Kimi K2p5 moves to version kimi-k2.5
Moonshot AI updates its flagship model nomenclature to kimi-k2.5 for improved version tracking.
Version now kimi-k2.5 (was kimi-k2p5) — verified by the OnAirToday AI Progress Tracker against Moonshot's published documentation.
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The OnAirToday AI Progress Tracker recorded a verified change to Moonshot's Kimi K2p5 (version kimi-k2.5): Version now kimi-k2.5 (was kimi-k2p5).
Kimi K2.5 is Moonshot AI’s open-weight multimodal model for text, image and video understanding, coding, and tool-using workflows. Published results distinguish standalone reasoning from tool-assisted and Agent Swarm configurations, which should not be treated as interchangeable.
What changed in this review:
- Uses the official Kimi K2.5 API identifier, kimi-k2.5.
- Adds the documented 256K-token context window.
- Adds documented USD pricing per million tokens: $0.60 uncached input and $3.00 output.
- Adds published AIME 2025, SWE-bench Verified, Humanity's Last Exam and Terminal-Bench results.
- Kimi K3 appears in Amazon Bedrock's September 18 announcement; this profile remains specific to K2.5.
- Adds the reported Kimi K3-assisted Redis exploit demonstration, explicitly distinguished from a K2.5 vulnerability.
Teams building on Kimi K2p5 should confirm limits, pricing and benchmark coverage against the vendor's own documentation before relying on these figures.
The full profile — capabilities, benchmark citations, known flaws and risk guidance — is on the tracker at /ai-models/kimi-k2p5.
References:
- https://huggingface.co/moonshotai/Kimi-K2.5
- https://github.com/MoonshotAI/Kimi-K2.5
- https://platform.moonshot.ai/docs/pricing/chat
- https://aws.amazon.com/blogs/machine-learning/introducing-kimi-k3-on-amazon-bedrock/
Generated insight by OnAirToday AI
The incremental versioning of Moonshot's Kimi model highlights the rapid, iterative pace of development within China's competitive AI ecosystem. This update signals a continued refinement of architecture as companies strive for superior performance benchmarks in domestic language processing.

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