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.

dejaguarkyngPlatform engineer, Jungle GridPublished April 23, 2026Reviewed April 23, 2026
Price FLUX.1-devEstimate cost
10-12 GB
INT4 start

Approximate starting range before runtime headroom.

22-24 GB
FP16 start

Useful for accuracy-first deployments.

RTX 4090 24GB or L40S-class route
Safe GPU floor

A strong default when you want one safe answer fast.

Direct answer

The fast answer for FLUX.1-dev

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.

Quick answer

FLUX.1-dev fits most cleanly when you start from VRAM, not brand names.

FLUX.1-dev usually needs about 10-12 GB in INT4, 14-16 GB in INT8, and 22-24 GB in FP16. A safe starting route is RTX 4090 24GB or L40S-class route.

For FLUX.1-dev, the route decision starts with memory fit. The model usually needs about 10-12 GB in INT4, 14-16 GB in INT8, and 22-24 GB in FP16 before you add runtime headroom.

  • Safe starting GPU: RTX 4090 24GB or L40S-class route
  • Best general production routes: RTX 4090 24GB, L40S 48GB, A10G 24GB
  • Add headroom for runtime behavior instead of treating the model size as the whole answer.

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.

PrecisionApproximate VRAMTypical route
INT410-12 GBCheapest healthy route when quality holds
INT814-16 GBBalanced production starting point
FP1622-24 GBAccuracy-first route with more headroom

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

About the author

dejaguarkyng

Platform engineer, Jungle Grid

Platform engineer documenting Jungle Grid's routing, pricing, and execution workflow from inside the product and codebase.

  • Maintains Jungle Grid's public landing content, product docs, and SEO content library in this repository.
  • Builds across the routing, pricing, and developer-facing product surfaces that the public site describes.

Why trust this page

This content is based on current Jungle Grid product behavior, public docs, and the live pricing and routing surfaces used throughout the site.

  • FLUX.1-dev route guidance here uses the current model library values stored in Jungle Grid's public landing app.
  • Cost and fit explanations align with the workload-first execution flow and live estimator exposed on the pricing surface.
  • This page is reviewed against the current public docs and model-route assumptions used throughout the site.
PricingOpen the pricing estimatorDocsRead the execution docsModelsBrowse the model hub

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.

Open the estimatorRun this workload
CostCost to run FLUX.1-devCheck the operating range and what changes the bill in production.DocsDocs and execution workflowInspect the API, CLI, and portal paths if you want to run the model immediately.

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.