Cohere32B~20 GB VRAM at Q4_K_M

Aya Expanse 32B — VRAM, speed & local setup

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

Written by Jakub Rusinowski · Last updated October 8, 2024

The flagship multilingual model. State-of-the-art non-English performance across 23 languages. For enterprises and researchers needing robust global language support with a 128k context window.

Aya Expanse 32B needs about 20 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.

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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	12.8 GB	~58 tok/s	Fits
Q3_K_M 3.41 bpw	15.9 GB	~47 tok/s	Fits
Q4_K_M 4.83 bpw	21.6 GB	~35 tok/s	Tight
Q5_K_M 5.67 bpw	25 GB	~4 tok/s	Offload
Q6_K 6.56 bpw	28.6 GB	~4 tok/s	Offload
Q8_0 8.50 bpw	36.5 GB	~3 tok/s	Offload
F16 16.00 bpw	66.7 GB	—	Too big

Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. Aya Expanse 32B VRAM calculator →

Get Aya Expanse 32B running

The cheapest catalogued GPU that runs Aya Expanse 32B is the AMD Radeon RX 7900 XTX (24 GB).

Buy this hardware AMD Radeon RX 7900 XTX 24GB — 24 GB VRAM · 355 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)

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AMD Radeon RX 7900 XTX 24GB

24 GB VRAM · 355 W board power

2026 prices are volatile — check the current listing.

Check price on Amazon

How to run Aya Expanse 32B

Install Ollama, then run:

$ollama run aya-expanse:32b

Weights on Hugging Face: CohereForAI/aya-expanse-32b ↗

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: 32 Billion
Context window: 128,000
Architecture: Dense
Provider: Cohere
Licence: CC-BY-NC
Practical deployment: Single consumer GPU
Specified at: Q4_K_M
System RAM: 32 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.

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Can I run Aya Expanse 32B on my GPU?

Other Aya Expanse sizes

Aya Expanse 8B~6 GB at Q4_K_M

Aya Expanse 32B — frequently asked questions

How much VRAM does Aya Expanse 32B need?

About 20 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 32B run on an RTX 4090 (24 GB)?

Yes. Aya Expanse 32B needs about 20 GB at Q4_K_M, inside a 24 GB card, at an estimated 35 tokens/sec.

How do I run Aya Expanse 32B locally?

Install Ollama and run `ollama run aya-expanse:32b`. 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.