Yi 1.5 9B Chat — VRAM, Speed & Local Setup

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

Written by Jakub Rusinowski · Last updated May 13, 2024

Model library → Yi 1.5 Family → Yi 1.5 9B Chat

An upgrade to the popular 6B/9B class. Punchy performance for consumer cards.

Yi 1.5 9B Chat needs about 6 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters	9 Billion
Context window	32,000
Architecture	Dense
Provider	01.AI
Licence	Yi License
Specified at	Q4_K_M
System RAM	16 GB
Record updated	2024-05-13

Licence

Yi License — commercial use permitted. Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

Quant	Weights	VRAM needed	Est. speed	Fit on 24 GB
Q2_K	2.9 GB	4.5 GB	~151 tok/s (est.)	Fits comfortably
Q3_K_M	3.8 GB	5.4 GB	~129 tok/s (est.)	Fits comfortably
Q4_K_M	5.3 GB	6.9 GB	~102 tok/s (est.)	Fits comfortably
Q5_K_M	6.3 GB	7.9 GB	~90 tok/s (est.)	Fits comfortably
Q6_K	7.2 GB	8.8 GB	~81 tok/s (est.)	Fits comfortably
Q8_0	9.4 GB	11.0 GB	~66 tok/s (est.)	Fits comfortably
F16	17.7 GB	19.3 GB	~38 tok/s (est.)	Fits comfortably

Want the memory numbers alone, at every quantization level and your own context length? Use the Yi 1.5 9B Chat VRAM calculator.

Buy This HardwareIntel Arc B570 10GB — 10 GB VRAM · 150 W board power Deploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Yi 1.5 9B Chat is the Intel Arc B570 (10 GB).

Affiliate disclosure: Some links on this page are affiliate links — if you buy through them, LLM Configurator may earn a commission at no extra cost to you. As an Amazon Associate, LLM Configurator earns from qualifying purchases.

Intel Arc B570 10GB

10 GB VRAM · 150 W board power

2026 prices are volatile — check the current listing.

Check price on Amazon

How to Run Yi 1.5 9B Chat

Install Ollama, then run:

ollama run yi:9b

Weights on Hugging Face: 01-ai/Yi-1.5-9B-Chat.

Best for: chat, coding.

Can I Run Yi 1.5 9B Chat on My GPU?

Other Yi 1.5 Family Sizes

Yi 1.5 34B Chat — about 22 GB VRAM at Q4_K_M

Yi 1.5 9B Chat — Frequently Asked Questions

How much VRAM does Yi 1.5 9B Chat need?

About 6 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.

Does Yi 1.5 9B Chat run on an RTX 4090 (24 GB)?

Yes. Yi 1.5 9B Chat needs about 6 GB at Q4_K_M, inside a 24 GB card, at an estimated 102 tokens/sec.

How do I run Yi 1.5 9B Chat locally?

Install Ollama and run `ollama run yi:9b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Yi 1.5 Family come in?

Yi 1.5 34B Chat (22 GB), Yi 1.5 9B Chat (6 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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