Arc B580 vs GeForce RTX 5060 for Local AI

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Which GPU is better for local AI workloads?

Intel wins capacity (12 vs 8GB) and price; NVIDIA wins software maturity and equal bandwidth (448 GB/s each). If your models fit 8GB, the 5060 is the safer, faster-to-deploy pick; if you need 12B-class models under $300, the B580 is the only new card that holds them.

Spec comparison: what actually differs

The table below is computed live from our hardware database. Positive deltas favor the Arc B580.

Specification	Arc B580	GeForce RTX 5060	Difference
VRAM	12	8	+50%
Memory bandwidth	456	448	+2%
Memory type	GDDR6	GDDR7	—
Memory bus	192	128	—
TDP	190	145	+31%
CUDA cores	—	3840	—
Architecture	Battlemage	Blackwell	—
Launch MSRP	$249	$299	-17%
Street price	$249	$299	-17%

Specs from our sourced product database. See how we source data.

What about price?

Launch MSRP: $249 (B580) versus $299 (5060).

Which one should you buy for LLMs and image generation?

Intel · 2024

Arc B580

Buy the B580 for 12GB under $250.

Full specs & benchmarks →

NVIDIA · 2025

GeForce RTX 5060

Buy the 5060 for plug-and-play CUDA at the same bandwidth.

Full specs & benchmarks →

Is it faster for LLM inference?

B580 holds 12B at Q4; 5060 caps at 8B. llama.cpp works on both (Vulkan vs CUDA).

How does it handle image generation?

SDXL comfortable on B580's 12GB; 5060 needs optimizations. Setup friction favors NVIDIA.

Which AI models fit on each card?

Computed from our model VRAM database at Q4 quantization: Arc B580 has 12 GB, GeForce RTX 5060 has 8 GB.

Fit only on the Arc B580 (12 GB)

Gpt Oss 20B ✓ Maple Preview ✓ Ling Mini 2.0 ✓ Deepseek R1 Distill Qwen 14B ✓ Qwen3 14B ✓ Confucius4-T3PO ✓ WebWorld-14B ✓ ContextPilot 14B ✓ Phi 4 ✓ Phi 3 Medium ✓ Ministral 3 14B Instruct ✓ Ministral 3 14B Reasoning ✓

Fit on both cards

Gemma 3 12B Mellum 2.1 Thinking FLUX.1 dev Gemma 4 12B IT Ornith 1.5 9B OxCoder 9B Gemma 2 9B K2 Horizon 7B NeoHorse 1 9B Ministral 3 8B Reasoning Ministral 3 8B Instruct Granite 4.2 8B LFM2.5 8B A1B Qwen 3 8B ALoDLM 8B Deepseek R1 Distill Llama 8B Llama 3.1 8B Stable Diffusion 3.5 Large Gemma 4 E4B IT Edge0 8B A1B (preview) Ling-3.0-tiny Qwen2 5 7B ZGCM-1 7B Mistral 7B V03 Gemma 4 E2B IT K2 Horizon 3.7B Gemma 3 4B Ministral 3 3B Reasoning NeoHorse 1 4B Nanbeige4.2 3B Spark X2.5 4B Qwen3 4B Ministral 3 3B Instruct Granite 4.2 3B Stable Diffusion XL 1.0 Llama 3 2 3B Granite Swash 3B A600M LFM2.5 2.6B MiniCPM5 2B Qwen3 1 7B Spark X2.5 1.7B Whisper large-v3 Llama 3 2 1B K2 Horizon 0.9B Coqui XTTS-v2 Qwen3 0 6B GPT-X3 150M

Q4_K_M-equivalent sizes; context and quantization choices shift real limits. Check each model page for full quantization tables.

Frequently asked questions

Arc B580 or RTX 5060 for a first AI GPU?

RTX 5060 for ease: CUDA works everywhere. B580 if your budget is hard-capped at $250 and you want 12GB for 12B-class models.