Can the GeForce RTX 3090 run Stable Diffusion 3.5 Large?
Stable Diffusion 3.5 Large runs locally on an 8 GB GPU at Q4, which needs about 7.3 GB of VRAM for the 8-billion-parameter MMDiT weights plus activation overhead. The FP16 model needs about 19.6 GB, so a 24 GB GPU such as the RTX 3090 or RTX 4090 runs SD 3.5 Large at FP16 with the T5 encoder offloaded.
At Q4_K_M quantization with 16,384 context, the Stable Diffusion 3.5 Large requires approximately 7.28GB of VRAM. The GeForce RTX 3090 has 24GB available (16.72GB headroom).
VRAM Breakdown
| Component | Size (GB) | Source |
|---|---|---|
| Model weights (Q4_K_M) | 4.8 | calculated |
| Loading overhead (10%) | 0.48 | calculated |
| Activation overhead | 2.0 | vendor_spec |
| Total required | 7.28 | |
| GPU memory available | 24 | vendor_spec |
| Headroom / shortfall | +16.72 |
Quantization Options
| Quant | Weights (GB) | Total @ 4K (GB) | Total @ 32K (GB) | Fits GeForce RTX 3090? |
|---|---|---|---|---|
| Q4_K_M | 4.8 | 7.28 | 7.28 | Yes |
| Q5_K_M | 5.7 | 8.27 | 8.27 | Yes |
| Q6_K | 6.6 | 9.26 | 9.26 | Yes |
| Q8_0 | 8.5 | 11.35 | 11.35 | Yes |
| FP16 | 16 | 19.6 | 19.6 | Yes |
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If It Doesn't Fit: Alternatives
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Frequently Asked Questions
Can the Stable Diffusion 3.5 Large run on 24GB VRAM?
Yes. At Q4_K_M quantization with 4K context, the Stable Diffusion 3.5 Large needs approximately 7.28GB. Your 24GB of usable memory has 16.72GB headroom.
What is the maximum context length I can use on the GeForce RTX 3090?
The Stable Diffusion 3.5 Large supports up to 32,768 tokens of context. Larger context increases KV-cache memory requirements. At 4K context the model needs ~7.28GB; at 32K it needs more.
Which quantization should I use with the GeForce RTX 3090?
Q4_K_M is the recommended starting point — it offers the best speed-to-quality tradeoff. If you have VRAM headroom, Q6_K or Q8_0 improves quality at the cost of speed. FP16 is only for inference servers with ample memory.
How much VRAM does Stable Diffusion 3.5 Large need?
Stable Diffusion 3.5 Large needs about 7.3 GB of VRAM at Q4 and about 19.6 GB at FP16 for the diffusion model alone, plus up to 9.4 GB for the T5-XXL text encoder at FP16 unless you offload it to system RAM.
Can an RTX 3060 12GB run SD 3.5 Large?
Yes, at Q4 or FP8 quantization with the T5 encoder offloaded to CPU, which needs about 7.3–11 GB of VRAM. FP16 does not fit 12 GB, so expect slower first-token latency from the offloaded encoder.
Related Pages
Full Stable Diffusion 3.5 Large fit page · All AI models · GeForce RTX 3090 specs · VRAM calculator
VRAM figures are calculated from model architecture parameters using established formulas. Benchmark data is measured and cited per row. GPU memory is vendor_spec from manufacturer datasheets.