Model requirements
FLUX.1-dev GPU Requirements
FLUX.1-dev usually starts around 10-12 GB in INT4, 14-16 GB in INT8, and 22-24 GB in FP16. A safe production starting point is RTX 4090 24GB or L40S-class route.
Approximate starting range before runtime headroom.
Useful for accuracy-first deployments.
A strong default when you want one safe answer fast.
VRAM table
FLUX.1-dev memory and route profile
FLUX.1-dev is primarily used for image generation and creative pipelines. Most teams start with the quickest safe answer for memory fit, then compare which production routes make sense.
The ranges on this page are practical starting points for planning. Actual deployment requirements still depend on runtime overhead, batching, and the execution framework.
Execution notes
What changes the route in production
A memory-fit answer is only useful if the route is healthy. Pages like this should explain that fit, latency, and route quality all matter once the model goes live.
For FLUX.1-dev, the most relevant follow-up pages are the cost page and the run-without-GPU page because those are the next practical questions most teams ask.
- Creative generation tools
- Batch image pipelines
- Interactive image apps
Next step
Take FLUX.1-dev from research into a real route
Once the fit is clear, price the route and test one workload so you can compare the theory against live capacity.
Related pages
Related model pages
Use the sibling pages below to compare requirements, cost, and remote execution options for this model.
FAQ
Frequently asked
What GPU do I need for FLUX.1-dev?
A safe starting answer is RTX 4090 24GB or L40S-class route. Lighter quantized routes can use less memory, but that is the clean default most teams need first.
Can FLUX.1-dev run on a consumer GPU?
In many cases yes, especially with quantization. The safer answer still depends on the exact precision, runtime overhead, and traffic shape you expect in production.
Why should this page link to pricing and run-without-GPU pages?
Because the next user question after requirements is usually either cost or whether the model can be run remotely without buying hardware directly.