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Kimi K3 πŸŒ™ (Moonshot AI) Review (2026)

The world's first open 2.8T-parameter model with Kimi Delta Attention and Stable LatentMoE.

β˜… 4.9
Editorial Rating
Pricing Model:
Open Weights (Kimi License)
Recommended For:
Massive context reasoning (1M+ tokens), multimodal CAD/game engineering, and tool orchestration
Test Kimi K3 on Moonshot Web β†—

Technical Overview

Kimi K3 by Moonshot AI is an open-weight 2.8-trillion parameter multimodal titan. By scaling MoE sparsity to 896 experts and activating only 16 per token, Kimi K3 maintains lightning-fast execution while retaining world-class contextual fidelity across 1,000,000 tokens.

Quick Start Command

BASH / TERMINAL
pip install transformers compressed-tensors && vllm serve moonshotai/Kimi-K3

Advantages (Pros)

  • βœ“ 2.8T total parameters with Stable LatentMoE activating only 16 out of 896 specialized experts
  • βœ“ Kimi Delta Attention (KDA) + Attention Residuals (AttnRes) yields 2.5Γ— scaling efficiency over K2
  • βœ“ #1 among open-weights models on Toolathlon Verified (76.5%) and Terminal Bench 2.1 (88.3%)
  • βœ“ Native multimodal vision encoder supports vision-in-the-loop debugging and UI/CAD generation

Considerations (Cons)

  • βœ— Requires specialized compressed-tensors library or custom vLLM fork for inference
  • βœ— High aggregate memory bandwidth required to maintain high expert-selection throughput