Aya Expanse 8B

Overview

Cohere For AI's multilingual 8B covering 23 languages, outperforming Gemma 2 9B and Llama 3.1 8B in its language set. CC-BY-NC — non-commercial only.

When to pick this model

• You're doing multilingual research that doesn't require commercial use
• You need strong coverage of low-resource languages at the 8B tier
• You're benchmarking against Gemma 2 9B and Llama 3.1 8B on non-English tasks
• You're building an internal evaluation harness

VRAM requirements by quantization

Quantization	VRAM required
Q4_K_M (recommended)	5 GB
Q5_K_M	6 GB
Q8_0	9 GB
FP16 (no quantization)	16 GB

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

In practice, Aya Expanse 8B fits an 8 GB consumer card at Q4_K_M (5 GB). Stepping up to Q8_0 nearly doubles the footprint to 9 GB, and unquantized FP16 weights take 16 GB — plan your GPU around the Q4 or Q5 figure unless you specifically need the higher fidelity.

Without a GPU, Aya Expanse 8B needs roughly 10 GB of system RAM to run on CPU via llama.cpp or Ollama — workable for background jobs, but far slower than GPU inference. Throughput estimates from our compatibility engine: around 12 tokens/sec on entry-level GPUs, on the order of 35 tokens/sec on a mid-range card, and up to 90 tokens/sec on high-end hardware — assuming the chosen quantization fully fits in VRAM.

What hardware do you need

The table below matches Aya Expanse 8B to common GPU memory tiers, using the highest-fidelity quantization that fully fits each card class. Spilling layers to system RAM works but costs most of the speed, so size your card to the quantization you actually want to run.

GPU memory	Example cards	Best fit for Aya Expanse 8B
8 GB	RTX 5070 Laptop, RTX 5060, RTX 5060 Ti 8GB	Q5_K_M (6 GB used)
12 GB	RTX 5070, RTX 5070 Ti Laptop, RTX 4080 Laptop	Q8_0 (9 GB used)
16 GB	RTX 5080, RTX 4080 Super, Radeon RX 9070 XT	FP16 (16 GB used)
24 GB	RTX 4090, Radeon RX 7900 XTX, RTX 5090 Laptop	FP16 (16 GB used)
32 GB	RTX 5090	FP16 (16 GB used)

Which GPU should you buy to run Aya Expanse 8B?

To run Aya Expanse 8B locally at Q4, you need ~5 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).

Published benchmark scores

Benchmark	Score
Dolly (vs Llama 3.1 8B)	83.9

Scores published by the model author or aggregated from public leaderboards. Re-measured monthly by our editorial team.

Strengths

• 23 language coverage with strong low-resource performance
• Beats Gemma 2 9B and Llama 3.1 8B on multilingual benchmarks
• Particularly strong on low-resource languages
• Compact 8B footprint

Limitations

• CC-BY-NC 4.0 — no commercial deployment
• Only 8K context
• Outclassed by Qwen 3 8B on most general tasks

Typical workloads

In our catalog grid, Aya Expanse 8B is filed under Multilingual incl. FR, Compact Chat — the use cases where its size/quality trade-off makes the most sense. Its tags translate to concrete workloads: multilingual workloads.

Note the 8k-token context window — fine for short interactions, limiting for long documents or big retrieval contexts. It ships under the CC-BY-NC 4.0 license — commercial use is generally possible but read the specific terms before embedding it in a product.

Architecture & training

Architecture: Dense · 32 layers · 32 heads · SwiGLU · GQA · SentencePiece ~128k vocab

Training: 23 languages, multilingual focus.

Quick start

ollama run aya-expanse:8b

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.

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Frequently asked questions

How much VRAM does Aya Expanse 8B need?

At the recommended Q4_K_M quantization, Aya Expanse 8B needs about 5 GB of VRAM. Q8_0 takes 9 GB, and unquantized FP16 weights take 16 GB.

Can Aya Expanse 8B run without a GPU?

Yes — with roughly 10 GB of system RAM it runs CPU-only through llama.cpp or Ollama. Expect a fraction of GPU speed, which is fine for background or batch jobs but slow for interactive chat.

What context window does Aya Expanse 8B support?

Aya Expanse 8B supports a 8k-token context window (8,192 tokens).

Can I use Aya Expanse 8B commercially?

Aya Expanse 8B ships under the CC-BY-NC 4.0 license. Commercial use is generally permitted subject to its terms — review the license text before shipping a product.

How fast is Aya Expanse 8B on consumer hardware?

Our compatibility engine estimates on the order of 35 tokens/sec on a mid-range GPU and up to 90 tokens/sec on high-end cards, assuming the quantization fully fits in VRAM.

Which quantization of Aya Expanse 8B should I download first?

Start with Q4_K_M (5 GB) — the standard size/quality sweet spot. Step up to Q5_K_M or Q8_0 only if you have VRAM headroom. It already fits an 8 GB card at Q5_K_M.