Question 1

How much VRAM does Phi-tiny-MoE-instruct need?

Accepted Answer

Phi-tiny-MoE-instruct (3.8B) requires approximately 8.393571424484252 GB of VRAM at full precision (FP16), 4.2 GB at 8-bit quantization (Q8), and 2.1 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 Phi-tiny-MoE-instruct?

Accepted Answer

We have 10 compatible GPUs indexed for Phi-tiny-MoE-instruct, including L4, RTX A4000, T4, A40, RTX 3090 and 5 more. Compatibility is determined by whether the GPU's VRAM can fit the model's memory footprint, potentially using quantization to reduce memory usage.

Question 3

What is the cheapest GPU to run Phi-tiny-MoE-instruct?

Accepted Answer

The cheapest GPU to run Phi-tiny-MoE-instruct in the cloud is the L4 at $0.20/hr. Other affordable options include RTX A4000 ($0.25/hr) and T4 ($0.35/hr). Prices reflect the lowest on-demand rate across cloud providers.

Question 4

Can Phi-tiny-MoE-instruct run on consumer hardware?

Accepted Answer

Yes, Phi-tiny-MoE-instruct can run on consumer GPUs like the RTX A4000 (16 GB VRAM) at full precision (FP16). Other compatible consumer GPUs include RTX 3090 and RTX A4500.

Question 5

What quantization options are available for Phi-tiny-MoE-instruct?

Accepted Answer

Phi-tiny-MoE-instruct supports the following quantization levels: FP16 (full precision): ~8.393571424484252 GB, Q8 (8-bit): ~4.2 GB, Q6 (6-bit): ~3.1 GB, Q4 (4-bit): ~2.1 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 16 experts (2 active), Phi-tiny-MoE-instruct has a larger total weight size but only activates a subset of parameters per token, which can affect effective memory usage during inference.

GPU	VRAM	Best Quant	From	Rent
L4	24 GB	FP16	$0.20/hr
RTX A4000	16 GB	FP16	$0.25/hr	Rent
T4	16 GB	FP16	$0.35/hr
A40	48 GB	FP16	$0.44/hr	Rent
RTX 3090	24 GB	FP16	$0.46/hr	Rent
RTX A4500	20 GB	FP16	$0.50/hr	Rent
L40S	48 GB	FP16	$0.86/hr	Rent
RTX 5090	32 GB	FP16	$0.99/hr	Rent
A10G	24 GB	FP16	$1.01/hr
A10	24 GB	FP16	$1.29/hr

Phi-tiny-MoE-instruct

VRAM Requirements

Compatible GPUs

Phi-tiny-MoE-instruct FAQ

VRAM requirements for Phi-tiny-MoE-instruct at different quantization levels
Quantization	VRAM Required
FP16	8.4 GB
Q8	4.2 GB
Q6	3.1 GB
Q4	2.1 GB