🐙 GPU COMPARISON MATRIX FOR AI / LLM WORKLOADS
Detailed technical comparison between five graphics cards: RTX 3060 12GB, RTX 5060 Ti 16GB, 9060 XT 16GB, Arc A770 16GB, and Arc B60 24GB, focusing on core metrics for AI, Deep Learning, and Local LLM deployments.
📊 Detailed Comparison Matrix
| Metric | NVIDIA GeForce RTX 3060 | NVIDIA GeForce RTX 5060 Ti | AMD Radeon RX 9060 XT | Intel Arc A770 (Graphics) | Intel Arc B60 (Workstation) |
|---|---|---|---|---|---|
| 1. VRAM Capacity | 12 GB GDDR6 | 16 GB GDDR7 | 16 GB GDDR6 | 16 GB GDDR6 | 24 GB GDDR6 |
| 2. Memory Speed | 15 Gbps (Bus: 192-bit) (Bandwidth: 360 GB/s) |
28 Gbps (Bus: 128-bit) (Bandwidth: 448 GB/s) |
16 Gbps (Bus: 128-bit) (Bandwidth: 320 GB/s) |
17.5 Gbps (Bus: 256-bit) (Bandwidth: 560 GB/s) |
19 Gbps (Bus: 192-bit) (Bandwidth: 456 GB/s) |
| 3. AI Compute (INT8 TOPS) | ~244 TOPS (Tensor Cores Gen 3) |
~759 TOPS (Tensor Cores Gen 5) |
~410 TOPS (RDNA 4 AI Accelerators) |
~256 TOPS (XMX Engines) |
~197 TOPS (XMX Engines Gen 2) |
| 4. Release Date | Q1 / 2021 | Q1 / 2025 | Q1 / 2025 | Q4 / 2022 | Q1 / 2025 |
💡 Quick Analysis for AI / Local LLM Engineers
-
VRAM & Model Capacity:
- The Intel Arc B60 stands out with its massive 24GB VRAM, matching upper-tier workstation cards in capacity. This allows it to comfortably host larger models (up to quantized 32B or heavily compressed 70B models) entirely within the GPU memory.
- The 5060 Ti, 9060 XT, and A770 sit comfortably at 16GB VRAM, which is the ideal sweet spot for running mid-sized models like Llama-3-8B or Qwen-2.5-14B without system RAM spillover.
- The RTX 3060 falls behind with 12GB, but remains a budget-friendly entry-level gateway card.
-
Memory Bandwidth (Token Generation Speed):
- The older Intel Arc A770 still holds the highest raw bandwidth (560 GB/s) due to its unconstrained 256-bit bus width, ensuring fluid data transfer during inference loops.
- The Arc B60 sits at 456 GB/s; even with its 24GB capacity, the 192-bit bus acts as a subtle speed limit compared to high-end architectures.
- The RTX 5060 Ti achieves a highly efficient 448 GB/s by leveraging next-gen GDDR7 28 Gbps modules, overcoming its narrow 128-bit bus constraint.
- The RX 9060 XT is the most bottlenecked here at 320 GB/s, which slightly bottlenecks its token-per-second output during pure LLM inference tasks.
-
Raw Inference Performance (INT8 TOPS):
- The RTX 5060 Ti absolutely obliterates the field with a staggering 759 TOPS, making it the premier choice for fine-tuning, computer vision, and heavy image generation loops.
- The RX 9060 XT occupies a strong mid-range position at ~410 TOPS, representing a substantial compute upgrade for AMD's mainstream platform.
- The Intel Arc B60 significantly underdelivers in compute density, dropping below 200 TOPS—effectively losing to both its predecessor (A770) and even the aging RTX 3060 in raw matrix mathematical operations.
-
Software Ecosystem & Compatibility:
- NVIDIA (3060, 5060 Ti): Seamless out-of-the-box operation natively powered by CUDA. 100% day-one compatibility with major frameworks (PyTorch, HuggingFace, vLLM).
- AMD (9060 XT): Relies on ROCm. Highly performant and native on Linux-based environments (via Ollama or Llama.cpp), though Windows support requires slightly more setup.
- Intel (A770, B60): Requires reliance on the OneAPI / OpenVINO toolkit or IPEX (Intel Extension for PyTorch), demanding a higher degree of manual environment configuration and command-line troubleshooting.