How much VRAM does Kimi K2.5 need?

Kimi K2.5 (1000B parameters) requires approximately 618.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Kimi K2.5?

The recommended quantization for Kimi K2.5 is Q4_K_M, which balances quality and memory efficiency.

Can it run?

No, Kimi K2.5 requires more memory than RTX 2070 Super 8GB provides.

FWon't run

Too heavy

Using Q4_K_M in vLLM

Capabilities:

Fit status

Too heavy

Decode

2.0 tok/s

TTFT

96800 ms

Safe context

Memory

618.2 GB / 8.0 GB

Weights610.0 GB

KV Cache5.0 GB

Runtime2.4 GB

Headroom0.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	F	Too heavy	2.0 tok/s	140800 ms	4K
Chat	F	Too heavy	2.0 tok/s	52800 ms	4K
Coding	F	Too heavy	2.0 tok/s	96800 ms	4K
RAG	F	Too heavy	2.0 tok/s	176000 ms	4K
Reasoning	F	Too heavy	2.0 tok/s	114400 ms	4K

How Kimi K2.5 (1000B params) fits at each quantization level on RTX 2070 Super 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	390.0 GB	Low	F0
Q3_K_S	3	490.0 GB	Low	F0
NVFP4	4