FLUX.1-schnell vs Qwen-Image
FLUX.1-schnell (11.9B parameters) and Qwen-Image (20.4B parameters) side by side: the memory each needs at every precision, what it costs to run on a live GPU, and the context window, KV cache and license where they are published. Numbers are computed from the models' published specs; this page does not rank quality.
Side by side
| Fact | FLUX.1-schnell | Qwen-Image |
|---|---|---|
| Parameters | 11.9B | 20.4B |
| Architecture | – | – |
| License | Apache 2.0 | Apache 2.0 |
| Published precision | BF16 | BF16 |
| VRAM needed, As published | 26.6 GB | 45.7 GB |
| VRAM needed, FP8 | 13.3 GB | 22.8 GB |
| VRAM needed, INT4 | 6.6 GB | 11.4 GB |
| Cheapest live fit, As published | RTX A6000 · $0.363/hr | RTX A6000 · $0.363/hr |
| Cheapest live fit, FP8 | RTX 4000 SFF Ada · $0.198/hr | RTX 4090 · $0.374/hr |
| Cheapest live fit, INT4 | RTX 4070 Super · $0.121/hr | RTX 4070 Super · $0.121/hr |
VRAM is the weight size at each precision times a flat 1.2 overhead; see the methodology. The FP8 and INT4 rows need a quantized checkpoint or an engine that quantizes on load. The fit is the lowest-priced single GPU type that holds the model at that precision, or the lowest-priced multi-GPU set (up to 8) when none does.
Which to pick
- FLUX.1-schnell needs less VRAM at its published precision (26.6 GB against 45.7 GB), so it fits on a smaller GPU.
These follow only from the facts in the table above. Whether either model does your task well is a separate question this page does not answer.
Keep reading
- FLUX.1-schnell: full VRAM table and live GPU fit
- Qwen-Image: full VRAM table and live GPU fit
- The FLUX model series
- The Qwen model series
- All models that fit in 32 GB
- All models that fit in 48 GB
Other comparisons
