Flux.1-Dev: An Introduction

Flux.1 is a new series of text-to-image models from Black Forest Labs that has set the new standard in quality and prompt adherence, and it can even render legible text. The Flux.1-Dev version of the model – a 12 billion parameter rectified flow transformer – generates high quality images in about 20 steps, and is released under a non-commercial license. In this benchmark, we measure the speed and cost performance of this new model on SaladCloud.

* An earlier benchmark of Flux.1-Schnell delivered 5243 images per dollar on Saladcloud.

Benchmark Design

The benchmark was conducted using k6, a modern load testing tool from Grafana Labs, to simulate a gradually increasing load from 7 to 12 virtual users over approximately 1.9 hours. See the exact configuration in GitHub. The test environment consisted of a container group on SaladCloud with 8-10 replicas (most commonly running 9 replicas).

Each virtual user submitted continuous consecutive image generation requests to the container group, and response time and failures were measured. Image generation requests consisted of 20 steps at a resolution of 1024×1024.

Each node was configured with

• NVIDIA RTX 4090 (24GB)
• 4 vCPUs
• 30GB Ram
• 1GB ephemeral storage

Deploying Flux.1-Dev on SaladCloud

To reproduce this benchmark, deploy the “Flux.1-Dev (FP8) – ComfyUI API” recipe from the “Create container group” page in the SaladCloud portal. Set the priority to “Batch” to optimize for cost-effectiveness.

Benchmark results

Conclusion

Deploying Flux.1-Dev on RTX 4090 (24 GB) GPUs on SaladCloud (batch priority) delivers 992 images per dollar. As with other text-to-image models on SaladCloud, deploying Flux.1-Dev in production results in more inferences per dollar and significant cost savings. Cost per image is just $0.00101.

The Flux1-Dev model demonstrates impressive stability and efficiency in this benchmark. With a 99.78% success rate and consistent response times averaging under 18 seconds, the model can readily be used for production deployments. The system showed moderate scalability, maintaining performance as virtual users increased from 7 to 12, with peak throughput achieved at 10 VUs. Under sudden spikes of traffic, an increased timeout and error rate should be expected.

Interested in free credits to try SaladCloud for Image Generation? Contact our support team today.