Cohere8B~6 GB VRAM at Q4_K_M

Aya Expanse 8B — VRAM, speed & local setup

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

Written by Jakub Rusinowski · Last updated October 8, 2024

The compact multilingual powerhouse. Outperforms Llama 3 8B in 23 languages. Perfect for non-English applications — ideal for Arabic, Chinese, Hindi, French, Spanish, Russian, and more.

Aya Expanse 8B 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.

Logic82

Creative80

Coding72

VRAM and speed by quantization

Quoted against NVIDIA RTX 4090 (24 GB). Includes the KV cache at 8K context, so it reads higher than the headline figure.

Quant	VRAM	Speed (est.)	Fit
Q2_K 2.63 bpw	4.5 GB	~155 tok/s	Fits
Q3_K_M 3.41 bpw	5.3 GB	~134 tok/s	Fits
Q4_K_M 4.83 bpw	6.7 GB	~107 tok/s	Fits
Q5_K_M 5.67 bpw	7.6 GB	~95 tok/s	Fits
Q6_K 6.56 bpw	8.5 GB	~86 tok/s	Fits
Q8_0 8.50 bpw	10.4 GB	~70 tok/s	Fits
F16 16.00 bpw	17.9 GB	~41 tok/s	Fits

Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. Aya Expanse 8B VRAM calculator →

Get Aya Expanse 8B running

The cheapest catalogued GPU that runs Aya Expanse 8B is the Intel Arc B570 (10 GB).

Buy this hardware Intel Arc B570 10GB — 10 GB VRAM · 150 W board power Deploy in the cloud now RTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

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

As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.

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 Aya Expanse 8B

Install Ollama, then run:

$ollama run aya-expanse:8b

Weights on Hugging Face: CohereForAI/aya-expanse-8b ↗

Specifications

Curated — A hand-written entry from before this catalogue recorded its sources. The figures are long-standing but their provenance is not on file.

Parameters: 8 Billion
Context window: 8,192
Architecture: Dense
Provider: Cohere
Licence: CC-BY-NC
Practical deployment: Laptop
Specified at: Q4_K_M
System RAM: 16 GB
Record updated: 2024-10-08

LicenceCC-BY-NC-4.0Research / non-commercial only

Research / non-commercial only — this licence does NOT permit shipping a commercial product.

Quality and use cases

Scores as published by the model’s authors or an independent evaluator — quality, not throughput, and not measured by us.

Best formultilingualglobal chatnon english

Can I run Aya Expanse 8B on my GPU?

Other Aya Expanse sizes

Aya Expanse 32B~20 GB at Q4_K_M

Aya Expanse 8B — frequently asked questions

How much VRAM does Aya Expanse 8B 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 Aya Expanse 8B run on an RTX 4090 (24 GB)?

Yes. Aya Expanse 8B needs about 6 GB at Q4_K_M, inside a 24 GB card, at an estimated 107 tokens/sec.

How do I run Aya Expanse 8B locally?

Install Ollama and run `ollama run aya-expanse:8b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Aya Expanse come in?

Aya Expanse 8B (6 GB), Aya Expanse 32B (20 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.