Kimi-K2-Instruct-0905: hardware requirements
Kimi-K2-Instruct-0905 needs about 632 GB of memory at Q4 quantization — a 621 GB download plus room for context and overhead. That is beyond consumer hardware; use it through an API instead.
Parameters
1026B
Tier
Server only
Licence
See model card
Released
2025-09-05
Will it run on your machine?
8GB RAMNot enough memory16GB RAMNot enough memory32GB RAMNot enough memory64GB RAMNot enough memory128GB RAMNot enough memory8GB VRAMNot enough memory12GB VRAMNot enough memory16GB VRAMNot enough memory24GB VRAMNot enough memory32GB VRAMNot enough memory
Download sizes by quantization
Lower quantization means a smaller file and less memory, at some cost to quality. Q4_K_M is the usual starting point. What is this?
| Quant | Download | RAM @ 4K | RAM @ 32K | Source |
|---|---|---|---|---|
| Q4_K_Mrecommended | 621 GB | 632 GB | 682 GB | measured |
| Q5_K_M | 729 GB | 739 GB | 789 GB | measured |
| Q6_K | 843 GB | 853 GB | 903 GB | measured |
| Q8_0 | 1091 GB | 1101 GB | 1152 GB | measured |
| BF16 | 2053 GB | 2064 GB | 2114 GB | measured |
“Measured” sizes are read from published GGUF files (unsloth/Kimi-K2-Instruct-0905-GGUF). “Estimated” sizes are derived from the parameter count and are typically within a few percent. The RAM columns add the context cache and runtime overhead to the download size.