GeForce RTX 5060 vs GeForce RTX 4060 for Local AI

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Which GPU is better for local AI workloads?

Both cards have 8GB VRAM, which caps them at 7B–8B LLMs at Q4 and SD 1.5/SDXL with optimizations. The 5060's 65% bandwidth jump makes those workloads noticeably faster. If you can buy either at $299, the 5060 is strictly better for AI.

Spec comparison: what actually differs

The table below is computed live from our hardware database. Positive deltas favor the GeForce RTX 5060.

Specification	GeForce RTX 5060	GeForce RTX 4060	Difference
VRAM	8	8	—
Memory bandwidth	448	272	+65%
Memory type	GDDR7	GDDR6	—
Memory bus	128	128	—
TDP	145	115	+26%
CUDA cores	3840	3072	+25%
Architecture	Blackwell	Ada Lovelace	—
Launch MSRP	$299	$299	—
Street price	$299	$299	—

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

What about price?

Both launched at $299 MSRP.

Which one should you buy for LLMs and image generation?

NVIDIA · 2025

GeForce RTX 5060

Buy the 5060 for free performance at equal price.

Full specs & benchmarks →

NVIDIA · 2023

GeForce RTX 4060

Buy a used 4060 only under $230; new, the 5060 wins outright.

Full specs & benchmarks →

Is it faster for LLM inference?

Both max out at 8B-class models in 8GB; the 5060 decodes them faster (448 vs 272 GB/s).

How does it handle image generation?

SDXL runs on both with optimizations; the 5060 is faster. Neither is comfortable for Flux.

Which AI models fit on each card?

Computed from our model VRAM database at Q4 quantization: GeForce RTX 5060 has 8 GB, GeForce RTX 4060 has 8 GB.

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

RTX 5060 vs 4060 — same price, which for AI?

The 5060: identical 8GB capacity but 448 vs 272 GB/s bandwidth means every AI workload that fits runs faster.

Is 8GB VRAM enough for local AI?

For 7B–8B LLMs at Q4 and SD 1.5: yes. For 14B LLMs or Flux: no — step up to a 16GB card like the 5060 Ti 16GB.