How much VRAM does Yi 1.5 9B need?

Yi 1.5 9B (9B parameters) requires approximately 9.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Yi 1.5 9B?

The recommended quantization for Yi 1.5 9B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, Intel Arc B580 12GB can run Yi 1.5 9B with a C grade (Runs well). Expected decode speed: 59.8 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

59.8 tok/s

TTFT

3237 ms

Safe context

Memory

9.3 GB / 12.0 GB

Weights5.5 GB

KV Cache1.4 GB

Runtime1.2 GB

Headroom1.2 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Tight fit	39.9 tok/s	7063 ms	4K
Chat	C	Runs well	39.9 tok/s	2649 ms	4K
Coding	C	Runs well	59.8 tok/s	3237 ms	4K
RAG	C	Tight fit	39.9 tok/s	8829 ms	4K
Reasoning	C	Runs well	39.9 tok/s	5739 ms	4K

How Yi 1.5 9B (9B params) fits at each quantization level on Intel Arc B580 12GB (12.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	D35
Q3_K_S	3	4.4 GB	Low	D36
NVFP4	4

Ollama

ollama run yi-1.5-9b

HuggingFace

huggingface-cli download yi-1.5-9b

Upgrade options

RX 9070 XT 16GBBudget pick

C74.6 tok/s decode

~$549 MSRP

RTX 5070 Ti 16GBBest value

C104.5 tok/s decode

~$749 MSRP

RTX 4070 Ti Super 16GBBiggest leap

C97.9 tok/s decode

~$799 MSRP