Quick answer: Yes, the RTX 4060 Ti runs SD 3.5 — but which variant you own decides how happy you’ll be, and not in the way most guides say. sd3.5_large.safetensors is 16.5GB, so SD 3.5 Large at full precision does not fit a 16GB card either; what the 16GB card does comfortably is Large at FP8, around 8.3GB of weights with real room for a ControlNet. SD 3.5 Medium is trivial on it at 5.11GB. The 8GB card is fine for SD 3.5 Medium, tolerable for Large only if you drop to FP8 with offload, and painful anywhere near default settings. If you’re shopping right now, don’t bother saving $100 on the 8GB — you’ll regret it the first time you queue a Large batch.
NVIDIA GeForce RTX 4060 Ti 16GB
16GB GDDR616GB VRAM runs SD 3.5 Large at FP8 with headroom for a ControlNet, where the 8GB card has to offload. The cheapest card that makes the 8B model comfortable.
Affiliate links — we may earn a commission at no extra cost to you. Amazon ships globally; Shopee SG covers Singapore & ASEAN.
Who this article is for
You already own a 4060 Ti and want to know what SD 3.5 will actually feel like on it. Or you’re deciding between the 8GB and 16GB variants and everyone on Reddit keeps giving you contradictory advice. Either way, this is a budget-shopper’s post — I’m not going to pretend a $400 card competes with a 4090 or a 5080. It doesn’t. But it’s genuinely capable if you match the model to the VRAM. For the broader ranked list of SD 3.5 GPUs across price tiers, see the best GPU for SD 3.5 guide.
VRAM math: SD 3.5 Large vs Medium at every precision
SD 3.5 Large is 8B parameters (MMDiT architecture). Medium is 2.6B. The precision you choose is what makes or breaks the 4060 Ti fit.
| Variant | Precision | Weights | Total inference VRAM (1024x1024) |
|---|---|---|---|
| SD 3.5 Large | FP16 | 16.5 GB | ~19 GB |
| SD 3.5 Large | FP8 | ~8.3 GB | ~11 GB |
| SD 3.5 Large | Q4 GGUF | ~4.2 GB | ~6-7 GB |
| SD 3.5 Medium | FP16 | 5.11 GB | ~7-8 GB |
| SD 3.5 Medium | FP8 | ~2.6 GB | ~4-5 GB |
The two FP16 figures are the published files, checked 2026-09-13: sd3.5_large.safetensors is 16.5GB and sd3.5_medium.safetensors is 5.11GB. Everything below them is that file halved or quartered.
Read the “Total inference VRAM” column, not the weights column — text encoders, VAE, and working buffers push the real number 2-3 GB above the raw checkpoint size. That is what rules out Large at FP16 here: 16.5 GB of weights is already over a 16GB card before anything else loads. The 16GB card’s actual home is Large at FP8, about 11 GB all-in, which leaves room for a ControlNet. On an 8GB card even FP8 Large overflows, so it is Q4 GGUF or offloading. Medium runs on either card without drama. If you want the deeper VRAM breakdown across all SD variants, the How Much VRAM for Stable Diffusion piece has the full tables.
Generation times on both variants
Times below are modelled from each card’s memory bandwidth and how much of the pipeline stays resident (methodology) rather than measured on our own hardware, for 20 steps at 1024x1024 with no ControlNet. Treat the gap between the two cards as the reliable part.
RTX 4060 Ti 16GB:
- SD 3.5 Large FP16 — does not fit; 16.5 GB of weights against 16 GB of VRAM
- SD 3.5 Large FP8 — ~10-13 seconds per image, the configuration this card is for
- SD 3.5 Medium FP16 — ~5-7 seconds per image
- SD 3.5 Medium FP8 — ~4-5 seconds per image
RTX 4060 Ti 8GB:
- SD 3.5 Large FP16 — not a consideration at 16.5 GB
- SD 3.5 Large FP8 with sequential offload — ~28-40 seconds per image (workable, not fun)
- SD 3.5 Large Q4 GGUF — ~4.2 GB of weights, the only Large build that sits on this card
- SD 3.5 Medium FP16 — ~7-10 seconds per image
- SD 3.5 Medium FP8 — ~5-7 seconds per image
The 8GB card’s 128-bit bus is identical to the 16GB, so raw compute is the same — the gap is entirely about VRAM swapping. When Large FP8 spills to system RAM through PCIe, you’re paying 3x the time per image for no quality benefit.
Check RTX 4060 Ti 16GB price on Amazon→Buy on Shopee SG→Which variant should YOU buy?
You only care about SD 3.5 Medium. Either card is fine. The 8GB saves you ~$100 and Medium fits comfortably.
You want SD 3.5 Large as your daily driver. Buy the 16GB. Full stop — but for FP8, not FP16. At 8.3 GB of weights it leaves room for a ControlNet and keeps gen times in the range where iteration still feels like iteration. FP16 on Large is a 24GB-card question.
You already own the 8GB card. Stick to Medium for most work — at 5.11 GB it fits properly. For Large, the Q4 GGUF at ~4.2 GB is the build that actually sits on the card; FP8 with sequential offloading works but wants a queue you can walk away from.
You want future-proofing on a budget. The RTX 4070 Ti Super at 16GB GDDR6X is roughly 40% faster than the 4060 Ti for another $200-250. If your budget stretches, take it.
Common mistakes to avoid
- Buying the 8GB variant and immediately loading Large FP16. It won’t OOM cleanly — it’ll silently offload to system RAM, and you’ll spend a week thinking your GPU is broken. It’s not. You just bought the wrong SKU.
- Not using FP8 checkpoints on the 8GB card. If you’re stuck with 8GB and need Large, grab the FP8 or GGUF Q4 variants from HuggingFace. They cut VRAM in half with barely visible quality loss at 1024x1024.
- Assuming the 16GB card is “slow” because it’s a 4060 Ti. For SD 3.5 Large FP16, 14-18 seconds is faster than a 3090 running the same workload without FP8 tricks. The narrow bus hurts big-batch throughput; it doesn’t wreck single-image latency.
- Skipping ControlNet planning. SD 3.5 Large + ControlNet on the 16GB is tight — you’ll want FP8 for the base model if you need two control passes. Budget your VRAM before you queue the job.
Final verdict
| Variant | SD 3.5 Large FP16 | SD 3.5 Medium | Verdict |
|---|---|---|---|
| RTX 4060 Ti 16GB | Yes, ~14-18s/img | Yes, ~5-7s/img | Buy this |
| RTX 4060 Ti 8GB | No (offload only, painful) | Yes, ~7-10s/img | Only for Medium |
Skip the 8GB variant for SD 3.5 Large — the pain isn’t worth the $100 savings. If your budget is genuinely capped at $300, look at the RTX 3060 12GB instead of the 4060 Ti 8GB; 12GB with FP8 Large still beats 8GB with any precision for this workload. And if you’re weighing SD 3.5 against Flux on the same card, Can the RTX 4060 Ti Run Flux is the sibling piece worth a read.
NVIDIA GeForce RTX 4060 Ti 16GB
16GB GDDR6The 16GB variant is the cheapest GPU that runs SD 3.5 Large FP16 without quantisation gymnastics. Skip the 8GB — you'll spend the savings on regret.
Affiliate links — we may earn a commission at no extra cost to you. Amazon ships globally; Shopee SG covers Singapore & ASEAN.
Bottom line: The RTX 4060 Ti 16GB is the right budget card for SD 3.5 in 2026 — the 8GB is only worth it if you promise yourself you’ll never touch Large.