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Moonshot's tech blog opens "Today, we are introducing Kimi K2.5" with figure files stamped 20260127; the Hugging Face[2] model card went public on 2026-01-27 and OpenRouter[3] listed kimi-k2.5 that day, with The Decoder[6] reporting it on 28 January.
Moonshot's model card: native multimodal agentic model, 1T total / 32B activated parameters, 256K context, MoonViT vision encoder, Modified MIT license and the K2.5 (Thinking) benchmark table against GPT-5.2 (xhigh), Claude 4.5 Opus, Gemini 3 Pro and DeepSeek V3.2.[1]
OpenRouter's record: created 2026-01-27, 262,144-token context, text and image input and third-party provider prices of $0.49 to $0.60 per million input tokens and $2.50 to $3.33 output.
17 February analysis of the PARL training method: only the orchestrator is trained while sub-agents stay frozen, the reward counters "serial collapse", and K2.5 beat GPT-5.2 Pro on BrowseComp and Claude Opus 4.5 on WideSearch.[1]
Kimi[1] Team's technical report (submitted 2 February 2026): joint text-vision pre-training, vision-free SFT and joint RL, plus Agent Swarm, which cuts latency by up to 4.5x against single-agent baselines.
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