Question 1

How much VRAM does Kimi-K2-Base need?

Accepted Answer

Kimi-K2-Base (1026.5B) requires approximately 2339.4491386413574 GB of VRAM at full precision (FP16), 1169.7 GB at 8-bit quantization (Q8), and 584.9 GB at 4-bit quantization (Q4). The actual VRAM usage may be slightly higher due to KV cache and runtime overhead.

Question 2

What GPUs can run Kimi-K2-Base?

Accepted Answer

We currently have no compatible GPUs indexed for Kimi-K2-Base. This may be because the model's VRAM requirements exceed available GPUs in our database, or VRAM data hasn't been computed yet.

Question 3

What is the cheapest GPU to run Kimi-K2-Base?

Accepted Answer

We don't currently have cloud pricing data for GPUs compatible with Kimi-K2-Base. Cloud pricing data is updated regularly — check back soon.

Question 4

Can Kimi-K2-Base run on consumer hardware?

Accepted Answer

Kimi-K2-Base requires approximately 2339.4491386413574 GB of VRAM at FP16, and even with 4-bit quantization (Q4) it needs about 584.9 GB. This exceeds the 24 GB available on the highest-end consumer GPU (RTX 4090), so Kimi-K2-Base requires datacenter or cloud GPUs.

Question 5

What quantization options are available for Kimi-K2-Base?

Accepted Answer

Kimi-K2-Base supports the following quantization levels: FP16 (full precision): ~2339.4491386413574 GB, Q8 (8-bit): ~1169.7 GB, Q6 (6-bit): ~877.3 GB, Q4 (4-bit): ~584.9 GB. Lower quantization reduces VRAM usage at the cost of some quality loss. Q8 offers a good balance between quality and memory savings, while Q4 provides maximum compression. As a Mixture of Experts (MoE) model with 384 experts (8 active), Kimi-K2-Base has a larger total weight size but only activates a subset of parameters per token, which can affect effective memory usage during inference.

Kimi-K2-Base

VRAM Requirements

Compatible GPUs

Kimi-K2-Base FAQ

VRAM requirements for Kimi-K2-Base at different quantization levels
Quantization	VRAM Required
FP16	2339.4 GB
Q8	1169.7 GB
Q6	877.3 GB
Q4	584.9 GB