Compare · GPUs
Arc B580 vs RTX 3060 for local LLMs
Both fit the same 16 models, but the Arc B580 generates about 27% faster thanks to 456 GB/s of memory bandwidth versus 360 GB/s.
Both fit the same 16 models, but the Arc B580 generates about 27% faster thanks to 456 GB/s of memory bandwidth versus 360 GB/s.
Every model at 8K context with the best quantization that fits. Offload assumes 32 GB of system RAM. Green marks the better result. Rows where the two differ come first.
| Model | Arc B580 | RTX 3060 |
|---|---|---|
| Qwen3 0.6B | Runs~470 tok/sQ8_0 | Runs~370 tok/sQ8_0 |
| Gemma 3 1B | Runs~280 tok/sQ8_0 | Runs~220 tok/sQ8_0 |
| Llama 3.2 1B | Runs~230 tok/sQ8_0 | Runs~180 tok/sQ8_0 |
| Llama 3.2 3B | Runs~87 tok/sQ8_0 | Runs~69 tok/sQ8_0 |
| Phi-4 Mini 3.8B | Runs~74 tok/sQ8_0 | Runs~58 tok/sQ8_0 |
| Qwen3 4B | Runs~70 tok/sQ8_0 | Runs~55 tok/sQ8_0 |
| Gemma 3 4B | Runs~65 tok/sQ8_0 | Runs~51 tok/sQ8_0 |
| Qwen3.5 4B | Runs~60 tok/sQ8_0 | Runs~47 tok/sQ8_0 |
| Mistral 7B v0.3 | Runs~39 tok/sQ8_0 | Runs~31 tok/sQ8_0 |
| Qwen2.5-Coder 7B | Runs~37 tok/sQ8_0 | Runs~29 tok/sQ8_0 |
| Llama 3.1 8B | Runs~35 tok/sQ8_0 | Runs~28 tok/sQ8_0 |
| DeepSeek-R1 Distill 8B | Runs~35 tok/sQ8_0 | Runs~28 tok/sQ8_0 |
| Qwen3 8B | Runs~34 tok/sQ8_0 | Runs~27 tok/sQ8_0 |
| Qwen3.5 9B | Runs~39 tok/sQ6_K | Runs~30 tok/sQ6_K |
| Gemma 4 12B | Runs~42 tok/sQ4_K_M | Runs~33 tok/sQ4_K_M |
| Gemma 3 12B | Offload~6.2 tok/sQ4_K_M | Offload~4.9 tok/sQ4_K_M |
| Mistral Nemo 12B | Runs~41 tok/sQ4_K_M | Runs~33 tok/sQ4_K_M |
| Phi-4 14B | Offload~5.1 tok/sQ4_K_M | Offload~4.0 tok/sQ4_K_M |
| Qwen3 14B | Offload~5.1 tok/sQ4_K_M | Offload~4.0 tok/sQ4_K_M |
| DeepSeek-R1 Distill 14B | Offload~5.1 tok/sQ4_K_M | Offload~4.0 tok/sQ4_K_M |
| gpt-oss 20B | Offload~10 tok/sQ4_K_M | Offload~8.6 tok/sQ4_K_M |
| Codestral 22B | Offload~3.2 tok/sQ4_K_M | Offload~2.7 tok/sQ4_K_M |
| Mistral Small 3 24B | Offload~2.9 tok/sQ4_K_M | Offload~2.5 tok/sQ4_K_M |
| Devstral Small 24B | Offload~2.9 tok/sQ4_K_M | Offload~2.5 tok/sQ4_K_M |
| Gemma 4 26B-A4B (MoE) | Offload~9.7 tok/sQ4_K_M | Offload~8.7 tok/sQ4_K_M |
| Gemma 3 27B | Offload~2.4 tok/sQ4_K_M | Offload~2.2 tok/sQ4_K_M |
| Qwen3.6 27B | Offload~2.5 tok/sQ4_K_M | Offload~2.2 tok/sQ4_K_M |
| Qwen3 30B-A3B (MoE) | Offload~11 tok/sQ4_K_M | Offload~10 tok/sQ4_K_M |
| Qwen3-Coder 30B-A3B | Offload~11 tok/sQ4_K_M | Offload~10 tok/sQ4_K_M |
| Gemma 4 31B | Offload~2.1 tok/sQ4_K_M | Offload~1.9 tok/sQ4_K_M |
| Qwen3 32B | Offload~2.0 tok/sQ4_K_M | Offload~1.8 tok/sQ4_K_M |
| DeepSeek-R1 Distill 32B | Offload~2.0 tok/sQ4_K_M | Offload~1.8 tok/sQ4_K_M |
| Qwen2.5-Coder 32B | Offload~2.0 tok/sQ4_K_M | Offload~1.8 tok/sQ4_K_M |
| Qwen3.6 35B-A3B (MoE) | Offload~12 tok/sQ4_K_M | Offload~11 tok/sQ4_K_M |
| Llama 3.3 70B | Won’t fit | Won’t fit |
| DeepSeek-R1 Distill 70B | Won’t fit | Won’t fit |
| Llama 4 Scout 109B-A17B | Won’t fit | Won’t fit |
| gpt-oss 120B | Won’t fit | Won’t fit |
| Qwen3 235B-A22B (MoE) | Won’t fit | Won’t fit |
Which should you buy?
The Arc B580 is the better card for local AI. Both fit the same 16 models, but the Arc B580 generates about 27% faster thanks to 456 GB/s of memory bandwidth versus 360 GB/s.
Software matters as much as memory. NVIDIA cards work out of the box with Ollama, LM Studio and llama.cpp through CUDA. AMD cards run through ROCm or Vulkan and Intel Arc through Vulkan or IPEX-LLM; both work, but setup takes longer and new features usually land on NVIDIA first.
See every result on its own page: Arc B580 and RTX 3060.
Questions
Is the Arc B580 or the RTX 3060 better for running LLMs?
The Arc B580 is the better card for local AI. Both fit the same 16 models, but the Arc B580 generates about 27% faster thanks to 456 GB/s of memory bandwidth versus 360 GB/s.
Which models can the Arc B580 run that the RTX 3060 can't?
None. Both cards fit the same models; the difference is speed.
Does the Arc B580 or RTX 3060 need anything else to run local AI?
Only the software. Install Ollama or LM Studio, pick a model that fits in VRAM, and it runs on the GPU. 32 GB of system RAM helps when a model spills over, but that path is much slower.
More comparisons
Estimates from memory size and bandwidth at 8K context. Real speed varies with software, drivers and settings.