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Intel Arc B580 for local LLMs

Written by Jakub Rusinowski · Last updated

With 12 GB at 456 GB/s, the Intel Arc B580 runs 69 catalogued models at Q4_K_M with 8K context. The largest that fits is Gemma 3 12B Instruct (~11.1 GB), and the top pick is Cosmos 3 Nano at 24–50 tok/s.

Surprisingly capable for AI at $249. 12 GB VRAM with OpenVINO/IPEX-LLM acceleration. Works with Ollama on Windows and Linux. Best Intel GPU for local AI in 2024–2025.

Models that run on the Intel Arc B580

Q4_K_M, 8K context, 12 GB usable. Ranked by quality and speed.

ModelVRAMSpeed
Cosmos 3 Nano
Cosmos 3
10.5 GB24–50 tok/s
Ministral 3 14B
Ministral 3
9.3 GB16–34 tok/s
DeepSeek R1 Distill Qwen 14B
DeepSeek R1
10.6 GB16–34 tok/s
Gemma 4 12B (Unified)
Gemma 4
8 GB18–38 tok/s
Mistral NeMo 12B
Mistral Family
9.4 GB18–38 tok/s
Bielik PL 11B v3.0 Instruct
Bielik
7.4 GB20–41 tok/s
Llama 3.2 Vision 11B
Llama 3.2 Vision
8.5 GB20–42 tok/s
Llama 3.2 11B Vision Instruct
Llama 3.2 Family
8.5 GB20–42 tok/s
Falcon 3 10B Instruct
Falcon 3
8.4 GB21–43 tok/s
Qwen 3.5 9B
Qwen 3.5
6.5 GB26–54 tok/s
GLM-4 9B
GLM-4.7 / GLM-Z1
6.2 GB23–48 tok/s
K2 Horizon 7B
K2 Horizon
7.4 GB23–48 tok/s
Showing 12 of 69

Buy it or rent the same memory

Buy the card, or rent a GPU with the same memory by the hour to try models first.

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Intel Arc B580 12GB
12 GB VRAM · 190 W board power
2026 prices are volatile — check the current listing.

Speed vs other GPUs

Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated

Specifications

Specs last updated 2026-07-12.

Memory
12 GB
Memory bandwidth
456 GB/s
Architecture
Xe2 Battlemage BMG-G21
Series
Arc Battlemage
Board power
190 W
Release year
2024
Launch price
$249
Usable for models
12 GB
Best for8B modelsbudget optionWindows AI
Recommended first model (Ollama)

Similar GPUs

Frequently asked questions

Can the Intel Arc B580 run local LLMs?

Yes. With 12 GB (12 GB usable by a model) it runs 69 of the catalogued models at Q4_K_M with 8K context; the largest is Gemma 3 12B Instruct, needing about 11.1 GB.

How fast is the Intel Arc B580 for AI inference?

It is estimated to run Llama 3.1 8B at 28–57 tok/s at Q4_K_M. Llama 3.3 70B does not fit: it needs about 44 GB against 12 GB usable. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.

What LLMs can I run on 12 GB?

Among the best that fit: Cosmos 3 Nano, Ministral 3 14B, DeepSeek R1 Distill Qwen 14B, Gemma 4 12B (Unified), Mistral NeMo 12B. The quickest start is Ollama: ollama run llama3.1:8b.