FLUX.2 is live! High-fidelity image generation made simple.

Double exposure is a photography technique that combines multiple images into a single frame, creating a dreamlike and artistic effect. With the advent of AI image generation, we can now create stunning double exposure art in minutes using LoRA models. In this guide, we'll walk through how to use the Flux Double Exposure Magic LoRA from CivitAI with DeepInfra's deployment platform.
Once you navigate to this section, you will see a screen like this:
5. Write your preferred model name.
6. We'll use FLUX Dev for this LoRA. You can keep it as it is.
7. Add the following CivitAI URL: https://civitai.com/models/715497/flux-double-exposure-magic?modelVersionId=859666
8. Click "Upload" button, and that's it. VOILA!
Once LoRA processing has completed, you should navigate to
http://deepinfra.com/<your_name>/<lora_name>
When you have navigated, you should view our classical dashboard, but with your LoRA name.
Now let's create some stunning visuals... Let's break down this stunning example:
bo-exposure, double exposure, cyberpunk city, robot face

Notice how we use BOTH bo-exposure and double exposure. This combination is crucial - using both terms together gives you the best double exposure effect.
More tutorials are on the way. See you in the next one 👋
Accelerating Reasoning Workflows with Nemotron 3 Nano on DeepInfraDeepInfra is an official launch partner for NVIDIA Nemotron 3 Nano, the newest open reasoning model in the Nemotron family. Our goal is to give developers, researchers, and teams the fastest and simplest path to using Nemotron 3 Nano from day one.
Guaranteed JSON output on Open-Source LLMs.DeepInfra is proud to announce that we have released "JSON mode" across all of our text language models. It is available through the "response_format" object, which currently supports only {"type": "json_object"}
Our JSON mode will guarantee that all tokens returned in the output of a langua...
GLM-4.6 API: Get fast first tokens at the best $/M from Deepinfra's API - Deep Infra<p>GLM-4.6 is a high-capacity, “reasoning”-tuned model that shows up in coding copilots, long-context RAG, and multi-tool agent loops. With this class of workload, provider infrastructure determines perceived speed (first-token time), tail stability, and your unit economics. Using ArtificialAnalysis (AA) provider charts for GLM-4.6 (Reasoning), DeepInfra (FP8) pairs a sub-second Time-to-First-Token (TTFT) (0.51 s) with the […]</p>
© 2026 Deep Infra. All rights reserved.