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...
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MoonshotAI: Kimi K2 0711 holds the #273 spot for context size out of 392 chat models in the CoreAI catalog — 131K tokens, roughly 98,304 words or 197 pages of text in a single conversation. On price, it is the #74 cheapest of 183 standard-tier models by input cost. It joined the catalog on 2025-07-11.
Every model in this table is available on CoreAI — open the web app and run the same prompt through MoonshotAI: Kimi K2 0711 and MoonshotAI: Kimi K2.5 side by side to judge with your own eyes.
A typical question (about 1,000 tokens in, 500 out) runs $0.00172 on MoonshotAI: Kimi K2 0711's raw per-token rates; a heavy session with a 50K-token document costs about $0.040. On CoreAI you don't juggle these numbers — one subscription covers MoonshotAI: Kimi K2 0711 and 300+ other models under a plan usage limit, with no API keys. See plans.
MoonshotAI: Kimi K2 0711 handles 131K tokens of context — roughly 98,304 words, or about 197 pages of text in one conversation.
MoonshotAI: Kimi K2 0711's underlying rates are $0.57 per 1M input tokens and $2.3 per 1M output tokens. On CoreAI it is included in one subscription alongside 300+ models, so there is no per-token billing to manage.
No — MoonshotAI: Kimi K2 0711 is text-only. If you need image understanding, its standard-tier peers with vision are listed in the comparison table above.
No — MoonshotAI: Kimi K2 0711 answers directly without an extended reasoning phase, which usually means faster responses.
Open the CoreAI web app or the iOS/Android app, pick MoonshotAI: Kimi K2 0711 in the model selector, and chat — no API key, no per-token billing. One subscription covers MoonshotAI: Kimi K2 0711 and 300+ other models.
The closest alternatives on CoreAI are MoonshotAI: Kimi K2.5, Qwen: Qwen3 VL 235B A22B Instruct, inclusionAI: Ling-2.6-flash — similar tier and capability. The fastest way to choose is running one prompt through them side by side in CoreAI's Compare view.
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