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Kimi K2.5

by Moonshot AI · kimi family

1040B

parameters

text-generation code-generation reasoning multilingual vision tool-use math

Kimi K2.5 is Moonshot AI's flagship open-weight model — a 1.04 trillion parameter Mixture-of-Experts with 32B active parameters per token. It employs 384 experts with 8 activated per forward pass, using Multi-head Latent Attention (MLA) to cut memory bandwidth by 40-50%. Trained on 15 trillion mixed visual and text tokens, it delivers state-of-the-art coding (76.8% SWE-Bench Verified) and agentic capabilities with Agent Swarm technology coordinating up to 100 sub-agents. At 374 GB even at aggressive 2-bit quantization, Kimi K2.5 demands enterprise-grade hardware — multiple high-VRAM GPUs or a Mac with 400 GB+ unified memory. The native INT4 weights from Quantization-Aware Training make 4-bit quantization practically lossless compared to FP16. Available on Ollama with a cloud-backed tag for those without the local resources.

Quick Start with Ollama

ollama run latest
Resources Ollama Hugging Face Official Page Research Paper
Creator Moonshot AI
Parameters 1T
Architecture mixture-of-experts
Context 250K tokens
Released Jan 15, 2026
License Modified MIT
Ollama kimi-k2.5

Quantization Options

Format File Size VRAM Required Quality Ollama Tag
Q2_K rec 374 GB 390 GB latest
Q4_K_M 580 GB 600 GB q4_K_M
Q8_0 1040 GB 1060 GB q8_0

Compatible Hardware

Q2_K requires 390 GB VRAM

Compatible Hardware

HardwareVRAMTypeFitEst. Speed
Mac Studio M4 Ultra 512GB512 GBmacRuns~2 tok/s
106 hardware device(s) cannot run this model at Q2_K.

Benchmark Scores

87.1
mmlu