What GPU do I need to run Qwen/Qwen-Image-2.1-Turbo?
7.1B parameters, published in BF16. View on Hugging Face
Set up Qwen-Image-2.1-TurboQwen-Image-2.1-Turbo is published by Qwen on Hugging Face, with 45,079 downloads and 1,135 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for activation memory and allocator fragmentation. Diffusion and video models carry no KV-cache. The real driver of extra memory is output resolution and frame count, which this flat overhead does not model. Full formula and assumptions: methodology.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 13.3 GB | 15.9 GB | RTX 3090 | 1 | $0.162/hr |
| FP8 (quantized) | 6.6 GB | 8.0 GB | RTX 4070 | 1 | $0.154/hr |
| INT4 (quantized) | 3.3 GB | 4.0 GB | RTX 3060 | 1 | $0.110/hr |
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run Qwen-Image-2.1-Turbo at its published (BF16) precision: 1× RTX 3090, at $0.162/hr per GPU ($0.162/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Qwen-Image-2.1-Turbo: common questions
Does Qwen-Image-2.1-Turbo fit on a 16 GB GPU?
Yes. At BF16 it needs 15.9 GB of VRAM, so a 16 GB card holds it with 0.1 GB to spare. A 12 GB card is not enough for it at BF16.
What is the least VRAM Qwen-Image-2.1-Turbo can run in?
4.0 GB, at INT4 (quantized), which fits a 6 GB card, against 15.9 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.
Does quantizing Qwen-Image-2.1-Turbo lower the GPU bill?
Yes. At BF16 the cheapest live fit is one RTX 3090 at $0.162/hr. At INT4 (quantized) it drops to one RTX 3060 at $0.110/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More Qwen-Image models
- Qwen-Image-2.1-viggle-turbo (7.1B, BF16)
- Qwen-Image-2.1 (7.1B, BF16)
- Qwen-Image-2.1-Lightning-v2-RL (7.1B, F32)
- Qwen-Image-2.1-TailSteer (7.1B, BF16)
- Qwen-Image (20.4B, BF16)
Lineage
Based on Qwen-Image-2.1.
Alternatives at this size
Other models for text-to-image within about a third of Qwen-Image-2.1-Turbo's 7.1B parameters, from other model lines.
- Z-Image-Turbo (6.2B, F32)
- stable-diffusion-3.5-large (8.1B, BF16)
- Chroma1-HD (8.9B, BF16)
- FIBO (8.3B, BF16)
- Juggernaut-Z-Image (6.2B, F16)
More on Qwen-Image-2.1-Turbo
Fits on a 16 GB GPU at BF16: every model that fits in 16 GB.
Fits on an 8 GB GPU at FP8: every model that fits in 8 GB.
Best image generation models: how Qwen-Image-2.1-Turbo ranks against the rest.
Related reading: RTX 3090 pricing and specs, Fast diffusion inference on GPU VMs, and What AI inference is.
