DeepInfra raises $107M Series B to scale the inference cloud — read the announcement

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 👋
Kimi K2.6 API Benchmarks: Latency, TPS & Cost Analysis (2026)<p>About Kimi K2.6 Kimi K2.6 is an open-source frontier model from Moonshot AI, released on April 20, 2026. It is a native multimodal agentic model built for long-horizon coding, autonomous execution, and swarm-based task orchestration. The model uses a Mixture-of-Experts (MoE) architecture with 1 trillion total parameters and 32 billion activated parameters per token, using […]</p>
Best SaaS Tools and API Providers for MiMo-V2.5<p>As LLM architectures grow increasingly complex, the introduction of the MiMo-V2.5 series represents a significant step forward in multimodal capabilities and massive context handling. Integrating a model with a 1M-token context window and native multimodal support (image, video, audio, text) introduces substantial infrastructure considerations. For developers and enterprise architects, the priorities are clear: managing inference […]</p>
Build a RAG App With DeepInfra and LangChain<p>Ask a base language model about your company’s refund policy and it will answer with confidence, fluency, and no idea what your policy actually says. The facts live in your PDFs, your internal wiki, and your ticket history, none of which the model has ever seen during training. Retrieval-augmented generation closes that gap by fetching […]</p>
© 2026 DeepInfra. All rights reserved.