure and Vertex a For Bedrock users, the data confirms Kimi K2 Thinking is competitively priced against Azure and Vertex but trails both on output throughput and latency, so latency-sensitive workloads may benefit from cross-provider testing. The page also flags Kimi K2 Thinking as deprecated in favor of the newer Kimi K2.5, a signal wo

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